WO2016176727A1

WO2016176727A1 - Operation scheduling of power generation, storage and load

Info

Publication number: WO2016176727A1
Application number: PCT/AU2016/050315
Authority: WO
Inventors: Rajab KHALILPOUR; Anthony Michael Vassallo
Original assignee: The University Of Sydney
Priority date: 2015-05-01
Filing date: 2016-04-29
Publication date: 2016-11-10

Abstract

A method of scheduling a community electricity network including two or more members in a community, each member having components including one or more of an electricity generation system, an energy storage system, an electricity load, and is electrically directly connected to at least another member. For each member, the method determines a respective first operating schedule of power flow of the components of the member and an electrical grid based on a respective forecast electricity production and/or consumption of the member while adjusting the electricity cost of the member towards a minimum and a respective second operating schedule of power flow of the components of the member and other members based on a forecast electricity production and/or consumption of the community to provide a respective second electricity cost of the member, wherein the total electricity cost of the members is less than a total of the first electricity cost.

Description

"Operation scheduling of power generation, storage and load" Cross-Reference to Related Applications

[1] The present application claims priority from Australian Provisional Patent

Application No 2015901569 filed on 1 May 2015, the content of which is incorporated herein by reference.

Technical Field

[2] The present disclosure generally relates to operation scheduling of power generation, storage and load of one or more members in a community. The disclosure relates to computer-implemented methods, software and computer systems that control and/or schedule the operation of power generation, storage and loads.

Background

[3] In a traditional electrical grid, power is supplied to users that, in turn, have a load that consumes the power. The supplier of the power, usually a power company associated with the electrical grid, charges the user typically based on an electricity price and the power consumed by the user.

[4] Due to technological advances, generation of electrical power, in general, is not limited to power companies. For example, renewable energy systems, such as photovoltaic (solar) systems and wind power systems may be owned and installed by private users, such as a household. That is, users with their own power generation systems may generate power to supply the user's load. Such private power generations systems may supply part of, in full, or in excess of the power needs of the user.

[5] A private power generation system of the user may suffer reliability issues in meeting the load requirements of the user at particular times. For example, a photovoltaic system relies on sunlight to generate power. During the night, or seasons with shorter daylight hours, a photovoltaic system by itself may not be able to meet the demands of the user's load. Conversely, there may be periods where a photovoltaic system generates more power than the contemporaneous load of the user such that there is excess power generated. [6] A user may mitigate such issues by including a local energy storage system, such as an electrical battery. Another means to mitigate these issues may include the user maintaining a connection to the electrical grid such that during times when the user's load exceeds the amount that can be produced by the private power generation system, the user can meet the demand by purchasing power from the grid at an electricity price from the grid. Conversely, when the user's private power generation system has excess power, the excess power can be sold back to the grid (usually to a power utility company) at a feed-in tariff.

[7] Thus users that have a private power generation system and are also connected to the grid may be, from the perspective of the electrical grid, both producers and consumers of electricity (i.e. "prosumers"). Such power generation systems that are distributed at multiple locations, as opposed to a centralised power plant, are known as distributed generation systems ("DG").

[8] The purchase and supply of power by a prosumer with an electrical grid may have some economic and technical disadvantages. In one scenario, the prosumer as an individual may not be in a strong bargaining position with a power company, and there may be a significant disparity between the grid electricity prices for purchasing power from the grid compared to the feed-in tariff for supplying power into the grid. In another example, the electricity price and the feed-in tariff may have varying time-of-use rates and the load and generation profile of the prosumer over time may not be economically advantageous.

Furthermore, there may be transmission losses associated with receiving and supplying power to and from the electrical grid.

[9] Any discussion of documents, acts, materials, devices, articles or the like which has been included in the present specification is not to be taken as an admission that any or all of these matters form part of the prior art base or were common general knowledge in the field relevant to the present disclosure as it existed before the priority date of each claim of this application.

[10] Throughout this specification the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps. Summary

[11] A method of scheduling a community electricity network including two or more members in a community. Each member has components including one or more of an electricity generation system, an energy storage system and an electricity load, and each member is electrically directly connected to at least one other member. The method comprises the step of determining, for each member, a respective first operating schedule of power flow of the components of the member and an electrical grid based on a respective forecast electricity production and/or consumption of the member, wherein determining the first operating schedule adjusts a respective first electricity cost of the member towards a minimum. The method further comprises the step of determining, for each member, a respective second operating schedule of power flow of the components of the member and other members of the community based on a forecast electricity production and/or consumption of the community to provide a respective second electricity cost of the member, wherein a total of the second electricity cost of the members is less than a total of the first electricity cost of the members.

[12] The method of scheduling may facilitate effective distribution of energy between the member's electricity resources, the community's electricity resources and the grid. For example, this may include a member receiving electricity from other members in the community rather than the grid. This may be advantageous as members of a community may be located geographically close to one another and therefore transmission and distribution losses (such as line loss) may be reduced when compared to receiving electricity from the grid. This method may also allow the community to reduce reliance on the grid as excess capacity of one member may be utilised by another member.

[13] In the method, the step of determining the second operating schedule may adjust the second operating schedule towards a maximum difference between: the total of the first electricity cost of the members of the community; and the total of the second electricity cost of the members of the community.

[14] In the method, the respective second electricity cost for each member to operate in the second operating schedule may be less than, or equal to, the respective first electricity cost for that member. [15] In the method, at least one member may be connected, separate from the electrically directly connection between members, to the electrical grid and the step of determining a respective second operating schedule further includes determining power flow with the electrical grid.

[16] In the method, the first and second operating schedules may be over a plurality of time periods, wherein the respective first and operating schedules include respective power flows that vary between at least two of the time periods.

[17] The method may further comprise sending, over a communications network, at least part of the second operating schedule to one or more members of the community.

[18] At least one member may have a controller to control power flow between two or more of: the electricity generation system of the member; the energy storage system of the member; the electricity load of the member; one or more other members of the community; and the electrical grid, and the method may further comprise: sending, over a communications network, at least part of the second operating schedule to the controller to control power flow in accordance with the at least part of the second operating schedule.

[19] In the method, the second electricity cost to operate in the second operating schedule for each member may comprise: adding a cost of electricity associated with power flow from other members of the community to the member; and deducting a price of electricity associated with power flow provided by the member to other members of the community, wherein cost and/or price of electricity associated with power flow between members of the community are determined at one or more community electricity prices.

[20] In the method, the second electricity cost to operate in the second operating schedule for each member may further comprise: adding a cost of electricity used by the member from the grid, calculated at grid electricity prices; and deducting a price of electricity provided by the member into the grid, calculated at feed -in tariffs, wherein the community electricity price(s) between members of the community are lower than feed-in tariffs of power provided by the member into the grid during corresponding time periods in the first and second operating schedules. [21] In one variation of the method, the second electricity cost does not include cost and/or price of electricity associated with power flow between one member to another member.

[22] A community electricity network for a plurality of members in a community comprising a plurality of controllers each associated with at least one member, wherein the controller controls power flow between two or more of: an electricity generation system of the at least one member; an energy storage system of the at least one member; an electricity load of the at least one member; one or more other members in the community; and the electrical grid. The community electricity network further comprises a first processing device to perform the method of scheduling a community network described above, wherein at least part of the second operating schedule is sent, over a communications network, to one or more of the plurality of controllers to control power flow in accordance with at least part of the second operating schedule.

[23] A controller for a member in a community including a plurality of members, wherein the controller of at least one member controls power flow between two or more of: an electricity generation system of the at least one member; an energy storage system of the at least one member; an electricity load of the at least one member; one or more other members in the community; and an electrical grid. The controller includes a second processing device to control power flow in accordance with at least part of the second operating schedule according to the method of scheduling a community network described above.

[24] The controller may have the second processing device configured to: receive, over a communications network, at least part of the second operating schedule.

[25] Alternatively, the controller may have the second processing device configured to: perform the method of scheduling a community network described above.

[26] A computer program comprising machine-executable instructions to cause a processing device to implement the method of scheduling a community network described above. [27] A method of operating a community electricity network comprising a plurality of members in a community. The method of operating a community electricity network comprises determining a second operating schedule in accordance with the method of scheduling a community network described above. The method further comprises sending, over a communications network, at least part of the second operating schedule to at least one of: one or more members of the community; and a representative of the community; an entity controlling at least part of the community electricity network, such that components of at least one member operate in accordance with at least part of the second operating schedule.

Brief Description of Drawings

[28] Examples of the present disclosure will be described with reference to:

[29] Fig. 1 is a schematic of power flow in a community electricity network;

[30] Fig. 2 is a flowchart of a method for scheduling a community electricity network;

[31] Fig. 3 is a schematic of a member having an electricity generation system, an energy storage system and an electricity load connected to a grid;

[32] Fig. 4 is a schematic of a community electricity network connected to a grid, where the electricity network includes a plurality of members connected by inter-member connections;

[33] Fig. 5 is a communications schematic of a community electricity network with a central first processing device;

[34] Fig. 6 is a communications schematic of an alternative community electricity network with a central controller;

[35] Fig. 7 is a communications schematic of an alternative community electricity network with decentralised controllers;

[36] Fig. 8 illustrates an example of a processing device; Fig. 9 illustrates power consumption of members in Example 1;

[38] Fig. 10 is a table showing the electricity production and consumption of members in scenario 2 of Example 1;

[3 ] Figs. 11a and 1 lb show an example of annual ambient temperature and global horizontal irradiation (GHI) for forecasting energy production in a photovoltaic electricity generation system in Example 1 ;

[40] Fig. 12 is a table showing the electricity production and consumption and respective costs in scenarios 1 to 3 in Example 1;

[41] Fig. 13 is a diagram representing energy exchange between members of the community having a community electricity network;

[42] Fig. 14 are charts illustrating the power bought from the grid and power sold to the grid in scenarios 1 to 3 in Example 1;

[43] Fig. 15 illustrates the average daily interaction of the members in scenarios 1 to 3 in Example 1;

[44] Fig. 16 is a table showing the electricity production and consumption and respective costs in cases 1 to 3 in Example 2;

[45] Fig. 17 illustrates the benefit of a member from the community network relative to the member's capital investment into electricity generation systems and energy storage systems (DGS) for the network;

[46] Fig. 18 is a table showing the electricity production and consumption and respective costs in Example 3;

[47] Fig. 19 is a table showing the electricity production and consumption and respective costs in Example 4; [48] Fig. 20 is a table showing the electricity production and consumption of a community in Example 5;

[49] Figs. 21(a) to 21(b) is a table showing the electricity production and consumption and respective costs in scenarios 1 to 3 in Example 5; and

[50] Fig. 22 is a diagram representing energy exchange between members of the community in Example 5.

Description of Embodiments

Overview of a community electricity network

[51] Figs. 1 and 4 illustrate a schematic of power flow in a community electricity network 1 for a community 3. The community 3 includes a plurality of members 5, where the members 5 may have components including one or more of an electricity generation system 7, an energy storage system 9 and an electricity load 11. Each member 5 is electrically directly connected to at least another member 5 which, in this is example, is provided by inter-member connections 4. The member 5 may also have a separate grid connection 6 to an electrical grid 13, separate to the inter-member connections 4, where the electrical grid 13 in addition provides power to locations and entities outside the community 3. As illustrated in Fig. 1, the members 5 may be electrically connected to each other, and/or the grid 13, via respective hubs 15 of each member 5. The components 7, 9, 11 and hub 15 of the member 5 may be connected to each other by intra-member connections 8 to facilitate power flow there between.

[52] That is, Fig. 1 illustrates three types of connections 4, 6 and 8. Firstly, intra-member connections 8 provide connections between components 7, 9, 11 and the hub 15 of a member 5. Secondly, inter-member connections 4 provide connections between members 5 of the community 3. Thirdly, grid connections 6 provide extra-community connections between the community 3 and the electrical grid 13 that is outside of the community 3.

[53] The electrical grid 13, also known as a "macrogrid", may be part of a wide area electrical grid operated by a public utility. In contrast, the community electricity network 1, also known as a "nanogrid" may be a community in a limited geographical area with electrically direct connections between members of the community. The electrically direct connection are in the form of inter-member connections 4, that are separate from (extra- community) grid connections 6 or the connections in the grid 13. That is, "electrically directly connected" means there are direct physical connections between members 5 that are separate from the macrogrid 13.

[54] For members 5 that have a respective electricity generation system 7, these members 5 have the capability of generating power to satisfy at least part of their electricity load 11. The electricity generation system 7 may also produce power that is distributed to other electrically directly connected members 5. The power from the electricity generation system 7 may also be fed into the electrical grid 13.

[55] Members 5 with energy storage systems 9 may store electricity for later use. For example, the energy storage system 9 may store excess power from the electricity generation system 7 of the member 5, or other members 5 in the community 3, or power from the electrical grid 13.

[56] Power flow, through connections 4, 6, 8, between components 7, 9, 11 of the member 5, other members 5, and the grid 13 may be controlled by a controller 16 as shown in Fig. 4. Each member 5 may have a respective controller 16, or alternatively, a controller 16 may be shared with two or more members 5. In yet another embodiment, the controller 16 may be centralised with control signals sent, through a communications network 205, to one or more components 7, 9, 11 or hub 15 of the members 5. Embodiments of the

communications network 205 between the controller and other elements of the system are described later in this description with reference to Figs. 5 to 7.

[57] Thus Fig. 1 illustrates a distributed generation system where electricity generation is distributed in multiple locations. The members 5 may be both consumers of electricity with their respective electricity load 11 and also producers of electricity with the electricity generation system 7. This may allow the community 3 to reduce reliance on the grid 13 to supply their energy needs. Overview of a method of scheduling the community electricity network

[58] A method 100 of scheduling the community electricity network 1 will now be described with reference to Fig 2. The method 100 may be performed by one or more processing devices 22, 201, 501 described below.

[59] The method includes the step 110 of determining a first operating schedule 110, for each member 5, that has a respective first electricity cost to that member 5. The first operating schedule include power flow of the components 7, 9, 11 of the member 5 and an electrical grid 13 based on forecast electricity production and/or consumption of that member.

Furthermore, determining the first operating schedule 110 adjusts the first electricity cost towards a minimum.

[60] Thus generally, in one example, the determined first operating schedule 110 and the corresponding first electricity cost provides a benchmark cost for each member 5 if the member operated on their own with the electricity grid 13.

[61] The method also includes the step 120 of determining a second operating schedule 120 for each member that has a respective second electricity cost to that member 5. The second operating schedule includes power flow of the components of the member and other members of the community based on forecast electricity production and/or consumption of the community 3. Determining the second operating schedule 120 includes determining a schedule where a total of the second electricity cost of the members is less than a total of the first electricity cost of the members 5.

[62] Thus generally in one example, the second operating schedule 120 is determined to provide an improved operating schedule for the member 5 with the constraint that the total second electricity cost will be less than the total benchmark first electricity cost. The second operating schedule takes into account the community 3 operating together and includes scheduling power between members in the community 3, which may be more beneficial than a particular member 5 that scheduling power (external to that member) to the grid 13 only.

[63] Since the total second electricity cost of the members 5 is less than the total of the first electricity cost of the members 5, the second determine schedule provides a net financial benefit (e.g. cost saving) to the community 3 compared with the members 5 that may otherwise be operating on their own. The financial benefit may be distributed to one or more members 5 as discussed later below. Furthermore, by scheduling power flow between members 5 of the community 3 through the direct inter-member connections 4, this may also reduce transmission and distribution losses (such as line losses) that may otherwise occur from directing power flow between users through the grid 13. This may have particular advantages where the members 5 of a community 3 are located in a relatively smaller geographical area compared to the area served by the grid 13. Furthermore, the power flow between members 5 in the community through the inter-member connections 4 may allow the path of power flow to circumvent grid connections 6 and the grid 13. This may be advantageous as power flow through grid connections 6 and the grid 13 may incur usage costs charged by a public utility company operating the grid connections and/or grid 13.

[64] It is to be appreciated that the first operating schedule 110 provides an indicative benchmark of the first electricity cost. Thus the first operating schedule 110 may include scheduling that is not actually used by the members 5. In contrast the second operating schedule 120 may provide an improved scheduling (over the first operating schedule 110) and it may be advantageous for members 5 of the community 3 to operate in accordance with the second operating schedule 120.

[65] The method 100 may include sending 130, over a communications network 205, at least part of the second operating schedule to be received 210 by a controller 16 of a member 5 as illustrated in Fig. 5. This allows the members 5, and in particular the components 7, 9, 11 of the members 5, to control power flow 220 in accordance with at least part of the received second operating schedule 120.

[66] In one variation, the method 100 may be sent to a representative of the community 3, who in turn sends at least part of the second operating schedule to the controller 16 of a member 5. In yet another alternative, the method 100 may include sending the second operating schedule to an entity exercising control over at least part of the community electricity network. In yet another variation or alternative, a controller 16 of a member 5 may perform the method 100 to determine the second operating schedule, and the controller 16 controls power flow in accordance with the at least part of the determined second operating schedule. These will be discussed in further detail below. [67] Each "member" may include a group of consolidated individual users that have a consolidated forecast production and/or consumption. This may also include consolidated components of the individual users in that group. For example, a community 3 may include multiple apartment blocks with each apartment block including multiple individual households, and each household having one or more respective electricity generation systems, energy storage system 9 and electricity load. In some examples, one of the apartment blocks may be considered as "a member" of the community with consolidated power forecast production and/or consumption of the individual households considered as the forecast for that member apartment. Similarly the consolidated components of individual households in the apartment (or common components in the apartment block) can be considered as the components of that member apartment.

Detailed description of elements of the community electricity network

[68] The elements of the community electricity network 1 will now be described in detail. (i) The controller 16

[69] The controller 16 includes a processing device 22. The processing device 22 may be in the form of a processing device 501 (illustrated in Fig. 8 and described in further detail below) that has an interface 540. The interface 540 of the controller 16 may provide control signals that control power flow. In one example, the control signals are provided to a switching device (such as a relay) that connect and disconnect connection 4, 6, 8 between the one or more components of the member 5, other members 5 and the grid 13. It is to be appreciated that other methods of connecting and disconnecting a connection 4, 6, 8 by a control signal may be used.

[70] The interface 540 of the controller 16 may also allow communication between the controller 16 and another processing device 201 (or other controller 16) over a

communications network 205 as shown in Fig. 5. This allows the controller 16 to receive, over the communications network 205, information such as at least part of the second operating schedule from a first processing device 201 as shown in Fig. 5. The controller 16, in turn, controls power flow through one or more of the connections 4, 6, 8 in accordance with at least part of the received second operating schedule. [71] In one variation, or alternative, the interface 540 may also allow the controller 16 to send information, over the communications network 205, to another processing device 201 (or other controller 16). In one example, the information sent may include sending at least part of the second operating schedule to another member 5, or a controller 16 of another member, or a third party. In another example, the information may include data associated with historical and/or forecast electricity production and/or consumption of member 5a, and/or other members 5 of the community 3, which in turn may be used by another processing device to perform the method 100 and determine one or more of the first and second operating schedules.

[72] The processing device 22 of the controller 16 of member 5a may, in one example, perform the method 100 to determine the second operating schedule for member 5a, as shown in Fig. 7. Member 5a may receive, over the communications network 205, data associated with historical and/or forecast electricity production and/or consumption of one or more members 5 of the community 3. At least part of this data may be used by the processing device 22 of the controller 16 to determine the second operating schedule. The processing device 22 of the controller 16 may send, over the communications network 205, the determined second operating schedule as discussed above.

[73] The controller 16 may include a memory 520 to store the second operating schedule or data 522 associated with historical and/or forecast electricity production and/or consumption of one or more members 5 of the community 3. The 520 may also include machine readable instructions 524 for the processor 510 to perform the method 100.

[74] Whilst in some examples, each member 5 may have a respective controller 16, it is to be appreciated that in other examples, a controller 16 may provide control signals to components of more than one member 5 (as shown in Fig 6).

(ii) The components 7, 9. 11 and hub 15 of the member 5

[75] The components 7, 9, 11 of a specific member (labelled as member 5a and referred to a member k in the equations described herein) from the community 3, will now be discussed with reference to Fig. 4. Member 5a may be a household that includes components of an electricity generation system 7, an energy storage system 9 and an electricity load 11. Member 5a may also include a hub 15 to which components 7, 9, 11 of member 5a are connected via at least some of the intra- member connections 8. The hub 15, in turn, may be connected to elements outside of member 5a, for example to another member 5 through inter- member connection 4 or to the electrical grid 13 through grid connection 6. Member 5a may also have a controller 16 to control the power flow through one or more of the connections 4, 6, 8.

[76] The electricity generation system 7 may include generation of electricity using renewable energy or non-renewable sources. Examples include systems that use solar power (such as a photovoltaic system), wind power (such as wind turbines or windmills) or hydropower (such as a hydroelectric system). Other examples include engine-generator combinations that use fuels such as diesel-electric generators. It is to be appreciated that other types of electricity generation systems 7 may be used.

[77] The energy storage system 9 may include a battery such as a rechargeable lead acid battery, lithium ion battery, nickel-metal hydride battery, nickel-cadmium battery, sodium- sulphur battery, vanadium redox battery, etc. In one example, the energy storage system 9 receives direct current for charging, and discharges direct current. In further examples, the energy storage system 9 may include rectifiers, inverters, converters, charge controllers, etc. to change or regulate the voltage, current and power flow to and from the energy storage system 9.

[78] It is to be appreciated energy storage systems 9 may not be limited to the above described batteries and may include other forms of energy storage 9. For example, a hydroelectric system may also be an energy storage system 9 by pumping water upstream (or above the turbine) to store potential energy. That is, a hydroelectric system may be both an electricity generation system 7 and an energy storage system 9. Importantly, the energy storage system 9 has the function of storing power from the electricity generation system 7 of the member (or other members) and/or power from the electrical grid 13. The energy storage system 9 also functions to provide power to the electrical load 11 of the member, other members 5 (including the electrical load and energy storage system of other members), or the electrical grid 9. [79] The electrical load 11 may be any load that consumes power. The electrical load 11, in one example, may include the power requirements from a refrigerator, a television, a heater, etc.

[80] The hub 15 provides a junction between the components of a member 5a, other members 5 and the electrical grid 13. In one example, the hub 15 may include a system of switching devices (such as relays) to direct power flow from a source to a destination in accordance with the second operating schedule. The hub 15 may receive control signals from a controller 16 that is remotely located, or co-located with the hub 15.

[81] The intra-member connections 8 will now be described with reference to Fig. 4. A first intra-member connection 21 provides a connection from the electricity generation system 7 to the hub 15. A second intra-member connection 23 provides a connection 8 from the electricity generation system to the electricity load 11. A third intra-member connection 25 provides a connection 8 from the electricity generation system to the energy storage system 9. A fourth intra-member connection 27 provides a connection 8 between the energy storage system 9 and the hub 15. A fifth intra-member connection 29 provides a connection 8 between the hub and the energy storage system 9. A sixth intra-member connection 31 provides a connection 8 between the hub 15 and the electricity load 11. A seventh intra- member connection 33 provides a connection 8 between the energy storage system 9 and the electricity load 11.

[82] In this example, an inverter 17 is provided along the first intra-member connection 21 between the electricity generation system 7 and hub 15. This changes direct current from, for example, a photovoltaic electricity generation system 7 to alternating current received at the hub 15 that may be more suitable for other components, other members 5, or the grid 13. Similarly, an inverter 17 is also provided on the, second intra-member connection 23, fourth intra-member 27 and seventh intra-member connection 33.

[83] Conversely, rectifiers 19 may be provided along the intra-member connections 8 to change alternating current to direct current such as between the fifth intra-member connection 29 from the hub 15 and the energy storage system 9. It is to be appreciated that other methods of converting alternating current to direct current, and/or direct current to alternating current may be used. [84] Charge controllers 18, converters (such as buck converters and boost converters) may be provided to regulate and/or change voltages and current of the power flow through the intra-member connections 8. It is to be appreciated that the inverters, rectifiers, charge controllers, and converters may be provided alternatively, or additionally, at other locations such as within the electricity generation system, energy storage system, electricity load, the hub 15, the inter-member connections 4, grid connections 6, etc. It is to be appreciated that two or more of the functions of the above mentioned components may be performed by single device. For example, a single inverter may be provided to convert direct current from the energy storage system 9 to alternating current to both the load 11 and the hubl5. Furthermore it is to be appreciated that a single device may operate in more than one mode, for example to operate as an inverter and a rectifier. Such a device, in some embodiments, may be selectively configurable (for example by controller 16) to operate in different modes. As discussed above, controlling power flow may include providing switching devices (such as relays) to connect and disconnect the power flow between the components 7, 9, 11, the hub 15, other members 5 and the grid 13. It is to be appreciated that the switching devices may be provided at or along the connections 4, 8, 6, at the components 7, 9, 11, the hub 15 or other suitable locations in a respective electrical circuit.

[85] In the embodiment illustrated in Fig. 4, there are seven intra-member connections 8 between the components 7, 9, 11 and the hub 15. These intra-member connections 8 provide direct power flow between components that may reduce losses and increase efficiency. For example, the second intra-member connection 23 allows direct power flow, through inverter 17, from the electricity generation system 7 to the electricity load 11. However, alternative power flows from the electricity generation system 7 to the electricity load 11 may be established, for example, through the first intra-member connection 21 and sixth intra- member connection 31 via the hub 15. Another alternative is from the third intra-member connection 25 and, through the energy storage system 9, the seventh intra-member connection 33. These alternative power flows may have more losses (such as losses during inverting). However, it is to be appreciated that some other examples may have more, or less, intra- member connections 8. (Hi) Processing device

[86] Fig. 8 illustrates an example of a processing device 501. The processing device 501 may be used at a central first processing device 201 and/or the processing device 22 of controller 16. The processing device 501 includes a processor 510, a memory 520 and an interface device 540 that communicate with each other via a bus 530. The memory 520 stores instructions and data for implementing the method 100 described above, and the processor 510 performs the instructions from the memory 520 to implement the method 100. The interface device 540 facilitates communication with the communications network 205 and, in some examples, to switching devices controlling power flow. It should be noted that although the processing device 501 (in the form of the central first processing device 201, or processing device in controller 16) is shown as an independent network element in Figs. 5 to 7, the processing device 501 may also be part of another network element. Further, functions performed by the processing device 501 may be distributed between multiple network elements.

[87] The processing device 501 may perform the method 100 of determining the first and second operating schedules with the constraints provided by some or all of the formulas described herein. For example, the processing device 501 may utilise an optimisation software package to determine the first and second operating schedules. An example of an optimisation software with the trade name CPLEX Optimizer offered by International Business Machines Corporation (IBM).

Communications schematic of the community electricity network

[88] The second operating schedule may be determined and communicated to the community electricity network, and implemented, in a variety of ways. Examples of how the second operating schedule may be determined, communicated and implemented will now be described.

(i) Schematic of the community electricity network with a central first processing device 201

[89] Fig. 5 illustrates a communications schematic of a community electricity network 200 for the community 3 including a central first processing device 201. The first processing device 201 includes a first processor 203 and is in communication with, over a communications network 205, members 5 of the community 3. The members 5 include a controller 16, or a member device 216, associated with one or more members 5. A data store 207 may be in communication with, over the communications network 205, the first processing device 201, controllers 16, or member device 216.

[90] The first processor 203 of the central first processing device 201 performs the method 100 to determine the second operating schedule. To perform the method, the first processing device 201 may receive relevant information, including the forecast electricity production and/or consumption of the members 5 of the community and information relevant to electricity prices from the data store 207, controllers 16 and member devices 216.

[91] After determining the second operating schedule, the first processing device 201 may send, over the communications network 205, at least part of the second operating schedule to one or more of the data store 207, controllers 16 and member devices 216. In cases where the controller 16 receives at least part of the second operating schedule, the controller 16 may control power flow of the associated member(s) 5. In another case, the second operating schedule may be stored in the data store 207. In turn, the controller 16 may receive 210, over the communications network 205, from the data store 207 at least part of the second operating schedule to control power flow of the associated member(s) 5. In yet another case, the member device 216 may receive 210 at least part of the second operating schedule. The member device 216 may, in turn, send at least part of the second operating schedule to respective components 7, 9, 11, the hub 15, or other equipment associated with the respective member 5 such that the components 7, 9, 11 of the members 5 can operate in accordance with the second operating schedule.

[92] In one example, the first processing device 201 may be a third party service provider that provides optimisation and scheduling services. Thus the first processing device 201 may be located remotely from the community 3. In another example, the first processing device may be located at or within the community 3. For example, the first processing device 201 may be part of a server for the community 3 that determines operating schedules to satisfy power needs of the community 3. [93] After the controller 16 or the member device 216 receives 210 the at least part of the second operating schedule, the processing device 22 of the controller 16 (or member device 216) may control power flow in accordance with the second operating schedule for the respective member as shown in Fig. 2.

(ii) Schematic of the community electricity network with a central controller 316

[94] Fig. 6 illustrates a communications schematic of an alternative community electricity network 300 for the community 3 including a central controller 316. The central controller 316 may send control signals, over the communications network 305, to a hub and components 310 of the members 5 to operate in accordance with the second operating schedule. The control signals may be sent directly to the hub and components 310 of the members 5 or, alternatively, indirectly through a member device 315.

[95] In one example, the central controller 316 includes a processor 303 to perform the method 100 to determine the second operating schedule. The second operating schedule may be stored in a data store 307 to be retrieved and sent to the processor 303 at a later time. In one variation, the second operating schedule may be determined by a separate processor (not shown) and stored in the data store 307. The processor 303 of the central controller 316 may retrieve the second operating schedule from the data store 307 to control power flow in the electricity network 301.

(Hi) Schematic o f the community electricity network with decentralised controllers 416

[96] Fig. 7 illustrates a communications schematic of an alternative community electricity network 400 for the community 3 having a plurality of decentralised controllers 416, each associated with one or more members 5. The decentralised controllers 416 may separately perform the method 100 to determine the second operating schedule and control power flow for respective members 5 in accordance with at least part of the determined second operating schedule.

[97] The community electricity network includes the plurality of decentralised controllers 416 in communication with one another over the communications network 405. In order for each of the decentralised controllers 416 to perform the method 100, each decentralised controller 416 receives information in relation to forecast electricity production and/or consumption of the other members 5 of the community 3 and information in relation to electricity prices. The decentralised controllers 416 may receive, over the communications network 405, at least part of this information from the other decentralised controllers 416. Alternatively, or in addition, the decentralised controllers 416 may receive this information from a data store 407. The data store 407 may have received the information from the decentralised controllers 416 or from a third party (not shown).

Detailed description of the method

[98] An example of the method 100 will now be described in detail. This will be discussed in two sections, with the first section discussing the step 110 of determining the first operating schedule with the associated first electricity cost and the considerations and constraints associated with that step. The second section discusses the step of determining 120 second operating schedule and the associated second electricity cost along with the constraints associated with that step.

(i) Determining the first operating schedule and first electricity cost

[99] The step 110 of determining the first operating schedule for each member 5 involves determining a schedule for power flow between components 7, 9, 11 and (in some

embodiments) the grid 13 that will provide a respective first electricity cost that is towards a minimum, and if possible at a minimum.

(a) Power flows in first operating schedule

[100] As noted above, the first step 110 provides a first operating schedule and a resulting first electricity cost of the member 5 (indicated as member k in the formulas) if the member 5 operated with their own (with components 7, 9, 11) and the grid 13. This is illustrated in Fig. 3 that shows member 5 and the respective components 7, 9, 11 that are connected to the grid via the hub 15 and grid connection 6. It is to be appreciated that some members 5 may have an electricity generation system 7 and energy storage system 9 that is sufficient to meet the requirements of the electricity load 11 and therefore may not be dependent on the grid 13. Accordingly in some embodiments, some members 5 may not have a grid connection 6. [101] In this example, there are seven power flows that need to be scheduled:

[102] X p ^G is the power from the electricity generation system 7 to the grid 13 during time period p. This power flows from the electricity generation system 7, through a first intra- member connection 21, the hub 15 and grid connection 6, to the grid 13.

[103] Xj?p ¹ is the power from the electricity generation system 7 to the electricity load 11 during time period p. This power flows from the electricity generation system 7, through a second intra- member connection 23, to the electricity load 11.

[104] X p is the power from the electricity generation system 7 to the energy storage system 9 during time period p. This power flows from the electricity generation system 7, through a third intra-member connection 25, to the energy storage system 9.

[105] X _p ^G is the power from the energy storage system 9 to the grid 13 during time period p. This power flows from the energy storage system 9, through a fourth intra-member connection 27, the hub 15 and grid connection 6, to the grid 13.

[106] X _p ^s is the power from the grid 13 to the energy storage system 9 during time period p. This power flows from the grid 13, through the grid connection 6, the hub 15 and a fifth intra-member connection 29, to the energy storage system 9.

[107] X p is the power from the grid 13 to the electricity load 11 during time period p. This power flows from the grid 13, through the grid connection 6, the hub 15 and a sixth intra-member connection 31, to the electricity load 11.

[108] X p is the power from the energy storage system 9 to the electricity load 11 during time period p. This power flows from the energy storage system 9, through a seventh intra- member connection 33, to the electricity load 11.

(b) The forecast electricity production and/or consumption

[109] The scheduled power flows need to satisfy the respective first forecast electricity production and/or consumption of the member 5 include: L_kp is the forecast local electricity demand of the electricity load 11 during time period p. That is, this is the forecast electricity consumption of the member 5 that excludes demand, if any, for storing power in the energy storage system 9; and

S_kp is the power produced by the electricity generation system 7 during time period

P-

(c) Cost function (C^* ) for each member operating alone with the grid

[ 110] The cost function (C^*) for each member 5 may be represented by the following equation:

C_k* =∑^P _{P i}(FOM + FOM_k ^s _p) + ∑^p _p^(SC^G _p + X_k ^G _p ^L. EP_p ^G + X_k ^G _p ^s . EP_p ^G - X_k ^s _p ^G. FIT,

G^inv. X^ ^c . FIT^G) Equation ( l) where,

C_k is the cost of the forecast horizon for member k from time period p =1 to p = P;

FOM_kp is the fixed operation and maintenance cost for the electricity generation system during time period p;

FOM_kp is the fixed operation and maintenance cost for the energy storage system during time period p;

SC_kp is the supply charge for connection with the grid 13 during time period p;

EP_p is the electricity price of power from the grid 13 during time period p;

FITp is the feed- in tariff of power from the member to the grid 13 during time period p; and

Vkp ^inv i^s the efficiency of an inverter between the electricity generation system 9 and the electricity load 11 during time period p. [ 111] As discussed above, the cost function (C*) provides an assessment of the cost for each member 5 operating alone with the grid. When determining the first operating schedule for the method 100, it is desirable to determine the first operating schedule such that the first electricity cost (that can be derived from the cost function C^* above) is adjusted to towards a minimum, or at the minimum. However, there are certain practical and commercial constraints that need to be considered, which may be factored by at least some of the following equations.

(d) Constraints for determining the first operating schedule and first electricity cost

[ 112] Firstly, the electricity generation system 7 can only produce a finite amount of power. The electricity generation system 7 of the member 5 produces power at time period p that is sent to the energy storage system 9, the electricity load 11 , and the grid 13 may be modelled according to the following equation:

¾¾^G = X^ ^G + X% ^L + X% ^S Equation (2) where,

S£p is the power supplied (e.g. rate of energy from solar irradiation, wind power, fossil fuel) to the electricity generation system during time period p; η ρ is the efficiency of the electricity generation system during time period p;

Xkp ^Gis the power from the electricity generation system during time period p that is sent, via the hub, to the grid G;

Xjp ^Lis the power from the electricity generation system during time period p that is sent to the load L of the member; and

X p ^Sis the power from the electricity generation system during time period p that is sent to the energy storage system of the member. [ 113] The left hand side of equation 2 represents the power produced by the electricity generation system as a whole during time period p and takes into account the efficiency of the electricity generation system 7.

[ 114] Power to the local electricity load 11 of the member 5 at time period p could be supplied from the electricity generation system 7, the energy storage system 9 and the grid 13. This may be modelled according to the following equation. p ≥ kp + kp ^invXkp ^L + Xkp Equation (3) where,

L_kp is the forecast local electricity demand of the electricity load during time period

Xkp^Lis the power sent from the grid to the electricity load during time period p; r]kp ^invis the efficiency of the inverter between the electricity generation system and the electricity load during time period p;

X p ^Lis the power sent from the electricity generation system to the electricity load during time period p; ^p^Lis the power sent from the energy storage system to the electricity load during time period p.

[ 115] The member may also have a reliability requirement R over the forecast time periods, that may reflect the fraction of the electricity demand L_p that must be satisfied. The reliability requirement ¾ is the complement of the loss of load probability ("LLP") (i.e. ¾ = 1 - LLP). The reliability constraint may be modelled by the following equation:

(¾^L + V ^invX£p ^L + Xu^Sp )/L_kP = R_k ^* Equation (4) where the parameter RL_k and the variable R_k* are the "required" and "ocurred" reliabilities for member k. For obvious reasons 0 < RLk < 1 and 0 < R_k ^* < 1. The constraint of Equation 4 is not applicable for off-grid users. A 100% reliability condition is provided when (R_k ^* = RL_k = l) .

[ 116] The energy storage system 9 also has a constraint in that it can only supply power that has been stored. The amount of power stored in an energy storage system 9, such as a battery, is known as a state of charge. Furthermore, to charge the battery, the energy storage system must receive direct current power from the electricity generation system 7 (after passing through a charge controller) or the grid 13 (after passing through a rectifier). To discharge the battery and provide power, the stored direct current power is sent to the electricity load 1 1 or the grid 13 (after passing through an inverter). There are losses associated with passing through inverters, rectifiers, charge controllers, converters and the like. The net change in energy charge of the energy storage system during time period p may be modelled by the following equation:

^■¾> ^— [ ^—

Equation (5) where,

S_kp is net change in energy charge of the energy storage system during time period p; βΐιρ is the self-discharge of the energy storage system during time period p; η^ρ is the efficiency of the charge controller for the energy storage system during time period p;

? / is the nominal charge efficiency of the battery of the energy storage system during time period p;

X_kp ^Sis the (direct current) power sent from the electricity generation system to the energy storage system during time period p; Vkp¹"^ ^me inverter nominal efficiency for the energy storage system during time period p; the (alternating current) power sent from the grid to the energy storage system;

X^p is the (alternating current) power sent from the energy storage system to the grid during time period p; η%ρ is the nominal discharge efficiency of the battery of the energy storage system during time period p; and

X_kp ^L is the (alternating current) power sent from the energy storage system to the electricity load during time period p.

[ 117] The net change in energy charge S_kp has a positive value when it is charged and a negative value during discharging. The state of charge of the energy storage system 9 is a culmination of this and may be represented by:

^S0Ck_P = ∑ '₌₁ ^Sk_P Equation (6) where,

SOCkp is the state of charge at time period p

[ 118] Furthermore the statement of charge should be controlled, during operation, with certain upper bound (SOC^u) to prevent over-charging and a lower bound (SOC^L) to prevent over-discharge. Thus a further constraint may be provided by the following equation:

SOCk≤ SOC_kp < SOCj^ Equation (7)

[ 119] In some energy storage systems 9 such as those that include one battery, it may not be possible, or it may be undesirable, to simultaneously charge and discharge the energy storage system 9. To include this constraint, a binary variable |_p to have a value of one when the battery is charged by the electricity generation system (DG) or grid (G). This may be represented by the following formulas:

X^ ^S≤ M. y_k ^s _p Equation (8)

X_kp ^S≤M. y_k ^s _p Equation (9)

X_k ^s _p ^G≤ M. (1 - y_k ^s _p) Equation (10)

X_k ^s _p ^L≤ M. (1 - y_k ^s _p) Equation ( 1 1) where, y_kp is a binary variable of one when the battery of the energy storage system is charged by the electricity generation system or the grid during time period p;

M is a constant of the big-M method.

[ 120] There may also be a constraint on the rate of charge and discharge of the energy storage system 9. That may be modelled by the following equations:

S_kp≤ CR Equation (12)

S_kp≥ - DR Equation (13) where,

CR_k is the maximum charge rate for the energy storage system; and

DR[ is the maximum discharge rate of the energy storage system.

[ 121] It may also be desirable that the electricity generation system 7 and the energy storage means 9 should not send power to the grid 13 during time period p if power is simultaneously received from the grid 13 as this may result in wastage of power (from losses) and increases costs to the member. This is addressed by introducing binary variable y _p to have the value of one when electricity is received by the member from the grid. The constraint may be represented by the following formulas

≤M. y£p Equation (14)

X^ ^G ≤ M. (1 - y£_p) Equation (15)

< . (l - y¾,) Equation (16) where, y£p is a binary variable of one when electricity is received by the member from the grid during time period p; and

M is a sufficiently big constant value (referred as Big-M value).

[122] In one example, the above mentioned equations provide constraints for determining the first operating schedule. It is to be appreciated that in some variations of the method may utilise a subset of these constraints and equations or additional equations and corresponding constraints or combinations thereof.

(ii) Determining the second operating schedule and second electricity cost

[123] The step 120 of determining the second operating schedule for each member 5 involves determining a schedule for power flow between components 7, 9, 11 of member 5a, other members 5 and the grid 13. For ease of reference, member 5a is referred to as "member k" in the formulas while another member 5 of the community 3 is referred to as "member k' "(where 1 < k ' < K, k'≠ 1 and K is the number of members 5 in the community 3). The second operating schedule provides respective second electricity cost to each member. If the total of the second electricity cost of the members 5 in the community 3 is less than the total of the first electricity cost of the members 5, then there is a net financial benefit of the members 5 operating in accordance with respective second operating schedules. It is to be appreciated that the community 3 may have electricity generation systems 7 and energy storage systems 9 that are sufficient to meet the requirements of the community. Accordingly at least one member 5, and/or the community 3 may not be dependent on the grid 13 and may not have grid connection 6.

(a) Power flows in the second operating schedule

[124] Referring to the network in Fig. 4, members 5 are connected to one another through inter-member connections 4. This provides additional power flows to that shown in Fig. 3 in that members can send and receive power to one another. In the example illustrated in Fig. 4, power that is sent and received by a member 5 (to either other members 5 or the grid 13) passes through the hub 15. Thus the inter- member connections 4 connect respective hubs 15 of members 5 of the community 3. By connecting through hubs 15 of members, this saves having connections between each component 7, 9, 11 of one member 5 to each component 7, 9, 11 of another member 5. This may reduce the number of inter- member connections 4 and reduce costs. However, it is to be appreciated that inter-member connections 4 between components 1, 9, 11 of members 5 may be implemented.

[125] There are a number of power flows that need to be scheduled. In this example, the power flow of member 5 a will include power flow between the hub 15 of member 5 a to one or more other members 5, the power flow between the hub 15 of member 5a to the grid 13, the power flow between the hub 15 of member 5a to the components 7, 9, 11 of member 5a, and the power flow between components 7, 9, 11 of member 5a. The power flow of member 5a is provided below:

[126] X_kp ^'H is the power from the electricity generation system 7 to the hub 15 during time period p for member k in the community. This power flows from the electricity generation system 7, through a first intra-member connection 21, to the hub 15.

[127] X _p ¹ is the power from the electricity generation system 7 to the electricity load 11 during time period p for member k in the community 3. This power flows from the electricity generation system 7, through a second intra-member connection 23, to the electricity load 11.

[128] Xj?p ^s is the power from the electricity generation system 7 to the energy storage system 9 during time period p for member k in the community. This power flows from the electricity generation system 7, through a third intra- member connection 25, to the energy storage system 9.

[129] X _p ^H is the power from the energy storage system 9 to the hub 15 during time period p for member k in the community. This power flows from the energy storage system 9, through a fourth intra-member connection 27, to the hub 15.

[130] X _p ^s is the power from the hub 15 to the energy storage system 9 during time period p for member k in the community. This power flows from the hub 15, through the fifth intra- member connection 29, to the energy storage system 9.

[131] X _p ^L is the power from the hub 15 to the electricity load 11 during time period p for member k in the community. This power flows from the hub 15, through a sixth intra- member connection 31 , to the electricity load 11.

[132] X _p ^L is the power from the energy storage system 9 to the electricity load 11 during time period p for member k in the community. This power flows from the energy storage system 9, through a seventh intra-member connection 33, to the electricity load 11.

[133] X_k&p is the power from the hub 15 of member k to another member (where k≠k ') during time period p. This power flows from the hub 15, through the inter-member connection 4, to the other member k'. The total power from hub 15 of member k to all the other members k ' in the community is given by the following sum, where the community has K members:

[134] X^i_kp is the power from another member k ' (where k Φ k ') to the hub 15 of member k during time period p. This power flows from another member k', through the inter-member connection 4, to member k. The total power to the hub 15 of member k from all the other members k ' in the community is given by the following sum, where the community has K members:

[135] X _p ^G is the power from the hub 15 of the member k in the community to the electrical grid 13 during time period p. This power flows from the hub 15, through a grid connection 6, to the electrical grid 13.

[136] X£_p ^H is the power from the electrical grid 13 to the hub 15 of the member k in the community during time period p. This power flows from the electrical grid 13, through a grid connection 6, to the hub 15.

(b) The forecast electricity production and/or consumption of the member

[137] The scheduled power flows for a member 5a need to satisfy the forecast electricity production and/or consumption of member 5a (i.e. member k) include:

L_kp is the forecast local electricity demand of the electricity load 11 during time period p for member 5a. That is, this is the forecast electricity consumption of the member k that excludes demand, if any, for storing power in the energy storage system 9; and

S _p is the power produced by the electricity generation system 7 during time period p for member 5a.

[138] The above mentioned forecast production and consumption for each individual member 5a during time period p is substantially the same as that used when determining the first operating schedule. However when determining the second operating schedule, the forecast production and consumption of other members of the community are factored into the determination with the cost function given below.

(c) Cost function (C) for each member operating alone with the grid

[139] The cost function (C^*) member 5a ( member k) may be represented by the following equation: C_k =

+ X£_p ^H. EP_p ^G - Xj?_p ^G. FIT_p ^G) +

∑P=I∑_fc'=i &k'*Mkv ^CEPP - X"i - CEP_p ) Equation (17) where,

FOM p is the fixed operation and maintenance cost for the electricity generation system during time period p for member k;

FOM p is the fixed operation and maintenance cost for the energy storage system during time period p for member k;

SC_kp is the supply charge for connection with the grid 13 during time period p for member k;

EP_p is the electricity price of power from the grid 13 during time period p;

FIT_p is the feed- in tariff of power from a member to the grid 13 during time period

P\

CEPp is the community electricity price at time period p;

[140] As discussed above, the cost function Q provides an assessment of the second electricity cost for each member 5a (member k) operating with the community 3. One major difference in the cost function Ck (provided by equation 17) compared to the cost function C_k (equation 1) is that Q takes into account power flow between members (represented by X_kj^_p and Xfckp) at forecast time period p. The power flow between members, in turn, are indicative of power flows at forecast time period p, of surplus production or storage of the member, or alternatively consumption (by the load 11 or energy storage system 9) that exceeds production of the electricity generation system 7 of the member. Therefore this formula facilitates determination of the second operating schedule based on forecast electricity production and/or consumption of the members 5 of the community during the forecast time period p.

[141] The present method 100 may be advantageous in instances where the community electricity price (CEP_P) at time period p is generally less than the electricity price (EP_p ^G) from the grid 13. That is, a member 5 having a deficit of power may be able to source power from another member 5 at a lower price than sourcing power directly from the grid 13. Conversely, it may be more beneficial for a member 5 with surplus power to dispatch the unused power to another member 5 of the community 3 rather than feeding the surplus to the grid 13. In one example, the community energy price may be more favourable than the feed-in tariff.

[142] In the above example, a cost of power to member k to "buy" power from another member is added and is based on the community electricity price (CEP). Conversely a price of power given to member k to "sell" power to another member A: ' is subtracted and is also based on the community electricity price (CEP). Although the community electricity price CEPp in the above example is the same during period p, it is to be appreciated that in other examples there may be a differential between the cost of power to a member k to "buy" power and the price of power to a member k to "sell" power to other members k'.

[143] It may be favourable for a member to supply surplus energy to another member, who may for example, have capacity in their energy storage system to store the excess power for later use by the member having the surplus or for other members. In yet another example, the community electricity price CEP may be relatively low, or nil, and the savings value

(described below) are determined and distributed evenly, proportionally, or by other methods to the members 5. The above situations are just some examples of how scheduling a community electricity network 1 in the community can be beneficial to one or more members 5, or the entire community 3.

[144] Therefore one constraint for the second operating schedule is that the total second electricity cost must be less than the benchmark first electricity cost. Otherwise, at least for the given time periods in the forecast horizon, it would be more beneficial for all the members to operate individually according to the first operating schedule. This constraint may be provided by the following equation: k=i ^Lfc Z,fc=i Equation (19)

[145] There is an obvious desire to obtain the maximum, or at least strive to obtain the maximum, benefit from the community electricity network. Therefore the method 100 may include adjusting the second operating schedule so that the difference between the total of the first electricity cost of the members and the total of the second electricity cost of the members is towards a maximum. This can be provided by the following equation:

SV = max∑£₌₁(ί7 - C_k) Equation (20) where,

SV is the calculated saving value for the entire community 3 if members 5 operated under the respective second operating schedules rather than members 5 operating under respective first operating schedules (for \ < k < K and \<p < P)

[146] Therefore equation 20 assists in determining the second operating schedule that provides the most benefit to the community 3 as a whole.

[147] To provide incentives for individual members 5 of the community to be party to the community electricity network 1 , each individual member 5 may require a quantifiable individual benefit. Therefore in one example of the method, a constraint for determining the second operating schedule may require each individual member to be the same, or preferably better off, than if the member 5 had operated individually (with the grid) under the first operating schedule. This constraint may be provided by the following equation:

C_k≤ C_k ^* \< k < K Equation (21)

[148] When determining the second operating schedule for the method 100, it is desirable to determine the second operating schedule such that the second electricity cost (that can be derived from the cost function Q) is adjusted to towards a minimum, or at the minimum. However, there are certain practical and commercial constraints that need to be considered, which may be factored by at least some of the following equations. (d) Constraints for determining the second operating schedule and second electricity cost

[149] When member 5a has a surplus of power, the surplus may be directed through the hub 15 to either one of, or both, the grid 13 or other members 5. Conversely, when member 5a has a power deficit, member 5a can source power, through the hub 15, from the grid 13 or other members. Furthermore, in some circumstances it may be desirable to have power flows through the hub 15, such as member 5a charging the energy storage system 9 with power from the grid 13 during off-peak times in anticipation for use at another time.

[150] Regardless of the reasons for the power flows, for each member k, the power flow going to and from the hub 15 from components 7, 9 and 11 should generally be equal to the power flow going to and from other members 5 and the grid 13 (with the exception of losses, such as transmission and distribution losses). This can be shown by the following equation: yDG.H , yS.H _ yH.S _ yH.L _ y f yH.K _ iif yK.H , yH.G _ yG.H

^Akp ^Akp ^Akp ^Akp ^~ k'=l & fc'≠fc ^Akk'p ^k' = l & fc'≠fc ^Afc' kp ^ ^Akp ^Akp

Equation (22)

[151] The left hand side of equation 22 represents the power flows from the components 7, 9, 11 to and from the hub 15 of member 5a (k). The right hand side of equation 22 represents the power flows between the hub 15 of member 5a (k) with other members 5 (k ') and the grid 5.

[152] Furthermore, at least some of the constraints and equations, or derivation thereof, described above when determining the first operating schedule may also be applicable when determining the second operating schedule.

[153] For example, equations 6, 7, 8, and 11 to 13, or substantially similar equations for the applying the respective constraint, may be used when determining the second operating schedule. Furthermore, equations 2 to 4, 9 to 10 and 14 to 16 may be adapted to include the hub 15 of member 5a, and the power flow from the hub 15 to other members 5 (member k') and (if the community electricity network is connected to the grid 13) the grid 13. Examples of this adaptation will be provided below: [ 154] Power to the local electricity load 11 of member 5 a (member k) at time period p may be supplied from the electricity generation system 7, the energy storage system 9 and from the hub 15 (which in turn receives power from other members 5 or the grid 13). This may be modelled according to the following equation.

L_kp≥ + V^D^^invX^ ^L + X_k ^s _p ^L Equation (23)

[ 155] Equation 23 is similar to equation 3 and it is to be appreciated similar variations may be implemented to factor in reliability requirements ¾ as provided in equation 4.

[ 156] Similar to equation 4 discussed above, the member may also have a reliability requirement R over the forecast time periods, that may reflect the fraction of the electricity demand L_p that must be satisfied. The reliability constraint may be modelled by the following equation:

^L + X_k ^S _p ^L)/LkP = R_k Equation (24) where the and R_k are the "occurred" reliabilities for member k at non-cooperating (first operating schedule) and cooperating (second operating schedule) conditions

respectively. The constraint of R_k≥ R^ in Equation 24 provides that with cooperation, member k should have higher or at least equal reliability compared with when operating individually. For obvious reasons 0 < R_k* < 1 and 0 < R_k< 1. A 100% reliability condition is provided when R_k = R_k = 1) .

[ 157] Furthermore, equation 2 has been adapted to show the power flow from the electricity generation system 7 to the hub 15 (instead of the grid 13) as shown in equation 25. Equation 25 describes the electricity generation system 7 of the member k producing power at time period p that is sent to the energy storage system 9, the electricity load 11, and the hub 15,

= X£p " + X£p ^L + X°p ^S Equation (25)

[ 158] Furthermore, the net change in energy charge of the energy storage system during time period p may be modelled by equation 26, which is derived from equation 5:

Equation (26)

[159] As noted above, in some energy storage systems 9 it may not be possible, nor desirable, to simultaneously charge and discharge the energy storage system 9. To include this constraint, a binary variable y_kp to have a value of one when the battery is charged by the electricity generation system (DG) or hub (H). This may be represented by equations 8 and 11 as previously provided in conjunction with equations 27 and 28 below that are derived from equations 9 and 10 respectively:

XKp ≤ M. y_k ^s _p Equation (27)

X_k ^s _p ^H≤M. (l - y_k ^s _p) Equation (28)

[160] It is to be appreciated these equations may be modified to include other factors, such as additional devices, efficiency losses, additional sources of power, etc.

[161] Furthermore, although the second operating schedule in the described examples includes power flows with the grid 13, it is to be appreciated that in some communities 3, the electricity generation systems and the energy storage systems are sufficient to supply the forecast electricity consumption of the community 3 as a whole. Therefore, in some instances it may not be necessary for the community electricity network 1 , operating in accordance with the second operating schedule, to be connected to the electrical grid 13. Nonetheless, calculation of the first electricity cost, with reference to electricity price and feed-in tariff with the grid 13, may be used to determine the second operating schedule and to determine the financial viability of the community having and operating the electricity network.

(Hi) Determining the economic viability of the community electricity network

[162] The above mentioned method may also be used to determine the economic viability of constructing and maintaining the community electricity network 1. The saving value provided by equation 20 indicates the economic benefit of operating under the second operating schedule for a period \< p < P. To determine the economic viability of the community electricity network 1, this saving value may be balanced by the cost of this network 1. The costs may include, for example, costs associated with constructing the inter- member connections 4, costs associated with easements or acquisition of land for the community electricity network 1, environmental costs associated with the inter-member connections 4, etc. It is to be appreciated that generally, the savings value in the medium to long term must be greater than the costs of having the electricity network 1.

Examples

[163] The following are non-limiting examples that illustrate the operation of the method 100 of scheduling a community electricity network 1.

(i) Example 1 - Network of nine homes

[164] Nine houses in Sydney, Australia, are located in a community 3. Each house is a member 5 of the community 3. The houses' electricity consumption is in the range of 4.4 MWh/y (for home #2) to 10.9 MWh/y (for home #9). The one-year hourly load profile of each house is available. As usually the profiles of hourly load over one year are not informative, the annual average daily load profiles for these nine houses are illustrated as graphs 600 in Fig. 9.

[165] The current electricity price from the grid 13 consists of three ToU (Time of Use) tariffs: (off-peak, shoulder, and on-peak). Off-peak (13 c/kWh) includes 10:00 pm to 7:00 am. Shoulder (21 c/kWh) is during 7:00 am to 2:00 pm and 8:00 to 10:00 pm on weekdays, and 7:00 am to 10:00 pm during weekend/public holidays. On-peak (52 c/kWh) period is during 2:00 pm to 8:00 pm on weekdays. There is also a daily supply charge of $ 0.87. With this electricity pricing scheme, the houses spent between $1336.8 (for home #2) and $10891.0 (for home #9) for their electricity cost over last financial year as illustrated in the table 610 in Fig. 10.

[166] The condition that all houses (i.e. members 5) are dependent on the grid 13 and buy their electricity completely from the grid 13 is taken as Scenario 1.

[167] The second scenario assumes that some of the houses 5 have decided to develop a nanogrid by installing a electricity generation system (in the form of a photovoltaic system, "PV systems") and/or energy storage system (such as a battery system) to reduce their purchase from the grid 13. In these examples, the electricity generation system is also known as a distributed generation system "DG" and the energy storage system "S", and the collective term for either one or both of these systems in a member 5 house is "DGS". The sizes of DGS systems are given in the table 610 in Fig. 10. In Scenario 2 the houses do not have any communication with one another with respect to exchange of power. The FiT is 8.0 c kWh (IPART, 2013) which is relatively low compared with ToU tariffs even at off-peak periods.

[168] This brings in Scenario 3 in which the nine homes would like to assess the economic practicality of building a local network. This could allow them to share their surplus electricity amongst themselves rather than selling to the grid. The group have agreed on a community electricity tariff of CEP=shoulder tariff= 21 c/kWh. If feasible, they might even be interested in totally disconnection from the grid.

[169] The annual ambient temperature profile 620 and GHI (global horizontal irradiation) profile 630 are illustrated in Figs. 11a and 1 lb. In this example, the PV systems have standard efficiency of 0.17 with periodical panels efficiency) affected by ambient temperature with a function of 1.09 - 0.0036x7^. Thus the forecast electricity production from the PV systems may be based on the data such as the annual ambient temperature and GHI that are illustrated in Figs. 1 la and 1 lb. The battery systems are li-ion with DoD (depth of discharge) of 85%. The charge controllers and inverters have an assumed efficiency of 98%. The batteries have charge and discharge duration of two hours and one hour, respectively. They have manufacturing round-trip efficiency of 92%.

[170] Step 110 of determining a first operating schedule is performed for each house and their first electricity cost (and thus saving with DGS) is determined. For obvious reason home k5 did not require optimization (as it had no DGS). The results for all nine homes are given in the table 640 shown in Fig. 12 (under Scenario 2). Under Scenario 2, the houses with DGS are able to reduce their electricity cost in the range of $ 80.4 (for k2 with 1 kWh battery) to $1620.3 (k8 with 5 kW PV and 4 kWh battery). Overall, the electricity costs of the nine homes reduce by 37.0% from $ 20069.4 of Scenario 1 to $12645.3 in Scenario 2 (the latter being the total of the first electricity cost of the member houses). This is achieved by total installation of 19.5 kW PV and 20.0 kWh battery systems. [171] When the nine houses build a community electricity network 1 (i.e. scenario 3), step 120 is performed to determine a second operating schedule for each house and the respective second electricity cost. With CEP of $0.21, the total second electricity cost of the member houses (i.e. the sum of their annual electricity bills) reduces to $10621.7 which is 47.0% less than that of scenario 1. It is also $2023.6 or 16.0% less than that the community's total grid costs for scenario 2. The nine homes will exchange around 10778.0 kWh of electricity amongst themselves with total value of $2263.4. Obviously house k5 is the least supplier of electricity (zero). The highest amount of electricity is supplied by k8 (2502.8 kWh) which has the largest PV system. In terms of receiving the electricity k4 is the lowest (143.9 kWh) whilst k7 is the highest (4540.8 kWh).

[172] In terms of net saving, all nine homes in scenario 3 have increase in their annual saving compared to Scenario 2. This was expectable due to constraint of equation 17. Overall the saving of these homes are $ 2023.7 higher than Scenario 2 of which the minimum benefit goes to house k2 ($96.2 or 4.8%) whilst k3 enjoys $315.9 (15.6%).

[173] The interaction of the houses amongst themselves is illustrated in the power exchange schematic 650 in Fig. 13. The lines' arrow shows the direction of power flow, and the lines' thickness displays the magnitude of energy quantity. It is evident from the network that all members have interaction with each other's due at different quantities. The most significant arrows are towards k7 has high energy demand, but does not possess a DG system and has only a battery. As such, members like kl, k3, k4, k6, k8 and k9 send their surplus energies to this member not only to utilize its battery but also supply its unserved energies.

[174] The interactions of the nine houses with the grid over the three scenarios are illustrated in graphs 660 in Fig. 14. Under Scenario 1, the houses have one-way interaction with the grid with annual electricity purchase of 72.6 MWh. When the houses install DGS systems in Scenario 2, the interaction with grid become bidirectional. With 19.5 kW PV and 20 kWh battery not only the annual electricity purchase drops to 55.5 MWh (23.5%), but also the houses sell (feed-in) 18.5 MWh surplus electricity to the grid. The cooperating community electricity network 1 makes it possible for one member to use another member's redundant electricity and reduce feed-in to the grid 13. Figure 14-Scenario 3, clearly illustrates that with community electricity network 1 not only feed-in electricity to the grid has almost halved (from 18.5 MWh of Scenario 2 to 9.6 MWh in Scenario 3), but the time of use demand from the grid has also declined (from 55.5 MWh of Scenario 2 to 46.6 MWh in Scenario 3).

[175] The annual average daily interaction with the grid 13 under the three scenarios is also depicted in graph 670 in Fig. 15. It is evident that with Scenario 2, the load profile notably declines during midday times when PV systems output is at maximum. Interestingly there is a peak at off-peak periods (before 7:00 am) when the batteries of the energy storage systems try to be charged before the tariff changes to shoulder. With Scenario 3, at least three advantages are observed. First, the peak load of off-peak time as observed in Scenario 2, notably declines mainly due to the fact that the members with battery and without PV systems can wait to charge their battery with PV output of another member rather than charging from grid.

Second, the better utilization of batteries amongst the members allows storing the midday extra PV output and reducing the power export to grid at low FiT. As such, the negative part of the profile for Scenario 3, moves upper compared with scenario 2 in the graph 670 in Fig. 15. Third, with the increased SOC level of batteries, it is possible to reduce the demand during afternoon (2:00 till 8:00 pm) and morning peak times. In summary the community electricity network 1 in this example not only reduces the costs of community members but also helps the macrogrid 13 with reduction of load during peak demand periods. This implies the economic advantage of community electricity network 1 for the members 5 of the community 3 as well as improving the efficiency of macrogrid 13 and in a larger perspective advancing global sustainability.

(ii) Example 2 - Various community electricity prices

[176] Example 1 considered a community electricity price (CEP) equal to grid's shoulder tariff. The result showed that the benefit of each member 5 from the electricity network 1 was different with minimum being only 4.8% of total saving for k2, which was less than one-third of the benefit that k3 gained (15.6%). This example is similar to the previous with a difference that the members 5 of the community 3 would like to investigate the impact of various CEP values on the performance of the community electricity network 1. The goal is to define a reasonable value for CEP so that all members receive a fair benefit. The community would like to assess the following cases: Case 1: CEP is taken equal to electricity price of off-peak period (which is still higher than FiT)

Case 2: CEP is taken equal to off-peak tariff during off-peak tariff periods and equal to half of ToU tariff during other periods. Therefore, this CEP will be time variants and those members 5 who consume more energy during on-demand periods, will incur higher electricity cost.

Case 3: The members 5 do not set a price for community electricity. The total annual saving is gathered and divided between the members in a way that 50% of the saving is divided equally amongst them and the next 50% is shared amongst those with DGS installation based on their installation capital costs. Those who have larger DGS systems (higher installation costs) will receive larger share of the second 50%.

[177] The three scenarios were executed and the results are given in the table 680 in Fig.

16. For obvious reasons the aggregated savings are unchanged across case studies. However, the distribution of benefits from the community electricity network 1 varies with application of different CEPs. For better illustration the results are also demonstrated in graph 690 in Fig.

17. For the base case (i.e. scenario 3 in Example 1) the gap between the lowest and highest benefits is 10.8% (4.8-15.6%). This gap becomes 23.4% (3.0-26.4%) for Case 1, 32.3% (1.0- 33.3%) for Case 2, and 11.2% (5.6-16.8%) for Case 3.

[178] It is evident from the graph 690 in Fig. 17 that the uppermost benefits in cases with high benefit variances (Case 1 and Case 2) go for those members with small DGS investment. For instance in Case 1 and case 2, k7 receives 26.4%, and 33.3% of benefits, respectively, with only $ 2378.6 investment in a battery system. Interestingly, the second highest benefit goes to home k5 without DGS installation (22.2% in Case 1, and 24.5% in Case 2). Case 3 (shown with solid line in Fig. 17), however, expectedly depicts a linear trend with an increase in DGS installation costs. The base case and Case 3 show relatively close and more sensible trend. (Hi) Example 3 - Various community electricity prices and benefit of additional DGS

[179] It was found in Example 1, that though the community electricity network 1 notably reduces export of electricity to the grid (from 18.5 MWh to 9.6 MWh), still a notable amount has to be sent to the grid at low feed-in tariff. Now, house k5 which does not have any DGS installation is interested to support the community with installation of a 15 kWh battery system. The community members are interested to assess the impact of the addition of this battery system to the performance of the overall system. Member k5 also is interested to see that when the network operates optimally, how much extra annual saving the house could have compared with Example 1. All other parameters are similar to Example 1 except the CEP which is equal to Case 3 of Example 2.

[180] The results of this example are given in table 700 in Fig. 18. Performing step 110 to determine the first operating schedule and first electricity price with the 15kWh battery compared to the first electricity price without the battery (such as in Scenario 2) showed that member k5, can save $630.5 in its electricity cost with a 15kWh battery system. Obviously, the results for other eight homes were unchanged at first stage. Performing step 120 to determine the second operating schedule and corresponding second electricity cost to the member k5 showed however that the 15 kWh battery system could increase the annual electricity savings of the community around $1014.0 which is 61% more than when it is operating individually for house k5 ($630.5). Under the agreed CEP tariff (Case 3), not only does member k5 receive extra benefit compared with example 1 ($772.2 ), but other member also are benefited with the addition of this battery to the network in the range of $22.7 (k2) to $38.6 (k8) during the planning horizon.

(iv) Example 4 - Impact of grid electricity tariffs

[181] Currently there are at least two arbitrary grid electricity tariffs being flat and time-of- use. In previous examples, it was assumed that all community members 5 have ToU contract with the grid. The previous examples proved the feasibility of community electricity network 1. But, will the network perform feasibly with a flat tariff? The members 5 are interested to check the performance of the proposed community electricity network 1 with flat tariff in case in future they desire to practice. All other parameters are similar to Example 1 with the CEP being equal to Case 3 of Example 2. [182] The results of this study are given in table 710 in Fig. 19. The results show that flat tariff does not favour using battery when there is no PV installation. Battery is useful to shift local demand by saving electricity at low-cost times and using at high-cost periods. Therefore when the tariff is flat, the battery system of member k2 and k7 are unnecessary. But the other six members who have PV systems (kl, k2-k4, k6, and k8-k9) are able to notably reduce their electricity cost. Overall, the nine houses when operate individually could have annual saving of $6064.6. When the homes build a network 1, even those members k2 and k6 having battery systems without a respective PV system find application (to store the redundant PV generation of the other members 5 of the community 3). The community is able to save extra $1709.8 which is obviously less than when there is ToU tariff ($2023.7) as the flat tariff reduces the flexibility of the community for demand shifting.

Example 5 - Larger community network

[183] Another example of a community electricity network will now be described with reference to Figs. 20 to 22. Thirty five houses in Sydney, Australia, are located in a community 3. The houses' electricity consumption is in the range of 3.7 MWh/y (home #29) to 13.2 MWh/y (home #18). The one-year hourly load profile of each house is available. The ToU electricity tariff structure is similar to the previous examples (such as Example 1). With this, the houses spent between $1253.40 (for home #29) and $3908.10 (for home #12) for their electricity bill over a previous financial year as shown in the table 800 in Fig. 20. Also, the size information of PV and/or battery systems for each member (when available) is provided in the table 800. The performance specifications of PV and battery systems are similar to the previous examples.

[184] Similar to the previous examples, there are three scenarios: Scenario 1 where each member 5 has full grid dependence; Scenario 2 where there is a non-cooperative DGS system and each member uses their own DGS (if available) and the grid; and Scenario 3 where the community shares surplus in a cooperative community electricity network 1.

[185] The CEP is similar to Case 3 in Example 2 above, which is where the members 5 do not set a price for community electricity and the total annual saving is divided between the members 5 in such a way that 50% of the saving is divided equally among them and the other 50% is shared among those with DGS installations, based on their installation capital costs. [186] The results of the three scenarios are shown in table 850 in Fig. 21. In summary, the results show that when fully grid-dependent (Scenario 1), the members will pay a total amount of $80540.10 to the utility companies. With the PV -battery installations (Scenario 2) as per (Figure 20), the total annual saving in electricity costs for these non-cooperative homes becomes $23479.8. When the homes operate as a cooperative community electricity network 1 (Scenario 3), the saving increases overall by more than 40% to $33208.9. This increase in saving of members from 24.8% (for home #11) to 198.6% (for home #4) is based on their DGS system configuration and load pattern.

[187] The interaction between each of the thirty five members 5 are also illustrated in Fig. 22, which shows the network of energy exchange amongst the thirty five members. The line thickness shows the magnitude of energy quantity between the members. It is important to note that the energy flow between the members 5 of the community 1 may represent energy (electricity) flows that, at least in part, would otherwise be between the member 5 and the grid 13. For the reasons discussed above, it may be advantageous for electricity flow to be, when a member's energy demand required, to be between members 5 of a community 3. In particular, members 5 of a community 3 may be geographically closer to one another compared to the power plant(s) supplying the grid 13 and therefore receiving electricity from the community 3 may reduce transmission and distribution losses. For example, electricity sourced from within the community 3 may not need to be transformed to high voltages and carried over distance on high voltage power lines.

[188] It will be appreciated by persons skilled in the art that numerous variations and/or modifications may be made to the above-described embodiments, without departing from the broad general scope of the present disclosure. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive.

Claims

THE CLAIMS DEFINING THE INVENTION ARE AS FOLLOWS:

1. A method of scheduling a community electricity network including two or more members in a community, each member having components including one or more of an electricity generation system, an energy storage system and an electricity load, and each member is electrically directly connected to at least one other member, the method comprising: determining, for each member, a respective first operating schedule of power flow of the components of the member and an electrical grid based on a respective forecast electricity production and/or consumption of the member, wherein determining the first operating schedule adjusts a respective first electricity cost of the member towards a minimum; and determining, for each member, a respective second operating schedule of power flow of the components of the member and other members of the community based on a forecast electricity production and/or consumption of the community to provide a respective second electricity cost of the member, wherein a total of the second electricity cost of the members is less than a total of the first electricity cost of the members.

2. The method of claim 1 , wherein the step of determining the second operating schedule adjusts the second operating schedule towards a maximum difference between:

- the total of the first electricity cost of the members of the community; and

- the total of the second electricity cost of the members of the community.

3. The method of any one of the preceding claims, wherein the respective second electricity cost for each member to operate in the second operating schedule is less than, or equal to, the respective first electricity cost for that member.

4. The method any one of the preceding claims, wherein at least one member is connected, separate from the electrically directly connection between members, to the electrical grid and the step of determining a respective second operating schedule further includes determining power flow with the electrical grid.

5. The method of any one of the preceding claims, wherein the first and second operating schedules is over a plurality of time periods, wherein the respective first and operating schedules include respective power flows that vary between at least two of the time periods.

6. The method according to any one of the preceding claims, further comprising: sending, over a communications network, at least part of the second operating schedule to one or more members of the community.

7. The method of any one of the preceding claims, wherein at least one member has a controller to control power flow between two or more of: the electricity generation system of the member; the energy storage system of the member; the electricity load of the member; one or more other members of the community; and the electrical grid, wherein the method further comprises: sending, over a communications network, at least part of the second operating schedule to the controller to control power flow in accordance with at least part of the second operating schedule.

8. The method according to any one of the preceding claims, wherein the second electricity cost to operate in the second operating schedule for each member comprises: adding a cost of electricity associated with power flow from other members of the community to the member; and deducting a price of electricity associated with power flow provided by the member to other members of the community, wherein cost and/or price of electricity associated with power flow between members of the community are determined at one or more community electricity prices.

9. The method according to claim 8, wherein the second electricity cost to operate in the second operating schedule for each member comprises: adding a cost of electricity used by the member from the grid, calculated at grid electricity prices; and deducting a price of electricity provided by the member into the grid, calculated at feed- in tariffs, wherein the community electricity price(s) between members of the community are lower than feed-in tariffs of power provided by the member into the grid during corresponding time periods in the first and second operating schedules.

10. The method according to any one of claims 1 to 6, wherein the second electricity cost do not include cost and/or price of electricity associated with power flow between one member to another member.

11. A community electricity network for a plurality of members in a community comprising:

- a plurality of controllers each associated with at least one member, wherein the controller controls power flow between two or more of:

- an electricity generation system of the at least one member;

- an energy storage system of the at least one member;

- an electricity load of the at least one member; - one or more other members in the community; and

- the electrical grid; and a first processing device to perform the method according to any one of claims 1 to 10, wherein at least part of the second operating schedule is sent, over a communications network, to one or more of the plurality of controllers to control power flow in accordance with at least part of the second operating schedule.

12. A controller for a member in a community including a plurality of members, wherein the controller of the at least one member controls power flow between two or more of:

- an electricity generation system of the at least one member;

- an energy storage system of the at least one member;

- an electricity load of the at least one member;

- one or more other members in the community; and

- an electrical grid, wherein the controller includes a second processing device to control power flow in accordance with at least part of the second operating schedule according to any one of claims 1 to 10.

13. The controller according to claim 12, wherein the second processing device is configured to:

- receive, over a communications network, at least part of the second operating schedule.

14. The controller according to claim 12, wherein the second processing device is configured to: - perform the method according to any one of claims 1 to 10.

15. A computer program comprising machine-executable instructions to cause a processing device to implement the method according to any one of claims 1 to 10.

16. A method of operating a community electricity network comprising a plurality of members in a community, the method comprising: determining a second operating schedule in accordance with any one of claims 1 to

10; and sending, over a communications network, at least part of the second operating schedule to at least one of: one or more members of the community; and a representative of the community; an entity controlling at least part of the community electricity network, such that components of at least one member operate in accordance with at least part of the second operating schedule.