GB2519632A

GB2519632A - System And Method For Providing Electrical Supply Grid Service

Info

Publication number: GB2519632A
Application number: GB1414642.7A
Authority: GB
Inventors: Andrew Howe
Original assignee: Individual
Current assignee: Individual
Priority date: 2013-08-16
Filing date: 2014-08-18
Publication date: 2015-04-29
Also published as: GB201414642D0

Abstract

A system and method for providing a response to an electrical grid 7, including at least one virtual response electricity meter 2, which includes computing hardware operable to calculate an availability measurement from one or more loads L1 and L2, equipped with load control devices 5a and 5b. The system may be operable to use with pre installed utility metering systems, and may be suitable for commercial or residential premises. The loads may be controlled on electrical grid frequency. The loads may include storage heaters. The virtual response meter may measure a parameter on each load, such as a resistance measurement, for determining their energy storage status.

Description

SYSTEM AND METHOD FOR PROVIDING ELECTRICAL SUPPLY GRID SERVICE

Technical Field

The present disclosure relates to systems for providing electrical supply grid service, for example electrical supply grid balancing. Moreover, the present disclosure concerns methods of providing electrical supply grid service. Furthermore, the present disclosure relates to devices for implementing aforesaid systems.

Additionally, the present disclosure relates to a computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute aforesaid methods.

Background

Controlling a behaviour of electrical loads to provide energy balancing services to a national scale grid is well known. In the United Kingdom, the National Grid will contract for selectively turning on or off electrical loads for providing aforesaid balancing services. Such electrical loads optionally include, for example storage heaters.

Storage heaters each generally include a thermal energy storage system, for example usually including thermal bricks which are at least partially thermally insulated from an associated room environment. A thermal sensor, for example usually implemented using a bi-metallic strip as a sensing element, provides mechanical control over a vent that throttles a volume of air passing through an associated storage heater, and hence heat delivery to an associated room from the storage heater. Optionally, a mechanical knob provides a bias to the vent as a crude temperature control. Moreover, the storage heaters are usually wired to a separate fuse provided with a central timer than supplies the storage heaters with electricity on low tariff overnight rates.

More recently, electronic controls have been employed for controlling storage heaters, and some storage heaters have electronic controls integrated into their enclosures with controls for setting times when the heater is on or off, together with a wireless interface to room thermostats which are spatially remote from the enclosures of the storage heaters. A lowest cost and common configuration for home heating comprises several storage heaters, for example five storage heaters, wherein each storage heater is wired into rings or spurs which are in turn connected to an "economy 7' meter; such an "economy 7' meter takes into account relatively less expensive off-peak supply of electrical power. The storage heaters are not on a timed switch, as that function is contained within the meter, which supplies electricity in a low tariff period, for example midnight to 07:00 hrs, to an associated home heating system. A energy storage associated with such use of storage heaters is typically 7 hours at full power consumption. Storage heaters have associated radiators which can be specified at given powers and common sizes, for example including 0.85kW, 2.4kW and 3.4kW. For 3.4 kW, an associated current rating is 13A. House designers select radiator powers suited to room space heating requirements; for example, for a typical modern house, a total heating power required is around 15kW peak heat to keep warm on cold windy nights. Moreover, on an average winter day, the heat requirement can range from --5% to +100% of 15kW to maintain a comfortable room temperature. Smaller rooms, for example with 10 square metres floor area, have relatively smaller radiators, whereas larger rooms, for example with square metres floor area, have two or more relatively larger radiators.

Frequency control of loads is well known in the art, for example for implementing smart grids. Storage heaters are well known in the art. Moreover, smart meters are well known in the art.

The common point in many of the contemporary storage heater installations is via a 13A spur, wall socket box.

Summary

The present invention seeks to provide a system for controlling and measuring an electric grid balancing service from a population of loads that integrates with existing utility electricity metering systems.

Moreover, the present invention seeks to provide a load controller and associated method for controlling storage heaters to provide a frequency responsive service, namely an electric grid balancing service based upon grid operating frequency, that has properties of being non-random and deterministic and is independent of measurement of an internal energy state of one or more storage heaters; the load controller is beneficially optionally independent of a load, for example one or more storage heaters, and is designed to be installed serially in an electricity supply in a spur feeding one or more storage heaters.

According to a first aspect, there is provided a system as defined in appended claim 1: there is provided a system for providing a response service to an electrical grid, wherein the system includes at least one virtual response electricity meter, wherein the at least one virtual response electricity meter includes computing hardware which is operable to compute an availability of response from an arrangement of one or more loads equipped with load control devices, and to provide a measurement of response service.

The invention is of advantage in that an improved service to provide electrical grid stability is achievable by operation of the at least one virtual response electricity meter.

Optionally, the system is operable to employ pre-installed utility metering systems.

Optionally, in the system, the one or more loads are controlled spatially locally within a domestic or commercial premises. More optionally, in the system, the one or more loads are operable to control themselves in an autonomously manner, based on electrical grid frequency.

Optionally, in the system, the at least one virtual response electricity meter is operable to measure at least one physical parameter associated with its one or more loads for determining their energy storage status, wherein information derived from the at least one physical parameter is utilized to control the response service provided. More optionally, in the system, the at least one physical parameter includes a resistance measurement of the one or more loads.

Optionally, in the system, the computing hardware is operable to employ a plurality of mutually different control algorithms for controlling the one or more loads, and is operable to switch temporally between the algorithms when providing the service to reduce quantization of switching states within the system.

Optionally, in the system, the one or more loads include at least one storage heater heating element.

According to a second aspect, there is provided a method of operating a system to provide a response service to an electrical grid, wherein the method includes: (i) using at least one virtual response electricity meter of the system, wherein the at least one virtual response electricity meter includes computing hardware which is operable to compute an availability of response from an arrangement of one or more loads equipped with load control devices, and (ii) using the at least one virtual response electricity meter of the system to provide a measurement of response service.

Optionally, the method includes arranging for the system to employ pre-installed utility metering systems.

Optionally, the method includes controlling the one or more loads spatially locally within a domestic or commercial premises. More optionally, in the method, the one or more loads are operable to control themselves in an autonomously manner, based on electrical grid frequency.

Optionally, in the method, the at least one virtual response electricity meter is operable to measure at least one physical parameter associated with its one or more loads for determining their energy storage status, wherein information derived from the at least one physical parameter is utilized to control the response service provided. More optionally, in the method, the at least one physical parameter includes a resistance measurement of the one or more loads.

Optionally, the method includes arranging for the computing hardware to employ a plurality of mutually different control algorithms for controlling the one or more loads, and is operable to switch temporally between the algorithms when providing the service to reduce quantization of switching states within the system.

Optionally, in the method, the one or more loads include at least one storage heater heating element.

According to a third aspect, there is provided a grid operated with response service provided from at least one virtual meter according of the system pursuant to the first aspect.

According to a fourth aspect, there is provided a method of providing an aggregated response service, wherein the service is measured from at least one virtual meter of the system pursuant to the first aspect.

According to a sixth aspect, there is provided a load control device providing data and load control to the at least one virtual meter of the system pursuant to the first aspect.

According to a seventh aspect, there is provided an electricity meter providing the function of a virtual response meter as employed in the system pursuant to the first aspect.

According to a eighth aspect, there is provided a gateway device providing a function of a virtual response meter of the system pursuant to the first aspect.

According to a ninth aspect, there is provided an in-home energy monitoring device providing the function of a virtual response meter of the system pursuant to the first aspect.

According to a tenth aspect, there is provided a response meter that measures a response service delivered from a plurality of loads equipped with load control devices and provides a measurement of response service using pre-installed utility metering systems.

According to an eleventh aspect, there is provided a load controller comprising a first measuring arrangement for measuring a grid frequency, a second measuring arrangement for measuring a power flow, and a control arrangement for controlling power flow that responds to grid frequency to provide a service to a national grid controlling authority in a deterministic and linear method, whereby two or more different control programs are used for controlling the power flow, and the two or more control programs are arranged in operation to change a switch frequency in a scheduled and determined pattern.

According to a twelfth aspect, there is provided a computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute a method pursuant to the second aspect.

It will be appreciated that features of the invention are susceptible to being combined in various combinations without departing from the scope of the invention as defined by the appended claims.

Description of the diagrams

Embodiments of the present invention will now be described, by way of example only, with reference to the following diagrams wherein: FIG. 1 is an illustration of a domestic wiring arrangement in which embodiments

of the present disclosure cab be implemented; and

FIG. 2 is an illustration of a load controller, for example for use in the domestic wiring arrangement of FIG. 1.

In the accompanying diagrams, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.

Description of embodiments of the disclosure

In overview, embodiments of the present disclosure are concerned with controlling a behaviour of electrical loads to provide energy balancing services to a national-scale electricity grid. In the UK, National Grid contracts for having an option of turning on or off one or more electrical loads. Moreover, embodiments of the present disclosure are also concerned with load control devices which are integrated together with a service measurement system. Furthermore, embodiments of the present disclosure are concerned with a system for measuring an energy balancing service provided from a collection of loads integrated with an existing automatic meter reading system.

In particular, for example, embodiments of the present disclosure are concerned with a device for controlling storage heating arrangements which are integrated into a 13A socket spur. Additionally, embodiments of the present disclosure are also concerned with a storage heating controller, as will be elucidated in greater detail below.

In FIG. 1, there is shown an illustration of features regarding a manner in which, in a domestic or commercial premises 1, electrical loads 3, 4 (Li, L2) are connected via an in-house wiring 6, via a utility meter 2, to a local distribution 12 and a national grid 7.

An automatic meter reading system (AMR) comprises a home area network (HAN) constructed from load control blocks 5a, 5b, which are operable to communicate via a home network 13, in this case to a gateway, into the meter 2. In the UK, contemporary wireless Zigbee-based communication links provide an effective home communication network; "ZigBee" is a registered trade mark. In the domestic or commercial premises 1, meter readings are provided via another external network 8a, 8b, from the meter 2 to a server and its associated database 9. In the United Kingdom (UK), such data and communication services are provided centrally and operated under a licence from Government.

Utilities in the UK, such as nPower, have access to meter data readings on a national database; "nPowe( is a registered trade mark. These meter readings on the national database are integrated with their utility information technology (IT) infrastructure 10 and can be interrogated by computer applications 11.

-B-

in FIG. 1, load control devices are able to control loads of the domestic or commercial premises I in a local manner. In one embodiment, one or more of the loads are controlled based on a measured grid frequency at the one or more loads.

Such control is known as dynamic demand" and is autonomous and local.

Moreover, local and autonomous dynamic demand requires no communications infrastructure to support its operation, and is different to dispatched services such as demand response.

In order to ascertain a financial value of energy balancing services provided in respect of the domestic or commercial premises 1, it is necessary to measure a performance of the energy balancing service provided therefrom. One object of embodiments of the present disclosure is to allow such a function of measuring performance within a scope of a present definition of UK Smart meter deployment.

Technical specifications pertaining to such UK Smart meter deployment do not currently allow load control or allow information regarding each load's power consumption to be sent to an electrical power supplying utility.

In one embodiment, the electrical loads Li, L2 are connected to a mains electricity line Ln, and are controlled autonomously and locally, wherein each load Li, [2 is operable to decide when to switch itself on or off, based on electrical grid operating frequency; the electrical grid operating frequency deviates from a nominal frequency fo, for example substantially 50 Hz for the UK, depending upon power load coupled to the electrical grid. Such switch-on and switch-off information is known and available on the aforementioned HAN. The meter 2 also is operable to measure an instantaneous power consumption occurring within the domestic or commercial premises I. Therefore, the HAN is operable to compute: (a) the individual loads power consumption based on observing power changes and correlating with known load switch events in time; (b) whether a load is on or off; (c) whether a load is available to turn on or off and (d) whether a load responded on or off to a grid event.

Data processing arrangements, namely "intelligence", required to make this computation from the data on the HAN network is optionally beneficially incorporated into the meter 2; optionally,a master load or a separate control device on the HAN network is beneficially operable to execute these computations.

The data available is then beneficially aggregated for the domestic or commercial premises 1. However, the aforementioned UK Smart Meter programme constrains the data that can be sent to central database. Therefore, in order to measure the household's aggregated service provided by the domestic or commercial premises 1, it is necessary to reduce the data to meter readings. It is possible to provide meter readings for availability of kWs to switch integrated over time, namely a kwh reading.

Optionally, minimally, one kwh availability data point is provided. Moreover, optionally, it is also feasible to provide two availability measurements, namely one availability measurement providing an indication of an availability to switch loads on, and another providing an indication of an availability to switch loads off.

Viewed from the utility database, the energy balancing service provided from the domestic or commercial premises I can be considered to meter readings. For example, the availability in kWs integrated over time can be displayed as a kwh meter reading. Two such meters can, for example, measure response availability for high and low conditions. Using features provided for metering, it is possible to gain 1⁄2 hourly resolution data. The meters have capability to report energy use in defined 1⁄2 hourly slots, which are optionally separated for week and weekend days. This provides further granular data regarding when the response is made available from the domestic or commercial premises I. The utility then beneficially aggregates the availability potential service from N domestic or commercial premises 1, wherein N is greater than unity, and optionally at least many hundreds of such premises 1, and provides to the electrical grid a measurement of the service provided for which proprietors a payment is received, for example by owners of the premises I. This payment is optionally returned to individual home owners, for example as a rebate on their electricity bill.

The measurement of response availability requires the HAN network constructing virtual electricity meters. In an example embodiment, two such meters are used to measure high and low response availability. Optionally, these meters are added to form one meter which is operable to monitor high and low response availability from the premises 1.

There is thereby provided a system that can be enhanced by adding further virtual meters. Actual service delivery can thereby, for example, be measured. When a load responds to a grid event, those consumption kws associated with the load can be added together to report delivered service.

An accuracy of measurement required for response delivery or response availability is less than utility supply classes. The virtual meters therefore can learn what each load's power consumption is by averaging time-correlated meter readings. Load's know when they switch on or off, and therefore by observing the meter reading change, it is possible to filter intelligently several load power change events and allocate this power to a given load. For example, for loads that provide a substantially constant resistance, namely purely resistive loads, it is beneficially possible to compute their power using measured line voltage and an averaged load resistance, and computing their power therefrom. However, some loads will have variable power utilization, and it is then optionally necessary to estimate their power consumption based on current meter reading data.

There are various techniques known in the art for estimating accurately a power consumption of an individual load based on historical meter reading data correlated with switch points of that individual load.

While it is feasible for the meter to undertake these functions, it is also feasible for other HAN network devices, either a specific gateway or a home area load, to compute the virtual meter. Similarly, it is feasible for a specific gateway device to have another communications channel, for example via connection to the contemporary Internet via 3G or wired Internet, to communicate bi-directionally information concerning load and metering data to an aggregator. Through such a communication route, normal demand response is beneficially provided. -11 -

Optionally, a separate gateway or load intelligence is employed to optimise the consumption time profiles of the one or more loads. For example, homes with solar of other distributed generation optionally use the HAN network, wherein signals from such micro-power-generation to optimise the consumption of in-home generated energy. In one such example embodiment, the generation meter provides data to the HAN network, and load control devices together with the virtual meter processing power are operable in a selective manner to switch loads to use optimally in-home generation.

Optionally, the HAN network is integrated with a web service, so that browsers on wireless communication devices, for example mobile phones and smart phones, can be used for controlling the in-home energy use and to optimise the availability of one or loads for response.

By using the virtual meter technique, as aforementioned, the response service delivered is beneficially integrated into existing AMR technology and databases.

Using half-hourly time based resolution provides substantially near instantaneous measurement of response, for practical purposes. Across a large population of homes, for example the domestic or commercial premises 1, the response service will average well and underlying load profiles will become evident. Processing past data using time-of-day, weekday/weekend and seasonality together with metrics on weather and similar, allows accurate prediction of future service to be achieved in the system. This provides, for example, National Grid in the UK with confidence that the service will be provided. Moreover, a functionality in the system of measuring both availably and service delivery allows validation of the supplied service. For example, it not optionally be necessary to have 100% monitoring of delivered service, for example for payment purposes. A sub-population of domestic or commercial premises I optionally provides a statistical sample that the availability prediction and delivery corresponded. Moreover, it is optionally feasible to equip a sub-sample of the population of domestic or commercial premises I with more complex metering, if it was desired to capture and demonstrate service delivery against grid events with finer time resolution, for example to a temporal resolution of 1 second. -12-

In FIG. 2, a load controller 21, for example for use in an arrangement as depicted in FIG. 1, as described in the foregoing, is integrated into a standard 13A spur enclosure 22. Moreover, in FIG. 2, a standard storage heater is denoted by 23, with its associated control vent valve denoted by 24, and its associated thermal storage element depicted by 25. House-wiring comprises an "economy 7" meter 26, one or more fuses 27, together with rings and spurs 28. In a preferred embodiment of the present disclosure, a controller is connected in the 1 3A spur enclosure 22, and this provides a retrofit opportunity, whereby smart control is achievable without changing any existing heater. Of course, such a control element is optionally integrated into the heater itself, the electricity meter or other places in an electricity supply to a radiator.

The load controller 21 comprises a relay 29, an input mains electricity pod 30, an output electricity pod 31, an electronic load control arrangement 32, a electricity metering arrangement 33, and optionally a home area network communications arrangement 34.

The relay 29 is operable to provide control of the electricity flowing into the storage heater 23. Optionally, an electronic relay is used for implementing the relay 29, namely an electronic relay which is capable of fast switching (for example, via pulse width modulation (PWM) control), thereby providing a functionality to modulate the power flowing into the storage heater 23. Optionally, the controller 21 includes an arrangement for measuring the resistance of a heating element of the storage heater 23. Injection and synchronous detection of a low level non-mains frequency test signal, for example, allows the resistance of the heating element to be measured.

The resistance is determinable by the meter; however, it may be useful to detect the load resistance provided by the heating element, when the heating element is off and when no mains is supplied to the heating element. A load control device is beneficially employed for the storage heater 23 that is operable to measure mains frequency using methods, for example, known in the art. In a preferred embodiment of the present disclosure, a counter timer is operable to measure zero-crossings of mains alternating electricity supplied to the heating element of the storage heater 23, wherein an output from the counter timer is provided to a non-synchronous low pass filter to provide a filtered output signal indicative of grid frequency, for use for control purposes in the system. Other techniques such as phase-locked-loop (PLL) detection and Fourier transforms provide optimal estimators of grid frequency, namely providing lowest measurement noise for defined measurement bandwidths.

The load controller is able to provide either on/off or modulated control of the power, and hence energy, flowing into the heating element of the storage heater 23. Many control strategies are possible for controlling temporal-varying application of power to the heating element. Beneficially, the service provided to, for example, the National Grid is measured as a response availability. There are in practice two availabilities, high and low response availabilities. A high response availability corresponds to the number of kWthat can be turned on, for example in respect of the heating element. A low response availability corresponds to the number of kW that can be turned off, for example in respect of the heating element. The availability is provided in defined time windows, and, in the UK, this is linked to 48 (occasionally 50), substantially 1⁄2 hourly slots of a diurnal period. Some countries operate with a finer temporal resolution, for example 5 minute slots in some US ISO's.

In operating the storage heater 23 without measuring its energy storage, it is however possible to estimate the storage capability thereof by using the power flows into the storage heater 23, and known switch events when an internal thermostat of the storage heater 23 disconnects its load, namely disconnects the heating element.

Optionally, other measurements, for example a room temperature measured at the 13A spur, determined wirelessly by room thermostats, internal sensors in the storage heater can be used to improve this measurement. However, one objective of embodiments of the present disclosure is to have a remote easy-to-integrate load controller, namely the controller 21.

As aforementioned, the load controller integrated meter can measure the power flow into the storage heater 23. Moreover, it can also control the power flow thereto, either on-off, or optionally modulated at power levels intermediate between on and off A local grid frequency can be optionally measured, as aforementioned. Optionally, other parameters can also be determined or estimated, either locally or by other sensors. -14-

In normal operation, a meter switch for the storage heater 23 applies power at 24:00 hrs, namely at midnight. A thermal storage state of the storage heater 23 is unknown, but a suitable assumption is that it is zero. A resistance measurement in the load controller 21 optionally determines if there is residual heat, for example by measuring a resistance of the heater element. Storage heaters are usually sized to absorb 7 hours storage of thermal energy at full power consumption of the storage heater 23.

Depending on the room heating requirements during a night period pertaining, wherein the start heat energy has been stored, around 05:00 hrs in the morning, the storage heater 23 reaches its full thermal state, and an internal switch of the storage heater 23 disconnects the heater element of the storage heater 23. The load controller 21 is operable to spot this event by measuring a change in power consumption, or by performing a resistance measurement on the heater element of the storage heater 23. The event is thus a FULL storage event.

At 07:00 hrs, the "economy 7" meter disconnects the electrical supply to the storage heater 23. Optionally, there is potentially a need for a battery or other power source for coping with a loss of mains electricity to the load controller 21. At midnight, namely 24:00 hrs, the cycle starts again. If the day has been warm, then, when power from the "economy 7' meter is switched on, the thermal storage element of the storage heater may be, for example, 90% full. In such case, the full storage event may be repeated at 01:00 hrs. If the night is very cold, potentially the storage heater 23 depletes its thermal storage at, for example, 06:00 hrs, when the "economy 7' meter is supplying electricity to the storage heater 23. This allows a record of an EMPTY storage event to be generated. More likely, around 17.30 hrs, a householder returns from work on cold days and finds that the thermal storage of the storage heater 23 is exhausted, and enjoys a cold evening until midnight, namely 24:00 hrs.

However, the intelligent load controller can use its low power resistance measurement to determine a state of the thermostat switch in the radiator connecting, even if there is no electricity supplied from the "economy 7" meter.

Hence, the load controller 21 can determine EMPTY events, without mains being supplier to the storage heater 23. Optionally, the resistance measurement of the heater element of the storage heater 23 provides an indication, but not measurement, of the thermal energy state of the storage heater 23. However, correlation of full and empty energy states optionally improves a measurement accuracy of the thermal energy state. Further accuracy improvements are optionally obtained by correlating with power measurements from the load controller integrated meter, and optionally the outflow of energy from the storage heater 23 is estimated from other measurements, for example temperature measurements of the energy storage element of the storage heater 23 as a function of time and also room temperature measurements. Such direct measurements, which are available, includes a room temperature at the load controller, for example. An Infrared sensor is optionally used to make an approximate measurement of room ambient temperature, and a PIR function can be optionally used to determine room occupancy.

The load controller 21 functions to optimise the flow of electrical energy, both to keep the given room warm, and to provide a grid service availability. The storage heater 23 availability is however constrained by other factors. For example, when in an on state, the "economy 7' meter is not available at all between 07:00 hrs and 24:00 hrs, namely 07:00 hrs and midnight, as described in the foregoing. Clearly, a novel economy response service is beneficially introduced, and electricity provided for a 24 hour diurnal period. Optionally, it is advantageous in the system described, if the meter deliberately switches the supply on/off/on to signal "real time"; the load controller 21 optionally determines an externally generated TIME signal event from its electrical mains supply.

In regard to a normal "economy 7" service, at midnight, namely 24:00 hrs, the load controller 21 receives mains electricity. It can optionally hold off its load, namely not apply power to the heater element of the storage heater 23; in such a scenario, the load is now available to turn on, namely to provide a high response. The load controller 21 is beneficially operable to aim to switch the load on, and get the heat storage in the thermal storage element of the storage heater 23 to a maximum by 07:00 hrs. In order to achieve this aim, the load controller 21 eventually determines the load needs to be turned on. At this point, it is not available for purposes of providing a high response. However, it is now available for providing a low response, namely it can be turned off While the load is available, depending on the measurement of grid frequency, the load controller 21 needs to respond, namely to change a load state of the heater element of the storage heater 21. In general, all loads having a mutually similar characteristic and timing does not provide a linear -16-dynamic frequency response service; while they can ALL switch at one frequency, this is called a FGDM service in the UK, it is advantageous and gets paid more to provide a dynamic response. In this embodiment of the present disclosure, this service is provided by many on/off loads being aggregated within the system. For example, in an example arrangement, there are 32 possible load control algorithms.

These load control algorithms are chosen, so that the frequency switch points for providing response are different, and so that each of the 32 loads are operable to change their associated switching state depending on their local electricity grid frequency measurement. The switch frequencies in the 32 control algorithms are beneficially chosen, so that the aggregated response from a sum of the 32 loads increases as a function of increasing frequency. For example, at 50+1/32*0.5Hz, one load will switch; at 50+2/32*0.5Hz, two loads will switch; and at 50+32/32*0.5, all loads will switch, and so forth. The 32 loads, each with a different but deterministic load control algorithm, will provide a substantially linear service, although it is of a quantised nature. Increasing 32 loads to say 1024 loads decreases such quantisation. Given the requirements of the electrical grid, 1024 loads provides 1/2mHz quantisation, which is easily low enough so as not to cause an issue with analog generation throttle feedback loops, namely droop, employed to stabilize the electrical grid. However, 32 loads represent a marginal solution, in view of such quantization issues.

Having a given load always switch at the same grid frequency is, however, a less desirable feature, in that the given load, for example switching at a 1/32 point, is switched more often than the load at a 32/32 point, with regard to thresholds at which a response service is provided. Within the 32 load control algorithms in this embodiment, control points, namely threshold for switching loads, are changed daily in a deterministic manner. A simplest example deterministic manner would be that, on day 1, a given load controller 21, switches at a 1/32 point, on day 2, the given load controller 21 switches at a 2/32 point, and so forth. However, many other possibilities exist for implementing such a deterministic manner, giving rise to multitude of potential switching control methods; however, by substantially avoiding random selection and utilizing deterministic control algorithms makes is relatively easier to model population of the load controllers 21 and their associated loads, enable linear systems analysis to be employed. A beneficially feature is that each load controller 21 has a selected 1 from n control strategy, wherein each control strategy is designed to provide features in respect of a linear response, which is deterministic but sharing the switching point stress" evenly when averaged over time, for a population of load controllers 21 and their associated loads, namely a

system pursuant to the present disclosure.

Pursuant to the present disclosure, it is optionally feasible to build aforementioned functionality into the "economy 7 meter", but this increases the coarseness of an individual houses' response and potentially increases a likelihood of a cold house being experienced by its owner. With control in the load controller 21, the risk is having one cold room in a house, which is potentially acceptable in many cases.

In determining the service delivery to grid from the system, a United Kingdom patent document GB134703.8 describes one method of integrating the service delivery through the UK Smart Metering network. Other methods are possible, for example the load controller 21 optionally has a display or alternative port to allow data to be communicated regarding the service provided by operation of the load controller 21 selectively switching its associated load in respect of the electrical grid.

Modifications to embodiments of the invention described in the foregoing are possible without departing from the scope of the invention as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "consisting of", "have", "is" used to describe and claim the present invention are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural. Numerals included within parentheses in the accompanying claims are intended to assist understanding of the claims and should not be construed in any way to limit subject matter claimed by these claims.

Claims

CLAIMS1. A system for providing a response service to an electrical grid, wherein the system includes at least one virtual response electricity meter, wherein the at least one virtual response electricity meter includes computing hardware which is operable to compute an availability of response from an arrangement of one or more loads equipped with load control devices, and to provide a measurement of response service.
2. A system as claimed in claim 1, wherein the system is operable to employ pre-installed utility metering systems.
3. A system as claimed in claim 1, wherein the one or more loads are controlled spatially locally within a domestic or commercial premises.
4. A system as claimed in claim 3, wherein the one or more loads are operable to control themselves in an autonomously manner, based on electrical grid frequency.
5. A system as claimed in claim 1, wherein the at least one virtual response electricity meter is operable to measure at least one physical parameter associated with its one or more loads for determining their energy storage status, wherein information derived from the at least one physical parameter is utilized to control the response service provided.
6. A system as claimed in claim 5, wherein the at least one physical parameter includes a resistance measurement of the one or more loads.
7. A system as claimed in claim 1, wherein the computing hardware is operable to employ a plurality of mutually different control algorithms for controlling the one or more loads, and is operable to switch temporally between the algorithms when providing the service to reduce quantization of switching states within the system.
8. A system as claimed in claim 1, wherein the one or more loads include at least one storage heater heating element.
9. A method of operating a system to provide a response service to an electrical grid, wherein the method includes: (i) using at least one virtual response electricity meter of the system, wherein the at least one virtual response electricity meter includes computing hardware which is operable to compute an availability of response from an arrangement of one or more loads equipped with load control devices, and (ii) using the at least one virtual response electricity meter of the system to provide a measurement of response service.
10. A method as claimed in claim 9, wherein the method includes arranging for the system to employ pre-installed utility metering systems.
11. A method as claimed in claim 9, wherein the method includes controlling the one or more loads spatially locally within a domestic or commercial premises.
12. A method as claimed in claim 11, wherein the one or more loads are operable to control themselves in an autonomously manner, based on electrical grid frequency.
13. A method as claimed in claim 9, wherein the at least one virtual response electricity meter is operable to measure at least one physical parameter associated with its one or more loads for determining their energy storage status, wherein information derived from the at least one physical parameter is utilized to control the response service provided.
14. A method as claimed in claim 13, wherein the at least one physical parameter includes a resistance measurement of the one or more loads.
15. A method as claimed in claim 9, wherein the method includes arranging for the computing hardware to employ a plurality of mutually different control algorithms for -20 -controlling the one or more loads, and is operable to switch temporally between the algorithms when providing the service to reduce quantization of switching states within the system.
16. A method as claimed in claim 9, wherein the one or more loads include at least one storage heater heating element.
17. A grid operated with response service provided from at least one virtual meter according of the system as claimed in claim 1.
18. A method of providing an aggregated response service, wherein the service is measured from at least one virtual meter of the system according to claim 1.
19. A load control device providing data and load control to the at least one virtual meter of the system according to claim 1.
20. An electricity meter providing the function of a virtual response meter as employed in the system as claimed in claim 1.
21. A gateway device providing a function of a virtual response meter of the system according to claim 1.
22. An in-home energy monitoring device providing the function of a virtual response meter of the system according to claim 1.
23. A response meter that measures a response service delivered from a plurality of loads equipped with load control devices and provides a measurement of response service using pre-installed utility metering systems.
24. A load controller comprising a first measuring arrangement for measuring a grid frequency, a second measuring arrangement for measuring a power flow, and a control arrangement for controlling power flow that responds to grid frequency to provide a service to a national grid controlling authority in a deterministic and linear method, whereby two or more different control programs are used for controlling the -21 -power flow, and the two or more control programs are arranged in operation to change a switch frequency in a scheduled and determined pattern.
25. A computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute a method as claimed in claim 9.