CN115313482A - Wind, light, fire and storage combined delivery optimization configuration method, system, equipment and medium - Google Patents
Wind, light, fire and storage combined delivery optimization configuration method, system, equipment and medium Download PDFInfo
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Abstract
The invention relates to a wind, light, fire and storage combined delivery optimization configuration method, a system, equipment and a medium, which comprises the following steps: determining a wind-solar-energy-fire-storage outgoing power transmission channel and an outgoing power transmission channel curve thereof based on the capacity of an outgoing power transmission channel to be planned, and determining an outgoing power transmission channel configuration energy storage charging and discharging principle and an outgoing method; based on the determined energy storage charging and discharging principle and the determined delivery power transmission channel configuration energy storage method, a wind-light-fire-storage combined delivery model is established by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and the established wind-light-fire-storage combined delivery model is solved by adopting a particle swarm algorithm to obtain the optimal capacity ratio of the wind-light-fire-storage. The method can be widely applied to the field of power grid optimal configuration.
Description
Technical Field
The invention relates to a wind, light, fire and storage combined delivery optimization configuration method, system, equipment and medium considering system cost, and belongs to the field of power grid optimization configuration.
Background
In order to gradually realize carbon peak reaching before 2030 years, carbon neutralization before 2060 years is in the target vision, a clean low-carbon, safe and efficient energy system is constructed, local power supply side, power grid side and load side resources are optimized and integrated, advanced technical breakthrough and system mechanism innovation are taken as supports, a novel power system development path with high integration of 'source-grid-load-storage' is constructed, and conventional power supplies of stocks are utilized, energy storage equipment is reasonably configured, and wind, light, fire and storage combined delivery is pushed to be the future key research direction.
However, in the current optimal configuration of the wind, light, fire and storage combined delivery process, the problem of high power abandon rate caused by not considering the prior transmission of wind, light and new energy is solved, and the configuration of energy storage equipment is lack of flexibility.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method, a system, a device and a medium for optimal configuration of wind, light, fire and storage combined delivery, so as to provide a support for increasing the proportion of renewable energy in the combined delivery system.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a wind, light, fire and storage combined delivery optimization configuration method, which comprises the following steps:
determining a wind-solar-energy-fire-storage outgoing power transmission channel and an outgoing power transmission channel curve thereof based on the capacity of an outgoing power transmission channel to be planned, and determining an outgoing power transmission channel configuration energy storage charging and discharging principle and an outgoing method;
based on the determined energy storage charging and discharging principle and the determined delivery method of the delivery power transmission channel configuration, a wind-light-fire-storage combined delivery model is established with the aim of minimum operation cost of the wind-light-fire-storage combined delivery system, and the established wind-light-fire-storage combined delivery model is solved by adopting a particle swarm algorithm to obtain the optimal capacity ratio of the wind-light-fire-storage.
Further, the method for determining the wind-solar-thermal storage delivery power transmission channel and the delivery power transmission channel curve thereof based on the capacity of the delivery power transmission channel to be planned, and determining the energy storage charging and discharging principle and the delivery method of the delivery power transmission channel configuration includes:
determining a wind-solar-fire-storage delivery power transmission channel and a delivery power transmission channel curve thereof based on the capacity of the delivery power transmission channel to be planned;
determining an energy storage charging and discharging principle of the external power transmission channel configuration based on the determined wind-solar-fire storage external power transmission channel;
on the basis of determining the curve of the outgoing power transmission channel and the principle of energy storage charging and discharging, the wind, light, fire and energy storage combined outgoing method is determined.
Further, the wind-solar-fire-storage outgoing power transmission channel comprises three outgoing power transmission channels of extra-high voltage direct current, extra-high voltage alternating current and conventional alternating current, and the curve of the outgoing power transmission channel is determined based on the determined outgoing power transmission channel, and the method comprises the following steps:
when the channel is an extra-high voltage direct current transmission channel, the curve characteristic of the outgoing transmission channel is as follows: during the load trough period, i.e. 0-00 and 23;
when the power transmission channel is an extra-high voltage alternating current power transmission channel, the curve characteristic of the external power transmission channel is as follows: during the load trough period, 0-7, 00, 23;
when an extra-high voltage conventional alternating-current power transmission channel is selected, the curve characteristic of the external power transmission channel is as follows: during the load trough period, 0-7, 00-00, 23.
Further, the determining, based on the determined outgoing power transmission channel, that the outgoing power transmission channel is configured with an energy storage charging and discharging principle includes:
when thermal power operates according to the lowest load rate and the theoretical wind-solar output is larger than the capacity of an outgoing power transmission channel, wind-solar energy meets the power balance requirement in a power abandoning mode, and an energy storage facility is in a charging state;
and when the thermal power operates according to the lowest load rate and the theoretical wind-solar output is smaller than the capacity of the outgoing power transmission channel, the energy storage facility is in a discharging state.
Further, the wind, light, fire and storage combined delivery model comprises an objective function and constraint conditions thereof, wherein the objective function is used for minimizing the operation cost of the wind, light, fire and storage combined delivery system;
the objective function comprises the initial investment cost of wind, light and fire storage and the operation and maintenance cost of equipment, and the calculation formula is as follows:
F＝min(C 0 +C m )
C 0 ＝∑(N wt C wt +N pv C pv +N ther C ther +N bat C bat )fcr
C m ＝∑(k wt0 P wt Δt+k pv0 P pv Δt+k ther0 P ther Δt+k bat0 P bat Δt)
in the formula, F is the outward conveying operation cost; c 0 To initial investment costs, C m For operating maintenance costs, N wt 、N pv 、N ther 、N bat Respectively the installed capacities of wind power, photovoltaic, thermal power, energy storage and other equipment, and the unit is MW; c wt 、C pv 、C ther 、C bat The investment prices of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively in units of ten thousand yuan/MW; f. of cr Is a depreciation factor; r is depreciation rate; lf is the life cycle; k is a radical of wt0 、k pv0 、k ther0 、k bat0 Respectively representing the operation and maintenance cost coefficients of wind power, photovoltaic, thermal power, energy storage and other equipment, wherein the unit is ten thousand yuan/MWh; p wt 、P pv 、P ther 、P bat The unit is MW, and the unit is the power capacity of wind power, photovoltaic, thermal power, energy storage and other equipment; Δ t is the change time;
the constraint conditions comprise power balance constraint, wind turbine generator capacity constraint, photovoltaic power generation system capacity constraint, energy storage facility charge-discharge capacity and power constraint, thermal power unit output upper and lower limit constraint, renewable energy utilization constraint and renewable energy power rejection constraint.
Further, when the established wind, light, fire and storage combined delivery model is solved by adopting the particle swarm optimization, the method comprises the following steps:
inputting parameters of wind, light, fire and user load and simulation basic parameters;
determining the space dimension of the population according to the types and models of the wind turbine generator and the photovoltaic generator to be optimized, and initializing the initial position value and the speed value of the particle population;
calculating wind power and photoelectric power according to power output models of the wind turbine generator and the photoelectric generator; judging the operation state of each unit in the wind-solar-fire storage and delivery system according to a scheduling strategy;
calculating the fitness of all particle populations on the basis of the previous step, recording the position and the fitness of the optimal individual, and updating the position and the speed of the next generation of particle swarm;
calculating the fitness of the new population and judging whether the maximum iteration times are met; if the maximum iteration times are not met, returning to re-optimizing; and if the maximum iteration times are met, outputting the optimal position and fitness optimal value of the optimal individual as the optimal wind-solar-fire storage capacity ratio.
In a second aspect, the invention provides a wind, light, fire and storage combined delivery optimization configuration system, which comprises:
the external power transmission channel determining module is used for determining a wind-solar energy storage external power transmission channel and an external power transmission channel curve thereof based on the capacity of the external power transmission channel to be planned, and determining an external power transmission channel configuration energy storage charging and discharging principle and an external power transmission method;
the wind-light-fire-storage optimal capacity ratio calculation module is used for configuring an energy storage charging and discharging principle and a delivery method based on the determined delivery power transmission channel, establishing a wind-light-fire-storage combined delivery model by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and solving the established wind-light-fire-storage combined delivery model by adopting a particle swarm algorithm to obtain the wind-light-fire-storage optimal capacity ratio.
Further, the wind-solar-fire-storage combined delivery model comprises an objective function and constraint conditions thereof, wherein the objective function is used for minimizing the operation cost of the wind-solar-fire-storage combined delivery system;
the objective function comprises the initial investment cost of wind, light and fire storage and the operation and maintenance cost of equipment, and the calculation formula is as follows:
F＝min(C 0 +C m )
C 0 ＝∑(N wt C wt +N pv C pv +N ther C ther +N bat C bat )fcr
C m ＝∑(k wt0 P wt Δt+k pv0 P pv Δt+k ther0 P ther Δt+k bat0 P bat Δt)
in the formula, F is the outward conveying operation cost; c 0 To initial investment costs, C m Maintenance costs for operation，N wt 、N pv 、N ther 、N bat Respectively the installed capacities of wind power, photovoltaic, thermal power, energy storage and other equipment, and the unit is MW; c wt 、C pv 、C ther 、C bat The investment prices of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively in units of ten thousand yuan/MW; f. of cr Is a depreciation factor; r is depreciation rate; lf is the life cycle; k is a radical of wt0 、k pv0 、k ther0 、k bat0 Respectively representing the operation and maintenance cost coefficients of wind power, photovoltaic, thermal power, energy storage and other equipment, wherein the unit is ten thousand yuan/MWh; p wt 、P pv 、P ther 、P bat The unit is MW, and the unit is the power capacity of wind power, photovoltaic, thermal power, energy storage and other equipment; Δ t is the variation time;
the constraint conditions comprise power balance constraint, wind turbine generator capacity constraint, photovoltaic power generation system capacity constraint, energy storage facility charge-discharge capacity and power constraint, thermal power unit output upper and lower limit constraint, renewable energy utilization constraint and renewable energy power rejection constraint.
In a third aspect, the present invention provides a processing device, which at least includes a processor and a memory, where the memory stores a computer program thereon, and the processor executes the computer program when executing the computer program to implement the steps of the wind, light, fire and storage combined delivery optimization configuration method.
In a fourth aspect, the present invention provides a computer storage medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the steps of the wind, light, fire and storage combined delivery optimization configuration method.
Due to the adoption of the technical scheme, the invention has the following advantages: according to the wind-light-fire-storage combined delivery optimal configuration method, on the basis of analyzing the matching among the wind at the sending end, the light resource and the load at the receiving end, the thermal power flexibility is adjusted, energy storage equipment with different durations is reasonably configured, and the problem that the power abandonment rate is high due to the fact that the prior wind-light-fire-storage combined delivery process is not considered to preferentially deliver new wind-light energy is effectively solved. Therefore, the method can be widely applied to the field of power grid optimization configuration.
Drawings
Various additional advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Like parts are designated with like reference numerals throughout the drawings. In the drawings:
fig. 1 is a flow chart of a wind, light, fire and storage combined delivery optimization configuration method provided by the embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the description of the embodiments of the invention given above, are within the scope of protection of the invention.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In some embodiments of the invention, the invention provides a wind, light and fire energy storage combined delivery optimal configuration method, which is used for adjusting thermal power flexibility and reasonably configuring energy storage equipment with different time lengths on the basis of analyzing the matching among wind, light resources and loads of a receiving end; and establishing a wind-light-fire-storage combined delivery model by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and solving the established wind-light-fire-storage combined delivery model by adopting a particle swarm algorithm to obtain the optimal capacity ratio of the wind-light-fire-storage. The problem that power abandon rate is high due to the fact that prior wind and light new energy sources are not considered to be preferentially transmitted in the existing wind and light fire storage combined delivery process is effectively solved.
Correspondingly, in other embodiments of the invention, a wind, light, fire and storage combined delivery optimization configuration system, a device and a medium are provided.
Example 1
As shown in fig. 1, the present embodiment provides a wind, light, fire and storage combined delivery optimization configuration method, which includes the following steps:
1) Determining a wind-solar-energy-fire-storage outgoing power transmission channel and an outgoing power transmission channel curve thereof based on the capacity of an outgoing power transmission channel to be planned, and determining an outgoing power transmission channel configuration energy storage charging and discharging principle and an outgoing method;
2) Based on the determined energy storage charging and discharging principle and the determined delivery power transmission channel configuration energy storage method, a wind-light-fire-storage combined delivery model is established by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and the established wind-light-fire-storage combined delivery model is solved by adopting a particle swarm algorithm to obtain the optimal capacity ratio of the wind-light-fire-storage.
Preferably, the step 1) includes the following steps:
1.1 Based on the capacity of the outgoing transmission channel to be planned, determining a wind-light-fire-storage outgoing transmission channel and an outgoing transmission channel curve thereof;
1.2 Based on the determined outgoing power transmission channel, determining that the outgoing power transmission channel is configured with an energy storage charging and discharging principle;
1.3 Based on the curve of the outgoing power transmission channel and the principle of energy storage charging and discharging, the wind, light, fire and energy storage combined outgoing method is determined.
Preferably, in step 1.1), the selectable wind, light and fire storage external transmission channels include three external transmission channels of an extra-high voltage direct current, an extra-high voltage alternating current and a conventional alternating current, and when the wind, light and fire storage external transmission channels are selected based on the capacity of the external transmission channel to be planned, the method includes:
determining an outgoing power transmission channel curve based on the determined capacity of the outgoing power transmission channel of 800 ten thousand kilowatts, comprising:
when the power transmission channel is an extra-high voltage direct current power transmission channel, the curve characteristic of the external power transmission channel is as follows: in the load trough period, namely 0-00 and 23;
when the power transmission channel is an extra-high voltage alternating current power transmission channel, the curve characteristic of the external power transmission channel is as follows: in the load trough period, 0 to 7, 00 to 23;
when an extra-high voltage conventional alternating-current power transmission channel is selected, the curve characteristic of the external power transmission channel is as follows: in the load trough period, 0 to 7, 00, 23.
Preferably, in step 1.2), determining, based on the determined outgoing power transmission channel, an energy storage charging and discharging principle of the outgoing power transmission channel configuration includes:
when thermal power operates according to the lowest load rate and the theoretical wind-solar output is larger than the capacity of an outgoing power transmission channel, wind-solar energy meets the power balance requirement in an electricity abandoning mode, at the moment, the stored energy plays a role in absorption, and the wind-solar energy abandoning quantity is reduced through energy storage charging;
when thermal power operates according to the lowest load rate and the theoretical wind-solar output is smaller than the capacity of the outgoing power transmission channel, the outgoing power transmission channel is provided with an energy storage and discharge space, energy storage and discharge are completed under the condition that wind-solar electricity abandoning is not increased, and the requirement of next energy storage and charge is met.
Preferably, in the step 1.3), the specific steps are as follows: the wind-light-fire-storage combined delivery method realizes complementary coupling of wind-light-fire-storage space and time, and maximally represents the characteristics of various renewable energy sources, namely, the wind speed is low in spring and summer, and the photovoltaic power station and the thermal power generating unit bear more loads to ensure the stability of the system due to long sunshine time. The energy storage device effectively promotes the consumption condition of renewable energy sources, and the stability of the system is ensured; the wind speed is high in autumn and winter, the sunshine time is short, and the occupied power of the photovoltaic power station and the thermal power generating unit is small.
Preferably, in the step 2), the established wind, light, fire and storage combined delivery model includes an objective function and its constraint conditions that minimize the operation cost of the wind, light, fire and storage combined delivery system.
The objective function comprises the initial investment cost of wind-solar fire storage and the operation and maintenance cost of equipment, and is as follows:
F＝min(C 0 +C m ) (1)
C 0 ＝∑(N wt C wt +N pv C pv +N ther C ther +N bat C bat )fcr (2)
C m ＝∑(k wt0 P wt Δt+k pv0 P pv Δt+k ther0 P ther Δt+k bat0 P bat Δt) (4)
in the formula, F is the outward conveying operation cost; c 0 To initial investment costs, C m For operating maintenance costs, N wt 、N pv 、N ther 、N bat Respectively the installed capacities of wind power, photovoltaic, thermal power, energy storage and other equipment, and the unit is MW; c wt 、C pv 、C ther 、C bat The investment prices of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively in units of ten thousand yuan/MW; f. of cr Is a depreciation factor; r is depreciation rate, and the 20-year life cycle is 5%; lf is the life cycle; k is a radical of wt0 、k pv0 、k ther0 、k bat0 Respectively representing the operation and maintenance cost coefficients of wind power, photovoltaic, thermal power, energy storage and other equipment, wherein the unit is ten thousand yuan/MWh; p wt 、P pv 、P ther 、P bat Respectively wind power, photovoltaic, thermal power and energy storage equipmentPower capacity of (d), in units of MW; Δ t is the change time.
The constraint conditions comprise power balance constraint, wind turbine generator capacity constraint, photovoltaic power generation system capacity constraint, energy storage facility charge and discharge capacity and power constraint, thermal power unit output upper and lower limit constraint, renewable energy utilization constraint and renewable energy power rejection constraint. Specifically, each constraint is as follows:
(1) constraint of power balance
In order to ensure the continuous and reliable power supply requirement of a receiving-end power grid on a load, the whole system after the grid connection of the wind-light-fire storage delivery system must meet the power balance constraint as follows:
P wt (t)+P pv (t)+P ther (t)+P bat (t)＝P L (t) (5)
in the formula, P wt (t),P pv (t),P ther (t),P bat (t),P L And (t) power values of the wind power channel, the photovoltaic channel, the thermal power channel, the energy storage channel and the delivery channel at the moment t are respectively.
(2) Wind turbine capacity constraints
Each power generation unit must have an upper and lower bound on installed capacity, otherwise extremes are likely to occur in economic optimization, as follows:
in the formula (I), the compound is shown in the specification,
the minimum capacity, the equivalent capacity and the maximum capacity of the wind power at the moment t are respectively.
(3) Photovoltaic power generation system capacity constraints
The maximum installed capacity of a photovoltaic power generation system also satisfies upper and lower limits, as follows:
in the formula (I), the compound is shown in the specification,
the minimum capacity, the equivalent capacity and the maximum capacity of the photovoltaic power at the moment t are respectively.
(4) Energy storage facility charge-discharge capacity and power constraints
In the wind, light, fire and storage combined delivery system, in order to ensure the safe charging and discharging and the service life of the energy storage facility, the charging state and the charging and discharging power of the energy storage facility need to be limited, and firstly, the energy storage power is smaller than the rated power; secondly, the charging and discharging of the charge state adjusting energy storage facility is carried out in a reasonable range, the overcharge and the overdischarge are avoided, and the safety risk is reduced, as follows:
P c (t)≤P bat ,P d (t)≤P bat (8)
SOC bat (t+1)＝SOC bat (t)+(P c (t+1)×η bat -P d (t+1)/η bat )/E bat (9)
0.1≤SOC bat (t)≤0.9 (10)
in the formula, P c (t) and
respectively the charging power and the discharging power of the energy storage facility at the moment t; p c (t + 1) and P d (t + 1) respectively the charging power and the discharging power of the energy storage facility at the moment of t + 1; p is bat Is the rated power of the energy storage facility; SOC bat (t) and SOC bat (t + 1) are SOC values of the energy storage facility at the time t and the time t +1 respectively; eta bat Charging efficiency for the energy storage facility; e bat Is the rated capacity of the energy storage facility.
(5) Thermal power generating unit output upper and lower limit restraint
The wind, light and fire storage combined delivery system encourages the thermal power generating unit with the adjusting capacity to carry out deep adjustment for increasing the consumption level of new energy, and the method comprises the following steps:
p ther,min ＜p ther ＜p ther,max (11)
in the formula, p ther,min And p ther,max The minimum output power and the maximum output power of the thermal power generating unit are respectively, and the unit is MW.
(6) Renewable energy utilization constraint
In order to reduce the scale of newly increased thermal power, in a wind-light-fire-storage combined external power transmission channel, the electric quantity proportion of renewable energy is not lower than 50% in principle, and the following formula is as follows:
(∑p wt +∑p pv -∑p abandon )/∑p all ≥r E (12)
in the formula, Σ p wt Sigma p for the wind power generation pv For photovoltaic power generation abandon To discard the electricity, Σ p all For the total power supply of the outgoing power transmission channel, r E Is the lower limit of the utilization rate of renewable energy.
(7) Renewable energy power curtailment
Renewable energy sources such as wind power and photovoltaic are restricted by natural conditions, and output has a great uncertain characteristic. In order to ensure the effective utilization of renewable energy power generation, the power abandoning rate of the wind-light-fire storage and delivery system is restricted as follows:
∑p abandon /(∑p wt +∑p pv +∑p abandon )≤r ar (13)
in the formula, r ar The lower limit of the power abandon rate of the renewable energy source.
Preferably, in the step 2), when the particle swarm algorithm is used to solve the established wind, light, fire and storage combined delivery model, the method includes the following steps:
2.1 Input wind, light, fire load and user load parameters and simulation base parameters.
The simulation basic parameters include learning factors, iteration times, inertia weights, population sizes, and the like, which are not described in detail herein.
2.2 According to the types and models of the wind turbine generator and the photovoltaic generator to be optimized, determining the spatial dimension of the population, and initializing the initial position value and the speed value of the particle population.
2.3 Wind power and photovoltaic power are calculated from the power output models of the wind turbine and photovoltaic turbine. And determining the operation state of each unit in the wind-solar-fire storage delivery system according to the scheduling strategy.
2.4 Based on the step 2.3), calculating the fitness of all particle populations, namely the outgoing operation cost (formula 1), recording the position and the fitness of the optimal individual, and updating the position and the speed of the next generation of particle swarm;
2.5 Calculating the fitness of the new population and judging whether the maximum iteration number is met; if the maximum iteration times are not met, returning to the step 2.3) to perform optimization again; and if the maximum iteration times are met, carrying out the next step.
2.6 Output the optimal value of the position and fitness of the optimal individual and finish the algorithm.
Example 2
The embodiment 1 provides a wind, light, fire and storage combined delivery optimization configuration method, and correspondingly, the embodiment provides a wind, light, fire and storage combined delivery optimization configuration system. The system provided by this embodiment may implement the wind, light, fire and storage combined delivery optimization configuration method of embodiment 1, and the system may be implemented by software, hardware or a combination of software and hardware. For example, the system may comprise integrated or separate functional modules or functional units to perform the corresponding steps in the methods of embodiment 1. Since the system of this embodiment is substantially similar to the method embodiment, the description process of this embodiment is relatively simple, and reference may be made to part of the description of embodiment 1 for relevant points.
The wind, light, fire and storage combined delivery optimization configuration system provided by the embodiment comprises:
the external transmission channel determining module is used for determining a wind-solar-energy-storage external transmission channel and an external transmission channel curve thereof based on the capacity of the external transmission channel to be planned, and determining an external transmission channel configuration energy storage charging and discharging principle and an external transmission method;
the wind-light-fire-storage optimal capacity ratio calculation module is used for configuring an energy storage charging and discharging principle and a delivery method based on the determined delivery power transmission channel, establishing a wind-light-fire-storage combined delivery model by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and solving the established wind-light-fire-storage combined delivery model by adopting a particle swarm algorithm to obtain the wind-light-fire-storage optimal capacity ratio.
Example 3
The present embodiment provides a processing device corresponding to the wind, light, fire and storage combined delivery optimization configuration method provided in embodiment 1, where the processing device may be a processing device for a client, such as a mobile phone, a notebook computer, a tablet computer, a desktop computer, and the like, to execute the method in embodiment 1.
The processing equipment comprises a processor, a memory, a communication interface and a bus, wherein the processor, the memory and the communication interface are connected through the bus so as to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes the wind, light, fire and storage combined delivery optimization configuration method provided by embodiment 1 when running the computer program.
In some embodiments, the Memory may be a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory, such as at least one disk Memory.
In other embodiments, the processor may be various general-purpose processors such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), and the like, and is not limited herein.
Example 4
The wind, light, fire and storage combined delivery optimization configuration method of this embodiment 1 may be embodied as a computer program product, and the computer program product may include a computer readable storage medium on which computer readable program instructions for executing the wind, light, fire and storage combined delivery optimization configuration method of this embodiment 1 are loaded.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any combination of the foregoing.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A wind, light, fire and storage combined delivery optimal configuration method is characterized by comprising the following steps:
determining a wind-solar-fire-storage delivery power transmission channel and a delivery power transmission channel curve thereof based on the capacity of a delivery power transmission channel to be planned, and determining a storage energy charging and discharging principle and a delivery method of the delivery power transmission channel;
based on the determined energy storage charging and discharging principle and the determined delivery power transmission channel configuration energy storage method, a wind-light-fire-storage combined delivery model is established by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and the established wind-light-fire-storage combined delivery model is solved by adopting a particle swarm algorithm to obtain the optimal capacity ratio of the wind-light-fire-storage.
2. The wind, light, fire and storage combined delivery optimization configuration method according to claim 1, wherein the method for determining the wind, light, fire and storage delivery transmission channel and the delivery transmission channel curve thereof and determining the delivery transmission channel configuration energy storage charging and discharging principle and the delivery method based on the delivery transmission channel capacity to be planned comprises the following steps:
determining a wind-solar-fire-storage delivery power transmission channel and a delivery power transmission channel curve thereof based on the capacity of the delivery power transmission channel to be planned;
determining an energy storage charging and discharging principle of the external transmission channel configuration based on the determined wind-solar-fire storage external transmission channel;
on the basis of determining the curve of the outgoing power transmission channel and the principle of energy storage charging and discharging, the wind, light, fire and energy storage combined outgoing method is determined.
3. The wind, light, fire and storage combined delivery optimization configuration method of claim 2, wherein the wind, light, fire and storage combined delivery power transmission channel comprises three delivery power transmission channels of extra-high voltage direct current, extra-high voltage alternating current and conventional alternating current, and when determining the delivery power transmission channel curve based on the determined delivery power transmission channel, the method comprises the following steps:
when the channel is an extra-high voltage direct current transmission channel, the curve characteristic of the outgoing transmission channel is as follows: during the load trough period, i.e. 0-00 and 23;
when the power transmission channel is an extra-high voltage alternating current power transmission channel, the curve characteristic of the external power transmission channel is as follows: during the load trough period, 0-7, 00, 23;
when an extra-high voltage conventional alternating-current power transmission channel is selected, the curve characteristic of the external power transmission channel is as follows: during the load trough period, 0-7, 00-00, 23.
4. The wind, light, fire and storage combined delivery optimization configuration method according to claim 2, wherein the determining of the delivery power transmission channel configuration energy storage charging and discharging principle based on the determined delivery power transmission channel comprises:
when the thermal power operates according to the lowest load rate and the theoretical wind-solar output is larger than the capacity of an outgoing power transmission channel, the wind-solar energy meets the power balance requirement in a power abandoning mode, and the energy storage facility is in a charging state;
and when the thermal power operates according to the lowest load rate and the theoretical wind-solar output is smaller than the capacity of the outgoing power transmission channel, the energy storage facility is in a discharging state.
5. The wind, light, fire and storage combined delivery optimization configuration method of claim 1, wherein the wind, light, fire and storage combined delivery model comprises an objective function and constraint conditions thereof which minimize the operation cost of a wind, light, fire and storage combined delivery system;
the objective function comprises the initial investment cost of wind, light and fire storage and the operation and maintenance cost of equipment, and the calculation formula is as follows:
F＝min(C 0 +C m )
C 0 ＝∑(N wt C wt +N pv C pv +N ther C ther +N bat C bat )f cr
C m ＝∑(k wt0 P wt Δt+k pv0 P pv Δt+k ther0 P ther Δt+k bat0 P bat Δt)
in the formula, F is the delivery operation cost; c 0 To initial investment costs, C m For operating maintenance costs, N wt 、N pv 、N ther 、N bat Respectively the installed capacities of wind power, photovoltaic, thermal power, energy storage and other equipment, and the unit is MW; c wt 、C pv 、C ther 、C bat The investment prices of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively in units of ten thousand yuan/MW; f. of cr Is a depreciation factor; r is depreciation rate; lf is the life cycle; k is a radical of formula wt0 、k pv0 、k ther0 、k bat0 Respectively representing the operation and maintenance cost coefficients of wind power, photovoltaic, thermal power, energy storage and other equipment, wherein the unit is ten thousand yuan/MWh; p wt 、P pv 、P ther 、P bat The unit is MW, and the unit is the power capacity of equipment such as wind power, photovoltaic, thermal power, energy storage and the like; Δ t is the change time;
the constraint conditions comprise power balance constraint, wind turbine generator capacity constraint, photovoltaic power generation system capacity constraint, energy storage facility charge-discharge capacity and power constraint, thermal power unit output upper and lower limit constraint, renewable energy utilization constraint and renewable energy power rejection constraint.
6. The wind, light, fire and storage combined delivery optimization configuration method of claim 5, wherein when solving the established wind, light, fire and storage combined delivery model by adopting a particle swarm algorithm, the method comprises the following steps:
inputting parameters of wind, light, fire and user load and simulation basic parameters;
determining the space dimension of the population according to the types and models of the wind turbine generator and the photovoltaic generator to be optimized, and initializing the initial position value and the speed value of the particle population;
calculating wind power and photoelectric power according to power output models of the wind turbine generator and the photoelectric generator; judging the operation state of each unit in the wind-solar-fire storage and delivery system according to a scheduling strategy;
calculating the fitness of all particle populations on the basis of the previous step, recording the position and the fitness of the optimal individual, and updating the position and the speed of the next generation of particle swarm;
calculating the fitness of the new population and judging whether the maximum iteration times are met; if the maximum iteration times are not met, returning to re-optimizing; and if the maximum iteration times are met, outputting the optimal position and fitness optimal value of the optimal individual as the optimal capacity ratio of the wind, light and fire storage.
7. A wind, light, fire and storage combined delivery optimal configuration system is characterized by comprising:
the external transmission channel determining module is used for determining a wind-solar-energy-storage external transmission channel and an external transmission channel curve thereof based on the capacity of the external transmission channel to be planned, and determining an external transmission channel configuration energy storage charging and discharging principle and an external transmission method;
the wind-light-fire-storage optimal capacity ratio calculation module is used for configuring an energy storage charging and discharging principle and a delivery method based on the determined delivery power transmission channel, establishing a wind-light-fire-storage combined delivery model by taking the minimum running cost of the wind-light-fire-storage combined delivery system as a target, and solving the established wind-light-fire-storage combined delivery model by adopting a particle swarm algorithm to obtain the wind-light-fire-storage optimal capacity ratio.
8. The wind, light, fire and storage combined delivery optimization configuration system of claim 7, wherein the wind, light, fire and storage combined delivery model comprises an objective function and constraint conditions thereof which minimize the operation cost of the wind, light, fire and storage combined delivery system;
the objective function comprises the initial investment cost of wind, light and fire storage and the operation and maintenance cost of equipment, and the calculation formula is as follows:
F＝min(C 0 +C m )
C 0 ＝∑(N wt C wt +N pv C pv +N ther C ther +N bat C bat )f cr
C m ＝∑(k wt0 P wt Δt+k pv0 P pv Δt+k ther0 P ther Δt+k bat0 P bat Δt)
in the formula, F is the outward conveying operation cost; c 0 To initial investment cost, C m For operating maintenance costs, N wt 、N pv 、N ther 、N bat The installed capacities of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively represented by MW; c wt 、C pv 、C ther 、C bat The investment prices of wind power, photovoltaic, thermal power, energy storage and other equipment are respectively in units of ten thousand yuan/MW; f. of cr Is a depreciation factor; r is depreciation rate; lf is the life cycle; k is a radical of wt0 、k pv0 、k ther0 、k bat0 Respectively representing the operation and maintenance cost coefficients of wind power, photovoltaic, thermal power, energy storage and other equipment, wherein the unit is ten thousand yuan/MWh; p is wt 、P pv 、P ther 、P bat Respectively wind power, photovoltaic, thermal power and storageThe power capacity of the equipment can be equal, and the unit is MW; Δ t is the change time;
the constraint conditions comprise power balance constraint, wind turbine generator capacity constraint, photovoltaic power generation system capacity constraint, energy storage facility charge and discharge capacity and power constraint, thermal power unit output upper and lower limit constraint, renewable energy utilization constraint and renewable energy power rejection constraint.
9. A processing device comprising at least a processor and a memory, the memory having stored thereon a computer program, wherein the processor, when executing the computer program, performs the steps of implementing the method for combined wind, light, fire and storage delivery optimal configuration of any of claims 1 to 6.
10. A computer storage medium having computer readable instructions stored thereon which are executable by a processor to perform the steps of the wind, light, fire and storage combined delivery optimised configuration method according to any of claims 1 to 6.
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