Thermal storage capacity optimization configuration method, equipment and medium for photovoltaic and wind power consumption

Abstract

The present invention relates to a method, device and medium for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption, wherein the method comprises the following steps: determining the thermal storage system to assist in providing the photovoltaic and wind power, and constructing the thermal storage system constraints; taking the overall benefit maximization as the goal and the thermal storage system constraints, establishing a capacity optimization configuration model for the thermal storage and electricity storage system, solving the capacity optimization configuration model for the thermal storage and electricity storage system, and obtaining the optimal capacity configuration plan. Compared with the prior art, the present invention utilizes thermal power units for peak regulation to make the system more flexible and changeable, and in the case of multi-party cost optimization, controls the influencing factors, clarifies the objective function and simplifies the system cost, and uses energy storage equipment to peak the system, reducing the abandonment of light and wind while playing the role of efficient use of energy.

Description

Technical Field

[0001] The present invention belongs to the field of new energy storage, and relates to a method for optimizing the configuration of a heat storage and power storage system, and in particular to a method for optimizing the configuration of heat storage capacity for photovoltaic and wind power consumption. Background Art

[0002] In recent years, the photovoltaic and wind power industries have grown stronger and stronger, and the scale of photovoltaic and wind farms has also increased year by year. Since both solar energy and wind power are discontinuous, unstable and uncontrollable, large-scale grid connection of photovoltaic and wind power will bring a huge burden to the peak load regulation of the power grid, so the wind abandonment rate has always been high. The energy storage system helps the peak load regulation process of the system. The energy storage system can convert excess energy into thermal energy storage, which will become an important part of the safe operation of the power system. It can effectively improve the controllable power generation of photovoltaic and wind power generation, realize the peak load regulation of the power grid, and output electricity smoothly, reduce the impact of photovoltaic and wind power generation on the power grid, and effectively solve the problem of high wind power abandonment rate.

[0003] There are many technologies that use energy storage technology to absorb photovoltaic and wind power. For example, Dai Yuanhang et al. proposed the optimal scheduling of wind farms and combined heat and power with heat storage; Yu Jing et al. considered the strategy of wind power-heat power combined operation with heat storage devices; and patent application CN201910650474.3 disclosed a capacity optimization method for a solar-thermal-photovoltaic-wind power combined power generation system. However, the above existing solutions still have deficiencies such as insufficient flexibility and low energy utilization. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption, which has high flexibility and can effectively utilize energy while reducing the abandonment rate of photovoltaic and wind power.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption, the method comprising the following steps:

[0007] Determine the thermal storage system to assist in receiving photovoltaic and wind power, and establish thermal storage system constraints;

[0008] Taking the maximization of overall benefits as the goal and the constraints of the heat storage system, a capacity optimization configuration model of the heat storage and electricity storage system is established, and the capacity optimization configuration model of the heat storage and electricity storage system is solved to obtain the optimal capacity configuration plan;

[0009] The objective function of the capacity optimization configuration model of the thermal and electrical storage system is expressed as:

[0010] H(E)=max{G(E)+F(E)+T(E)+B(E)-R TESEC TES P TES -TAC system}

[0011] Where E is the optimal configuration capacity of heat storage; G(E), F(E), T(E), and B(E) are the benefits of solar thermal conversion, wind thermal conversion, alternative heating, and compensatory heating, respectively; R TES is the unit capacity price of the heat storage system; C TES is the unit power price of the heat storage system; T is the life of the heat storage system; AC system It is the annual operation and maintenance cost of the system.

[0012] Furthermore, the heat storage system assists in providing the photovoltaic and wind power electricity received, which is calculated based on the photovoltaic and wind power power, the minimum output of the thermal power unit and the heat storage optimal configuration power, specifically:

[0013]

[0014]

[0015] Where P d To improve the efficiency of photovoltaic and wind power; δ is the heat storage conversion efficiency; P fd P is the wind power that can be generated; gf is the photovoltaic power that can be generated; T is the number of time periods in which the heat storage system operates in one day; Δt is the duration of the heat storage operation in a single time period; P TES is the capacity of the heat storage system; P h,min It is the minimum output of thermal power unit.

[0016] Furthermore, the expression of the wind power that can be generated is:

[0017]

[0018]

[0019]

[0020]

[0021] In the formula, u, u in 、u out 、u e are actual wind speed, input wind speed, output wind speed and rated wind speed respectively; P fd , P e are the output power and rated power of wind power in actual conditions; K is the wind speed shape factor; α and β are the proposed power parameters; σ is the standard deviation of the wind speed sample; is the average wind speed in the sample.

[0022] Furthermore, the expression of the photovoltaic power generation is:

[0023] P gf =I tilt ×A×N×η gf

[0024] η gf =η gf.ref ×[1-δ×(T gf -T sta )]

[0025]

[0026] Where P gf is the actual output power of photovoltaic power; I tilt ,I ref are the irradiance on the inclined surface and the reference irradiance, respectively; A is the area of ​​the photovoltaic module; N is the number of photovoltaic modules; η gf , η gf.ref are the actual power generation efficiency and reference power generation efficiency of photovoltaic modules respectively; δ is the temperature correction coefficient; T gf , T sta , T en , T e , T ref They are the PV module operating temperature, test temperature under standard test conditions, temperature environment, rated operating temperature and reference temperature.

[0027] Furthermore, the minimum output of the thermal power unit is determined based on the output power of the generator set, and the expression of the output power of the generator set is:

[0028]

[0029] Where P h is the output power of the generator set; P t,force is the rated output power of the peak load unit; P c,force is the forced output power of the normal operation of the conventional units; i is the number of peak-shaving units; j is the number of guaranteed conventional units.

[0030] Furthermore, the thermal storage system constraints include wind power system safety constraints and photovoltaic system safety constraints, wherein the wind power system safety constraints are expressed as:

[0031]

[0032]

[0033] In the formula, p f (t) Wind power factor; is the maximum output of wind power at time t; P is the access capacity of wind power distributed power generation; f (t) is the active power of wind power grid-connected; ∑P fd is the total amount of wind power that can be generated; P fd,max is the maximum wind power acceptance;

[0034] The safety constraint condition of the photovoltaic system is expressed as:

[0035]

[0036]

[0037] In the formula, p g (t) is the photovoltaic power coefficient; is the maximum output of photovoltaic at time t; P is the access capacity of photovoltaic distributed power generation; g (t) is the active power of photovoltaic grid-connected; ∑P gf is the total photovoltaic power generation; P gf,max The maximum amount of photovoltaic power accepted.

[0038] Furthermore, the calculation formula of the light-to-heat conversion benefit is:

[0039] G(E)=E TG Rη1

[0040] In the formula, E TG The heat storage system increases the amount of heat converted by photovoltaics; R is the price of unit heat sent from the power grid; η1 is the efficiency of the electric boiler in converting light into heat;

[0041] The calculation formula of the wind-heat conversion benefit is:

[0042] F(E)=E TF Rη2

[0043] Where R is the price of unit heat delivered by the power grid; E TF The heat storage system increases the heat received by wind power conversion; η2 is the wind-to-electricity heat conversion efficiency of the electric boiler;

[0044] The calculation formula of the alternative heating benefit is:

[0045] T(E)=(E TF +E TG )(C f +R m β)

[0046] In the formula, C f The exhaust gas cost of the heating unit to generate unit heat; R m is the price of coal; β is the coal consumption rate of the heating unit;

[0047] The calculation formula of the compensation heating income is:

[0048] B(E)=(E TG +E TF )M B

[0049] Where M B The price at which the power grid compensates non-conventional peak-shaving units for peak-shaving electricity;

[0050] The calculation formula for the annual operation and maintenance cost of the system is:

[0051] AC system =AC fd +AC gf +AC h +AC TES

[0052] In the formula, AC system is the annual operation and maintenance cost of the system; AC fd is the annual operation and maintenance cost of the wind power generation unit; AC gf is the annual operation and maintenance cost of the thermal power generation unit; AC h is the annual operation and maintenance cost of the thermal power peak load-shaving unit; AC TES Annual operation and maintenance costs of energy storage equipment.

[0053] Furthermore, according to the typical daily consumption of abandoned solar and wind power and heat storage gradient scheduling, a scheduling strategy with a gradient of 50MW is adopted to solve the capacity optimization configuration model of the heat and electricity storage system and obtain the optimal capacity configuration plan.

[0054] The present invention also provides an electronic device, comprising:

[0055] one or more processors;

[0056] Memory; and

[0057] One or more programs stored in a memory, wherein the one or more programs include instructions for executing the method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption as described above.

[0058] The present invention also provides a computer-readable storage medium, characterized in that it includes one or more programs for execution by one or more processors of an electronic device, and the one or more programs include instructions for executing the method for optimizing configuration of thermal storage capacity for photovoltaic and wind power consumption as described above.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention utilizes thermal power units for peak load regulation, making the system more flexible and changeable, and controlling influencing factors, clarifying the objective function and simplifying the system cost under the condition of multi-party cost optimization.

[0061] 2. The present invention constrains the heat storage system according to the constraints of the actual project, adopts 50MW for cascade scheduling, determines the scheduling level according to the heat storage capacity, and the optimization configuration result is accurate and reliable.

[0062] 3. The present invention uses energy storage equipment to peak-shift the system, thereby reducing the rate of abandoned solar and wind power and achieving efficient energy utilization.

[0063] 4. The present invention aims to optimize the consumption of distributed photovoltaic and wind power. While clarifying the power consumption of users, it also determines the capacity of the heat and electricity storage system, and finally calculates the final profit. According to the peak regulation, the energy storage system plays a role in shaving the peak and filling the valley for the operation of the power system.

[0064] 5. The present invention calculates the optimal capacity ratio of photovoltaic, wind power, thermal power and heat storage systems in different situations, thereby improving the reliability and economy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0066] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0067] The present invention aims at optimizing the configuration method of heat storage capacity for photovoltaic and wind power consumption, using the output of thermal power units to achieve peak load regulation, and adopting cascade scheduling of heat storage equipment according to the actual engineering constraints of the heat storage system and the level of heat storage capacity. It proposes to use the benefits of photovoltaic conversion, wind power conversion, and alternative heating benefits and compensatory heating benefits to establish a mathematical model for the optimal capacity configuration of the heat storage system. The method is applied to a system including a wind power unit, a solar photovoltaic power generation unit, a thermal power peak load regulation configuration, and heat storage and power storage equipment. Specifically, refer to Figure 1 As shown, the method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption of the present invention comprises the following steps:

[0068] Determine that the heat storage system assists in providing and accommodating photovoltaic and wind power, and construct heat storage system constraints, which include wind power system safety constraints, photovoltaic system safety constraints, and power constraints; take the maximization of overall benefits as the goal and the heat storage system constraints, establish a capacity optimization configuration model for the heat storage and electricity storage system, and according to the typical daily absorption of abandoned photovoltaic and wind power storage gradient scheduling, adopt a scheduling strategy with a gradient of 50MW, solve the capacity optimization configuration model for the heat storage and electricity storage system, and obtain the optimal capacity configuration plan.

[0069] 1. Thermal storage system constraints

[0070] The thermal storage system assists in providing the following photovoltaic and wind power:

[0071] Calculate photovoltaic power generation and wind power generation and their safety constraints, load power, and minimum output of thermal power units to determine constraints;

[0072] According to the given load forecast curve, the output power of thermal power generating units is determined with the combination of generating units, rated output of peak-shaving units, number of peak-shaving units, normal forced output of conventional units, and number of conventional units clearly defined;

[0073] The heat storage system is used to assist in accommodating the amount of photovoltaic and wind power, based on the power that can be generated by photovoltaic and wind power, the minimum output of thermal power units and the optimal configuration power of heat storage.

[0074] (1) Wind power generation capacity and its safety constraints

[0075] The expression of wind power generation capacity is:

[0076]

[0077]

[0078]

[0079]

[0080] In the formula, u, u in 、u out 、u e are actual wind speed, input wind speed, output wind speed and rated wind speed respectively; P fd , P e are the output power and rated power of wind power in actual conditions; K is the wind speed shape factor; α and β are the proposed power parameters; σ is the standard deviation of the wind speed sample; is the average wind speed in the sample.

[0081] Due to the instability of new energy output and the imperfect compensation mechanism for promoting new energy consumption, the safety constraints on wind power systems are introduced:

[0082]

[0083]

[0084] In the formula, p f (t) Wind power coefficient, which is a piecewise function of wind speed v; is the maximum output of wind power at time t; P is the access capacity of wind power distributed power generation; f (t) is the active power of wind power grid-connected, which does not exceed the maximum range of wind power output; ∑P fd is the total amount of wind power that can be generated; P fd,max is the maximum wind power acceptance;

[0085] (2) Photovoltaic power generation and its safety constraints

[0086] The expression of photovoltaic power generation is:

[0087] P gf =I tilt ×A×N×η gf

[0088] η gf =η gf.ref ×[1-δ×(T gf -T sta )]

[0089]

[0090] Where P gf is the actual output power of photovoltaic power, W; I tilt ,I ref They are respectively the irradiance on the inclined surface and the reference irradiance, W / m 2 ; A is the area of ​​PV panels, m 2 ; N is the number of photovoltaic modules; η gf , η gf.ref are the actual power generation efficiency and reference power generation efficiency of photovoltaic modules respectively; δ is the temperature correction coefficient; T gf , T sta , T en , T e , T ref They are PV module operating temperature, test temperature under standard test conditions, temperature environment, rated operating temperature, and reference temperature, ℃.

[0091] Due to the instability of new energy output and the imperfect compensation mechanism for promoting new energy consumption, the safety constraints on photovoltaic systems are introduced:

[0092]

[0093]

[0094] In the formula, p g (t) is the photovoltaic power coefficient, which is a function of light intensity and temperature; is the maximum output of photovoltaic at time t; P is the access capacity of photovoltaic distributed power generation; g (t) is the active power of the photovoltaic grid, which does not exceed the maximum range of photovoltaic output; ∑P gf is the total photovoltaic power generation; P gf,max The maximum amount of photovoltaic power accepted.

[0095] (3) Minimum output of thermal power units

[0096] According to the given load forecast curve, the output power of the generator set is determined by clarifying the generator set combination, the number of peak-shaving units, the rated output of the peak-shaving units, the number of conventional units, and the normal forced output of conventional units:

[0097]

[0098] Where P h is the output power of the generator set; P t,force is the rated output power of the peak load unit; P c,force is the forced output power of the normal operation of the conventional units; i is the number of peak-shaving units; j is the number of guaranteed conventional units.

[0099] Calculate based on the basic electricity load of the corresponding user to determine the minimum output of the thermal power unit, specifically:

[0100] P fh -P fd -P gf <P h,min

[0101] Where P fh is the load power; P h,min is the minimum thermal power output; P fd Actual wind power output power; P gf is the actual photovoltaic output power.

[0102] (4) The thermal storage system assists in providing photovoltaic and wind power

[0103] The thermal storage system assists in providing the photovoltaic and wind power electricity, which is calculated based on the photovoltaic and wind power power, the minimum output of the thermal power unit and the thermal storage optimal configuration power. Specifically:

[0104]

[0105]

[0106] Where P d To improve the efficiency of photovoltaic and wind power; δ is the heat storage conversion efficiency; P fd P is the wind power that can be generated; gf is the photovoltaic power that can be generated; T is the number of time periods in which the heat storage system operates in one day; Δt is the duration of the heat storage operation in a single time period; P TES is the capacity of the heat storage system; P h,min It is the minimum output of thermal power unit.

[0107] 2. Objective Function

[0108] The objective function of the capacity optimization configuration model of the thermal and electrical storage system is expressed as:

[0109] H(E)=max{G(E)+F(E)+T(E)+B(E)-R TES EC TES P TES -TAC system}

[0110] Where E is the optimal configuration capacity of heat storage; G(E), F(E), T(E), and B(E) are the benefits of solar thermal conversion, wind thermal conversion, alternative heating, and compensatory heating, respectively; R TES is the unit capacity price of the heat storage system; C TES is the unit power price of the heat storage system; T is the life of the heat storage system; AC system It is the annual operation and maintenance cost of the system.

[0111] The calculation formula for the light-to-heat conversion benefit is:

[0112] G(E)=E TG Rη1

[0113] In the formula, E TG The heat storage system increases the amount of heat converted by photovoltaic power generation (MW*h); R is the price of unit heat transmitted by the power grid (yuan / (MW*h)); η1 is the photothermal conversion efficiency of the electric boiler.

[0114] The calculation formula for wind-heat conversion benefits is:

[0115] F(E)=E TF Rη2

[0116] Where R is the price of unit heat delivered by the power grid (yuan / (MW*h)); E TF It is used to increase the heat (MW*h) of wind power conversion accepted by the heat storage system; η2 is the wind-to-electricity heat conversion efficiency of the electric boiler.

[0117] The calculation formula for heat replacement benefits is:

[0118] T(E)=(E TF +E TG )(C f +R m β)

[0119] In the formula, C f The exhaust gas cost per unit heat generated by the heating unit (yuan / (MW*h)); R m is the price of coal (yuan / t); β is the coal consumption rate of the heating unit (kg / (kW*h)).

[0120] The calculation formula for compensatory heating benefits is:

[0121] B(E)=(E TG +E TF )M B

[0122] Where M B It is the compensation price (yuan / (MW*h)) for the peak-shaving electricity of unconventional peak-shaving units by the power grid.

[0123] The calculation formula for the system's annual operation and maintenance cost is:

[0124] AC system =AC fd +AC gf +AC h +AC TES

[0125] In the formula, AC system is the annual operation and maintenance cost of the system (yuan); AC fd is the annual operation and maintenance cost of the wind power generation unit (yuan); AC gf is the annual operation and maintenance cost of the thermal power generation unit (yuan); AC h is the annual operation and maintenance cost of the thermal power peak load regulating unit (yuan); AC TES is the annual operation and maintenance cost of the energy storage equipment (yuan).

[0126] 3. Model solution

[0127] According to the typical daily consumption of abandoned solar and wind power storage gradient scheduling, 50MW is determined as the thermal storage unit scheduling level. The part of photovoltaic and wind power margin greater than 0 needs to be dispatched to the thermal storage system for consumption, and the thermal storage capacity gradient at different times is obtained. According to the obtained capacity at different times, it is divided into multiple thermal storage capacity gradients, and the system's solar thermal conversion benefits, wind thermal conversion benefits, alternative heating benefits, compensatory heating benefits, thermal storage costs and operation and maintenance costs at different capacity gradient times are calculated. The thermal storage capacity gradient when the benefits are maximum is the optimal capacity configuration.

[0128] If the above method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0129] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption, characterized in that: The method comprises the following steps: Determine the thermal storage system to assist in receiving photovoltaic and wind power, and establish thermal storage system constraints; Taking the maximization of overall benefits as the goal and the constraints of the heat storage system, a capacity optimization configuration model of the heat storage and electricity storage system is established, and the capacity optimization configuration model of the heat storage and electricity storage system is solved to obtain the optimal capacity configuration plan; The objective function of the capacity optimization configuration model of the thermal and electrical storage system is expressed as: H(E)=max{G(E)+F(E)+T(E)+B(E)-R TES E-C TES P TES -TAC system } Where E is the optimal configuration capacity of heat storage; G(E), F(E), T(E), and B(E) are the benefits of solar thermal conversion, wind thermal conversion, alternative heating, and compensatory heating, respectively; R TES is the unit capacity price of the heat storage system; C TES is the unit power price of the heat storage system; T is the life of the heat storage system; AC system The annual operation and maintenance cost of the system; The heat storage system assists in providing the photovoltaic and wind power electricity received, which is calculated based on the photovoltaic and wind power power, the minimum output of the thermal power unit and the heat storage optimal configuration power. Specifically: Where P d To improve the efficiency of photovoltaic and wind power; δ is the heat storage conversion efficiency; P fd P is the wind power that can be generated; gf is the photovoltaic power that can be generated; T is the number of time periods in which the heat storage system operates in one day; Δt is the duration of the heat storage operation in a single time period; P TES is the capacity of the heat storage system; P h,min It is the minimum output of thermal power unit; According to the daily consumption of abandoned solar and wind power storage gradient scheduling, 50MW is determined as the thermal storage unit scheduling level. The part of photovoltaic and wind power margin greater than 0 needs to be dispatched to the thermal storage system for consumption, and the thermal storage capacity gradient at different times is obtained. According to the obtained capacity at different times, it is divided into multiple thermal storage capacity gradients. The system calculates the solar thermal conversion income, wind thermal conversion income, alternative heating income, compensatory heating income, thermal storage cost and operation and maintenance cost at different capacity gradient times. The thermal storage capacity gradient when the income is maximum is the optimal capacity configuration; Calculate based on the basic electricity load of the corresponding user to determine the minimum output of the thermal power unit, specifically: P fh -P fd -P gf <P h,min Where P fh is the load power; P h,min is the minimum thermal power output; P fd Actual wind power output power; P gf is the actual photovoltaic output power.

2. The method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption according to claim 1, characterized in that: The expression of wind power generation capacity is: In the formula, u, u in 、u out 、u e are actual wind speed, input wind speed, output wind speed and rated wind speed respectively; P fd , P e are the output power and rated power of wind power in actual conditions; K is the wind speed shape factor; α and β are the proposed power parameters; σ is the standard deviation of the wind speed sample; is the average wind speed in the sample.

3. The method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption according to claim 1, characterized in that: The expression of the photovoltaic power generation is: P gf =I tilt ×A×N×η gf or gf =the gf.ref ×[1-δ×(T gf -T sta )] Where P gf is the actual output power of photovoltaic power; I tilt ,I ref are the irradiance on the inclined surface and the reference irradiance, respectively; A is the area of ​​the photovoltaic module; N is the number of photovoltaic modules; η gf , η gf.ref are the actual power generation efficiency and reference power generation efficiency of photovoltaic modules respectively; δ is the temperature correction coefficient; T gf , T sta , T en , T e , T ref They are the PV module operating temperature, test temperature under standard test conditions, temperature environment, rated operating temperature and reference temperature.

4. The method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption according to claim 1, characterized in that: The thermal storage system constraints include wind power system safety constraints and photovoltaic system safety constraints, wherein the wind power system safety constraints are expressed as: In the formula, p f (t) Wind power factor; is the maximum output of wind power at time t; P is the access capacity of wind power distributed power generation; f (t) is the active power of wind power grid-connected; ∑Pfd is the total amount of wind power that can be generated; P fd,max is the maximum wind power acceptance; The safety constraint condition of the photovoltaic system is expressed as: In the formula, p g (t) is the photovoltaic power coefficient; is the maximum output of photovoltaic at time t; P is the access capacity of photovoltaic distributed power generation; g (t) is the active power of photovoltaic grid-connected; ∑P gf is the total photovoltaic capacity; Pgf,max is the maximum photovoltaic capacity accepted.

5. The method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption according to claim 1, characterized in that: The calculation formula of the light-to-heat conversion benefit is: G(E)=E TG Rη1 In the formula, E TG The heat storage system increases the amount of heat converted by photovoltaics; R is the price of unit heat sent from the power grid; η1 is the efficiency of the electric boiler in converting light into heat; The calculation formula of the wind-heat conversion benefit is: F(E)=E TF Rη2 Where R is the price of unit heat delivered by the power grid; E TF The heat storage system increases the heat received by wind power conversion; η2 is the wind-to-electricity heat conversion efficiency of the electric boiler; The calculation formula of the alternative heating benefit is: T(E)(E TF +E TG )(C f +R m β) In the formula, C f The exhaust gas cost of the heating unit to generate unit heat; R m is the price of coal; β is the coal consumption rate of the heating unit; The calculation formula of the compensation heating income is: B(E)=(E TG +E TF )M B Where M B The price at which the power grid compensates non-conventional peak-shaving units for peak-shaving electricity; The calculation formula for the annual operation and maintenance cost of the system is: AC system =AC fd + AC gf + AC h + AC TES In the formula, AC system is the annual operation and maintenance cost of the system; AC fd is the annual operation and maintenance cost of the wind power generation unit; AC gf is the annual operation and maintenance cost of the thermal power generation unit; AC h is the annual operation and maintenance cost of the thermal power peak load-shaving unit; AC TES Annual operation and maintenance costs of energy storage equipment.

6. An electronic device, characterized in that: include: one or more processors; Memory; and One or more programs stored in a memory, wherein the one or more programs include instructions for executing the method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that: It includes one or more programs for execution by one or more processors of an electronic device, and the one or more programs include instructions for executing the method for optimizing the configuration of thermal storage capacity for photovoltaic and wind power consumption as described in any one of claims 1-5.

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