A capacity planning method, system, and readable storage medium for a biomass-photovoltaic-energy storage combined power generation system.

Abstract

This invention relates to the field of integrated energy planning, and more particularly to a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system, comprising: S1: establishing a biomass power plant model; S2: establishing a capacity planning model containing a biomass power plant, a photovoltaic power plant, and energy storage based on the biomass power plant model; the capacity planning model takes minimizing the total cost of the combined power generation system as its objective function; S3: defining performance evaluation indicators; S4: solving the capacity planning model in step S2 to obtain the optimal capacity planning result that meets the performance evaluation indicators; the optimal capacity planning result is the capacity of the biomass power plant, the photovoltaic power plant, and the energy storage capacity. Using this invention can mitigate the impact of seasonal fluctuations on the output fluctuations of biomass power and photovoltaic power, improve the utilization rate of renewable energy, and enhance the system's ability to absorb distributed power sources and accommodate intermittent loads.

Description

Technical Field

[0001] This invention relates to the field of integrated energy planning, and in particular to a capacity planning method, system, and readable storage medium for a biomass-photovoltaic-energy storage combined power generation system. Background Technology

[0002] Biomass power generation utilizes the biomass energy inherent in biomass and is a type of renewable energy generation. It includes direct combustion of agricultural and forestry waste, gasification of agricultural and forestry waste, waste incineration, landfill gas generation, and biogas generation. China is a major agricultural country with abundant biomass resources. Various crops produce a huge amount of straw annually, and the potential for effective utilization through straw power generation is enormous. Photovoltaic power generation is also one of the most widely used renewable energy generation technologies. However, both biomass and photovoltaic power generation are significantly affected by seasonality, which can impact the stability of the power grid system during grid connection and even affect its safe and stable operation. To ensure grid safety, this can also affect the system's ability to absorb distributed power sources and accommodate intermittent loads. Summary of the Invention

[0003] In view of this, the present invention provides a capacity planning method, system and readable storage medium for a biomass-photovoltaic-energy storage combined power generation system. The main purpose is to mitigate the impact of seasonal fluctuations on the output fluctuations of biomass energy and photovoltaic power, improve the utilization rate of renewable energy, and enhance the system's ability to absorb distributed power sources and accept intermittent loads.

[0004] To achieve the above objectives, the present invention mainly provides the following technical solutions:

[0005] On one hand, embodiments of the present invention provide a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system, comprising:

[0006] S1: Establish a biomass power plant model;

[0007] S2: Based on the biomass power plant model, establish a capacity planning model that includes a biomass power plant, a photovoltaic power plant, and energy storage; the capacity planning model takes the minimum total cost of the combined power generation system as its objective function;

[0008] S3: Define the performance evaluation indicators;

[0009] S4: Solve the capacity planning model described in step S2 to obtain the optimal capacity planning result that meets the effect evaluation index; the optimal capacity planning result is the capacity of biomass energy, photovoltaic power station and energy storage.

[0010] Furthermore, the collection cost of biological raw materials in the biomass power plant model described in step S1 mainly includes the acquisition cost of biological raw materials, transportation costs, and other expenses:

[0011]

[0012] In the formula, S fuel For collection costs; X fuel For annual fuel purchase cost; Y fuel Annual transportation costs for fuel; Z fuel Other expenses;

[0013] The annual fuel purchase cost is determined by the annual fuel consumption and the fuel purchase price:

[0014] X fuel =B fuel ·p fuel

[0015] In the formula, B fuel Annual fuel consumption; p fuel The fuel purchase price;

[0016] Annual fuel consumption depends on the power plant's generating capacity and the unit's annual operating time:

[0017] B fuel =b fuel ·P·t

[0018] In the formula, b fuel Fuel consumption rate; P is unit power; t is annual operating time of the unit;

[0019] The formula for calculating the amount of biological raw materials required per unit of electrical energy is:

[0020]

[0021] In the formula, LHV fuel The lower heating value of the fuel; η e For power generation efficiency;

[0022] Fuel transportation costs are related to factors such as the amount of biomass collected, the distribution density of biomass, the biomass collection coefficient, the biomass availability coefficient, and the unit transportation cost.

[0023] Fuel transportation costs are:

[0024]

[0025] In the formula, k is a comprehensive coefficient determined by the biological raw material collection coefficient and the availability coefficient; ρ is the distribution density of biological raw materials; c is the unit transportation cost; and R is the collection radius.

[0026] The collection radius is determined by the annual fuel consumption:

[0027]

[0028] Other fees are as follows:

[0029]

[0030] In the formula, α represents the percentage of other expenses in the total collection cost; S fuel For collection costs.

[0031] Furthermore, the objective function is:

[0032] minC total =min(C ST +C OP ·C BE +S fuel -S ESS )

[0033] In the formula: C total C represents the total system cost. ST C represents the initial cost of the system. OP For operation and maintenance costs; C BE The cost of purchasing electricity from the grid; S ESS For energy storage revenue; S EP For environmental benefits;

[0034] The initial cost of the system is converted to daily initial cost, which is:

[0035]

[0036]

[0037] In the formula: f DR W is the depreciation factor. bi For the capacity of biomass power plants; The price per unit capacity of a biomass power plant; W pv For the capacity of photovoltaic power plants; The price per unit capacity of a photovoltaic power plant; W ess For energy storage capacity; d represents the price per unit capacity of energy storage; d represents the depreciation rate; and y represents the useful life.

[0038] The system's operation and maintenance costs are:

[0039]

[0040] In the formula: Δt bi Δt represents the daily operating time of a biomass power plant. pvΔt represents the daily operating time of a photovoltaic power station. ess The operating time of the energy storage within one day; This refers to the operation and maintenance cost of a biomass power plant per unit of time. This refers to the operation and maintenance cost of a photovoltaic power station per unit of time. These represent the operation and maintenance costs of energy storage per unit time.

[0041] The system's cost of purchasing electricity from the grid is:

[0042] C BE =P(t)·Q BE

[0043] In the formula: P(t) is the grid electricity price at time t; Q BE Let t be the amount of electricity the system purchases from the grid at time t;

[0044] Energy storage benefits:

[0045]

[0046]

[0047] In the formula: S ess Total revenue from energy storage; S bt For the revenue from newly connected renewable energy sources; The additional biomass power generation during season i, period t. p represents the newly generated photovoltaic power during period t in season i; bi For the grid connection price of energy for physical energy, p pv For photovoltaic feed-in tariffs;

[0048] The environmental benefits are:

[0049]

[0050] In the formula: w bi Daily power generation from biomass energy; w pv denoted as , where is the daily power generation from photovoltaic power; and N is the number of types of pollutants. The environmental value cost of Class k pollutants from thermal power generation; The environmental value cost of Class k pollutants from biomass power generation; This represents the environmental value cost of the kth type of pollutants generated by photovoltaic power generation.

[0051] Furthermore, the performance evaluation index includes: the complementary characteristics of biomass energy and photovoltaics, D; the smaller D is, the more the power generation of the system can meet the load demand, indicating that the complementarity between the two is better, the energy storage capacity required is smaller, and the cost is lower.

[0052] Furthermore, the complementary nature of biomass energy and photovoltaics is the fluctuation of the sum of the output power of biomass power generation and photovoltaic power generation relative to the load power, and its expression is:

[0053]

[0054] In the formula: D represents the complementary characteristics of biomass energy and photovoltaics; P represents the average power of the load. bi (t) represents the power generated by biomass energy at time t; P pv (t) represents the power generated by the photovoltaic system at time t; P L (t) represents the load power at time t;

[0055] Constraints:

[0056] D≤D r

[0057] D r The maximum rated biomass energy and photovoltaic complementary characteristics.

[0058] Furthermore, the performance evaluation index includes: power supply loss rate f; the power supply loss rate f reflects the reliability of the power supply from the biomass energy, photovoltaic and energy storage combined power generation system. The smaller the power supply loss rate f, the more reliable the system power supply; its expression is:

[0059]

[0060] In the formula: f is the power supply loss rate; P ess (t) represents the energy storage power at time t;

[0061] Constraints:

[0062] f≤f r

[0063] f r This represents the maximum power supply loss rate.

[0064] Furthermore, the performance evaluation index includes: the comprehensive utilization rate R of biomass energy and photovoltaic power generation; the higher the comprehensive utilization rate R of biomass energy and photovoltaic power generation, the smaller the fluctuation of renewable energy output of the combined power generation system; its expression is:

[0065]

[0066] In the formula: R is the combined utilization rate of biomass energy and photovoltaic power generation; Provide biomass energy output for season i during period t. Photovoltaic output for seasonal period i during time t; This represents the upper limit of biomass energy output during period t in season i. The upper limit of photovoltaic output during period t in season i;

[0067] Constraints:

[0068] R≥R r

[0069] In the formula, R r Minimum utilization rate of combined biomass and photovoltaic power generation.

[0070] Furthermore, the constraints of the objective function of the capacity planning model, which includes biomass power plants, photovoltaic power plants, and energy storage, include:

[0071] The capacity of a combined biomass, photovoltaic, and energy storage power generation system has a lower limit of 0 and an upper limit of 10 times the maximum daily load, expressed as:

[0072]

[0073] In the formula, This represents the maximum load of the day;

[0074] Power output during biomass energy operation Contributing to the operation of photovoltaic power satisfy:

[0075]

[0076] In the formula: The lower limit of biomass energy output during period t in season i; This represents the lower limit of photovoltaic power output during period t in season i. This represents the upper limit of biomass energy output during period t in season i. The upper limit of photovoltaic output during period t in season i;

[0077] The energy storage state of charge should meet the following requirements:

[0078]

[0079] In the formula: E represents the state of charge of energy storage during time period t in season i; soc-max This represents the upper limit of the energy storage state of charge; E soc-min This is the limit of the energy storage state of charge; The state of charge at the start of seasonal scheduling cycle i; The state of charge at the end of seasonal scheduling period i; ζ c For energy storage charging efficiency; ζ d The discharge efficiency of energy storage.

[0080] On the other hand, embodiments of the present invention provide a planning system including a processor and a memory, the memory storing a computer program, the processor calling the computer program to execute the steps of the method.

[0081] In another aspect, embodiments of the present invention provide a readable storage medium storing a computer program that is invoked by a processor to execute the steps of the method.

[0082] By means of the above technical solutions, the present invention provides a capacity planning method, system, and readable storage medium for a biomass-photovoltaic-energy storage combined power generation system.

[0083] It has at least the following advantages:

[0084] It can mitigate the impact of seasonal fluctuations on the output of biomass energy and photovoltaic power, improve the utilization rate of renewable energy, and enhance the system's ability to absorb distributed power sources and accept intermittent loads.

[0085] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0086] Figure 1 This is a schematic diagram of a biomass-photovoltaic-energy storage combined power generation system provided in an embodiment of the present invention. Detailed Implementation

[0087] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the specific embodiments, structures, features, and effects according to the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments. In the following description, different "embodiments" or "embodiments" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0088] refer to Figure 1 One embodiment of the present invention proposes a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system, comprising: S1: establishing a biomass power plant model; S2: establishing a capacity planning model containing a biomass power plant, a photovoltaic power plant, and energy storage based on the biomass power plant model; the capacity planning model takes the minimum total cost of the combined power generation system as its objective function; S3: defining performance evaluation indicators; S4: solving the capacity planning model in step S2 to obtain the optimal capacity planning result that meets the performance evaluation indicators; the optimal capacity planning result is the capacity of biomass energy, photovoltaic power plant, and energy storage. Preferably, the raw material for biomass energy is crop straw.

[0089] An embodiment of the present invention proposes a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system, which can mitigate the impact of seasonal fluctuations on the output fluctuations of biomass energy and photovoltaic power, improve the utilization rate of renewable energy, enhance the system's ability to absorb distributed power sources and accommodate intermittent loads, and reduce the upgrading and transformation costs of integrated energy planning.

[0090] An embodiment of the present invention proposes a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system. This method utilizes the complementarity of biomass energy and solar energy in terms of temporal and geographical distribution. In the combined power generation system, energy storage is used to store the electricity generated by the power generation system, and when there is load demand, it is supplied through transmission lines.

[0091] One embodiment of the present invention proposes a capacity planning method for a biomass-photovoltaic-energy storage combined power generation system. In this grid-connected version of the biomass-photovoltaic-energy storage combined power generation system, the power grid serves as a backup power source for the combined power generation system. When there is surplus electricity in the combined power generation system, it is fed into the grid; when the power supply is insufficient due to factors such as seasonal fluctuations, it is purchased from the grid.

[0092] As a preferred embodiment of the above, the collection cost of biological raw materials in the biomass power plant model in step S1 mainly includes the acquisition cost of biological raw materials, transportation costs, and other expenses:

[0093]

[0094] In the formula, S fuel For collection costs; X fuel For annual fuel purchase cost; Y fuel Annual transportation costs for fuel; Z fuel Other expenses.

[0095] The annual fuel purchase cost is determined by the annual fuel consumption and the fuel purchase price:

[0096] X fuel =B fuel ·p fuel

[0097] In the formula, B fuel Annual fuel consumption; p fuel This refers to the fuel purchase price.

[0098] Annual fuel consumption depends on the power plant's generating capacity and the unit's annual operating time:

[0099] B fuel =b fuel ·P·t

[0100] In the formula, b fuelt represents the fuel consumption rate; P represents the unit power; and t represents the annual operating time of the unit.

[0101] The formula for calculating the amount of biological raw materials required per unit of electrical energy is:

[0102]

[0103] In the formula, LHV fuel The lower heating value of the fuel; η e For power generation efficiency.

[0104] Fuel transportation costs are related to factors such as the amount of biomass collected, the distribution density of biomass, the biomass collection coefficient, the biomass availability coefficient, and the unit transportation cost.

[0105] Fuel transportation costs are:

[0106]

[0107] In the formula, k is a comprehensive coefficient determined by the biological raw material collection coefficient and the availability coefficient; ρ is the distribution density of biological raw materials; c is the unit transportation cost; and R is the collection radius.

[0108] The collection radius is determined by the annual fuel consumption:

[0109]

[0110] Other fees are as follows:

[0111]

[0112] In the formula, α represents the percentage of other expenses in the total collection cost; S fuel For collection costs.

[0113] As a preferred embodiment of the above, the objective function is:

[0114] minC total =min(C ST +C OP +C BE +S fuel -S ESS )

[0115] In the formula: C total C represents the total system cost. ST C represents the initial cost of the system. OP For operation and maintenance costs; C BE The cost of purchasing electricity from the grid; S ESS For energy storage revenue; S EP For environmental benefits.

[0116] The initial cost of the system is converted to daily initial cost, which is:

[0117]

[0118]

[0119] In the formula: f DR W is the depreciation factor. bi For the capacity of biomass power plants; The price per unit capacity of a biomass power plant; W pv For the capacity of photovoltaic power plants; The price per unit capacity of a photovoltaic power plant; W ess For energy storage capacity; d represents the price per unit capacity of energy storage; d represents the depreciation rate; and y represents the service life.

[0120] The system's operation and maintenance costs are:

[0121]

[0122] In the formula: Δt bi Δt represents the daily operating time of a biomass power plant. pv Δt represents the daily operating time of a photovoltaic power station. ess The operating time of the energy storage within one day; This refers to the operation and maintenance cost of a biomass power plant per unit of time. This refers to the operation and maintenance cost of a photovoltaic power station per unit of time. These represent the operation and maintenance costs of energy storage per unit of time.

[0123] The system's cost of purchasing electricity from the grid is:

[0124] C BE =P(t)·Q BE

[0125] In the formula: P(t) is the grid electricity price at time t; Q BE Let t be the amount of electricity the system purchases from the grid at time t.

[0126] Energy storage benefits:

[0127]

[0128]

[0129] In the formula: S ess Total revenue from energy storage; S bt For the revenue from newly connected renewable energy sources; The additional biomass power generation during season i, period t. p represents the newly generated photovoltaic power during period t in season i; bi For the grid connection price of energy for physical energy, p pv The feed-in tariff for photovoltaic power is used. When the grid's capacity to absorb renewable energy is insufficient, energy storage can store electricity and release it when the renewable energy absorption capacity is insufficient, thereby alleviating the problem of curtailment of solar power. Therefore, the increased revenue from biomass energy and photovoltaic grid connection after installing energy storage can be regarded as energy storage revenue.

[0130] The environmental benefits are:

[0131]

[0132] In the formula: w bi Daily power generation from biomass energy; w pv denoted as , where is the daily power generation from photovoltaic power; and N is the number of types of pollutants. The environmental value cost of Class k pollutants from thermal power generation; The environmental value cost of Class k pollutants from biomass power generation; Let represent the environmental value cost of the kth type of pollutant from photovoltaic power generation. Generally, pollutants from traditional thermal power generation systems mainly include SO2, NOx, CO2, and dust, while biomass energy and photovoltaic power generation can effectively reduce the emission of these pollutants, thus protecting the environment to a certain extent. Assume that biomass energy generates electricity under ideal conditions; specific parameters are shown in the table below.

[0133]

[0134] As a preferred embodiment of the above, the performance evaluation index includes: the complementary characteristics of biomass energy and photovoltaics, D; the smaller D is, the more the power generation of the system can meet the load demand, indicating that the complementarity between the two is better, the energy storage capacity required is smaller, and the cost is lower.

[0135] As a preferred embodiment of the above, the complementary characteristic of biomass energy and photovoltaic power is the fluctuation of the sum of the output power of biomass power generation and photovoltaic power generation relative to the load power, and its expression is:

[0136]

[0137] In the formula: D represents the complementary characteristics of biomass energy and photovoltaics; P represents the average power of the load. bi (t) represents the power generated by biomass energy at time t; P pv (t) represents the power generated by the photovoltaic system at time t; P L (t) represents the load power at time t.

[0138] Constraints:

[0139] D≤D r

[0140] D r The maximum rated biomass energy and photovoltaic complementary characteristics.

[0141] As a preferred embodiment of the above, the performance evaluation index includes: power supply loss rate f; the power supply loss rate f reflects the reliability of the power supply from the biomass energy, photovoltaic and energy storage combined power generation system. The smaller the power supply loss rate f, the more reliable the system power supply; its expression is:

[0142]

[0143] In the formula: f is the power supply loss rate; P ess (t) represents the energy storage power at time t.

[0144] Constraints:

[0145] f≤f r

[0146] f r This represents the maximum power supply loss rate.

[0147] As a preferred embodiment of the above, the performance evaluation index includes: the comprehensive utilization rate R of biomass energy and photovoltaic power generation; the larger the comprehensive utilization rate R of biomass energy and photovoltaic power generation, the smaller the fluctuation of renewable energy output of the combined power generation system; its expression is:

[0148]

[0149] In the formula: R is the combined utilization rate of biomass energy and photovoltaic power generation; Provide biomass energy output for season i during period t. Photovoltaic output for seasonal period i during time t; This represents the upper limit of biomass energy output during period t in season i. This represents the upper limit of photovoltaic output during the i-th time period t of the season.

[0150] Constraints:

[0151] R≥R r

[0152] In the formula, R r Minimum utilization rate of combined biomass and photovoltaic power generation.

[0153] As a preferred embodiment of the above, the constraints of the objective function of the capacity planning model containing biomass power plants, photovoltaic power plants, and energy storage include: the lower limit of the capacity of the combined biomass, photovoltaic, and energy storage power generation system is 0, and the upper limit is 10 times the maximum load in a day, expressed as:

[0154]

[0155] In the formula, This represents the maximum load of the day;

[0156] Due to the influence of the natural environment, biomass energy and photovoltaic power have upper and lower limits in actual operation. The power output of biomass energy during operation... Contributing to the operation of photovoltaic power satisfy:

[0157]

[0158] In the formula: The lower limit of biomass energy output during period t in season i; This represents the lower limit of photovoltaic power output during period t in season i. This represents the upper limit of biomass energy output during period t in season i. This represents the upper limit of photovoltaic output during the i-th time period t of the season.

[0159] The state of charge (SBC) is usually used to represent the operating status of an energy storage system. To ensure the stable operation of the energy storage system, the SBC is limited to a certain range, and the SBC at the beginning and end of a scheduling cycle should be equal to ensure the energy storage's regulation capability in the next cycle.

[0160] The energy storage state of charge should meet the following requirements:

[0161]

[0162] In the formula: E represents the state of charge of energy storage during time period t in season i; soc-max This represents the upper limit of the energy storage state of charge; E soc-min This is the limit of the energy storage state of charge; The state of charge at the start of seasonal scheduling cycle i; The state of charge at the end of seasonal scheduling period i; ζ c For energy storage charging efficiency; ζ d The discharge efficiency of energy storage.

[0163] Another embodiment of the present invention provides a planning system including a processor and a memory. The memory stores a computer program, and the processor invokes the computer program to execute the steps of the aforementioned method. It should be noted that, in this embodiment of the present invention, the processor may be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. The memory may include read-only memory and random access memory, and provides instructions and data to the processor. The memory may also include non-volatile random access memory.

[0164] Another embodiment of the present invention provides a readable storage medium storing a computer program, which is invoked by a processor to perform the steps of the aforementioned method. It should be noted that examples of readable storage media may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other optical or magnetic storage media.

[0165] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A method for capacity planning of a biomass energy-photovoltaic-energy storage combined power generation system, characterized in that, Comprising: S1: establishing a biomass power plant model; S2: establishing a capacity planning model containing a biomass power plant, a photovoltaic power plant and energy storage based on the biomass power plant model; the capacity planning model takes the minimum total cost of the combined power generation system as the objective function; S3: defining an effect evaluation index; S4: solving the capacity planning model in step S2 to obtain an optimal capacity planning result meeting the effect evaluation index; the optimal capacity planning result is the capacity of the biomass power plant, the photovoltaic power plant and the energy storage; The constraint condition of the objective function of the capacity planning model containing a biomass power plant, a photovoltaic power plant and energy storage includes: The capacity lower limit of the biomass power, photovoltaic and energy storage combined power generation system is 0, and the upper limit is 10 times the maximum load in a day, expressed as: In the formula, is the maximum load for the day; Biomass energy operation output and photovoltaic operation output satisfies: wherein: is the lower bound of the biomass energy output for season i time period t; is the lower bound of the photovoltaic output for season i time period t; is the upper bound of the biomass energy output for season i time period t, is the upper bound of the photovoltaic output for season i time period t; The state of charge of the energy storage should meet: where: SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; SoESeasoni, t is the state of charge of the energy storage for season i time period t; 2.The method according to claim 1, wherein, The collection cost of biological raw materials in the biomass power plant model in step S1 includes the purchase cost, transportation cost and other costs of biological raw materials: wherein is the annual cost of collection; is the annual cost of fuel acquisition; is the annual cost of fuel transportation; is other costs; The annual purchase cost of fuel is determined by the annual consumption of fuel and the purchase price of fuel: In the formula, is the annual fuel consumption; is the fuel purchase price; The annual consumption of fuel depends on the power generation scale of the power plant and the annual operation time of the unit: In the formula, is the fuel consumption rate; P is the unit power; t is the annual operation time of the unit. The calculation formula of the amount of biological raw materials required per unit of electrical energy is: wherein is the lower heating value of the fuel; is the efficiency of the power generation; The fuel transportation cost is related to the collection amount, distribution density of biological raw materials, collection coefficient of biological raw materials, available coefficient of biological raw materials and unit transportation cost factor; The fuel transportation cost is: In the formula, k is a comprehensive coefficient determined by the collection coefficient and the available coefficient of biological raw materials; ρ is the distribution density of biological raw materials; c is the unit transportation cost; and R is the collection radius; The collection radius is determined by the annual consumption of fuel: The other cost is: In the formula, a —— the percentage of other costs in total collection costs; For collection costs.

3. The method of claim 1, wherein, The objective function is: In the formula: is the total cost of the system; is the initial cost of the system; is the operation and maintenance cost; is the electricity purchase cost to the grid; is the energy storage benefit; is the environmental benefit; The initial cost of the system is converted to the daily initial cost, which is: wherein: is the depreciation coefficient; is the biomass power plant capacity; is the biomass power plant price per capacity; is the photovoltaic power plant capacity; is the photovoltaic power plant price per capacity; is the energy storage capacity; is the energy storage price per capacity; d is the depreciation rate; y is the useful life; The operation and maintenance cost of the system is: In the formula: is the operating time of the biomass power plant within a day; is the operating time of the photovoltaic power plant within a day; is the operating time of the energy storage within a day; is the operating and maintenance cost of the biomass power plant per unit of time; is the operating and maintenance cost of the photovoltaic power plant per unit of time; is the operating and maintenance cost of the energy storage per unit of time; The purchase cost of the system to the power grid is: In the formula: is the electricity price of the grid at time t; is the electricity purchased by the system from the grid at time t; The energy storage benefit is: In the formula: is the total energy storage revenue; is the revenue from the grid connection of new renewable energy; is the new biomass power generation in season i time period t, is the new photovoltaic power generation in season i time period t; is the biomass on-grid electricity price, is the photovoltaic on-grid electricity price; The environmental protection benefit is: wherein: the daily power generation of biomass energy; the daily power generation of photovoltaic; N is the number of types of pollutants; the environmental value cost of the kth type of pollutants for thermal power generation; the environmental value cost of the kth type of pollutants for biomass energy power generation; the environmental value cost of the kth type of pollutants for photovoltaic power generation. 4.The method according to claim 1, wherein, The effect evaluation index includes the complementary characteristics of biomass energy and photovoltaic; the smaller the time, the better the complementary characteristics of the two, the smaller the capacity of the energy storage configured, and the lower the cost.

5. The biomass-photovoltaic-energy storage combined power generation system capacity planning method according to claim 4, wherein The complementary characteristics of biomass energy and photovoltaic are the fluctuation of the sum of the output power of biomass power generation and photovoltaic power generation relative to the load power, expressed as: In the formula, D is the complementary characteristics of biomass energy and photovoltaic; is the average power of the load; is the power of biomass power generation at time t; is the power of photovoltaic power generation at time t; is the power of the load at time t; Constraint condition: The rated maximum biomass energy is complementary to photovoltaic characteristics. 6.The method for capacity planning of a biomass energy-photovoltaic-energy storage combined power generation system according to claim 1, wherein, The effect evaluation index includes: power supply loss rate ; power supply loss rate to reflect the reliability of the biomass energy, photovoltaic storage combined power generation system, the smaller the power supply loss rate , the more reliable the system power supply; its expression is: In the formula: is the power supply loss rate; is the energy storage power at time t; Constraint condition: The maximum power supply loss rate is 0.

7. The method of claim 1, wherein, The effect evaluation index includes the comprehensive utilization rate of biomass energy and photovoltaic combined power generation; the larger the comprehensive utilization rate of biomass energy and photovoltaic combined power generation, the smaller the renewable energy output fluctuation of the combined power generation system; and the expression is: where: R is the biomass energy and photovoltaic combined power generation comprehensive utilization rate; is the biomass energy output of season i time period t, is the photovoltaic output of season i time period t; is the upper limit of the biomass energy output of season i time period t, is the upper limit of the photovoltaic output of season i time period t; Constraint condition: In the formula, Minimum biomass energy and photovoltaic combined power utilization rate.

8. A planning system characterized by: The processor and the memory are included, the memory stores a computer program, and the processor calls the computer program to execute the steps of the method of any one of claims 1-7.

9. A readable storage medium characterized by: The computer program is stored, and the computer program is called by the processor to execute the steps of the method of any one of claims 1-7.

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