Power system optimization method and device based on biomass energy power generation facility site selection

Abstract

The invention provides an electric power system optimization method and device based on biomass energy power generation facility site selection, which can be applied to the technical field of biomass energy and electric power systems, and the method comprises the following steps: marking existing power generation facility data on grids; determining a first area for constructing biomass energy power generation facilities based on the power supply and demand data related to the existing power generation facility data; and simulating power generation costs in different scenes according to a preset function, and determining an optimal site selection area for constructing the biomass energy power generation facility in the first area based on the power generation costs.

Description

Technical Field

[0001] The present disclosure relates to the technical field of biomass energy and power system, and more specifically, to a power system optimization method and device based on the site selection of biomass energy power generation facilities. Background Art

[0002] The transformation of the energy industry is the core issue of carbon neutrality, among which the power sector faces the most severe challenges. Current planning research on the power sector mainly focuses on replacing the proportion of non-renewable energy in the power system with renewable energy, such as increasing the installed capacity of wind power and photovoltaic power generation. However, current research lacks consideration of biomass energy generation. Biomass energy is a renewable energy with zero carbon emissions and huge power generation potential. It can be directly burned for power generation or coupled power generation by transforming existing thermal power. The sources of biomass energy are mainly crop straw and forestry residues, which are relatively scattered and have obvious seasonal characteristics. When considering the site selection and grid connection difficulty of biomass energy power generation facilities, it is necessary to consider the distance from the supply end and the cross-seasonal storage problem at the intermediate end. In addition, there are many existing power generation technologies with different efficiencies and costs. Under the goal of achieving a balance between power supply and demand, there are often multiple solutions. How to achieve a balance between power supply and demand while taking into account the lowest cost and ultimately achieving carbon neutrality requires the establishment of a model that can determine the order of power dispatch. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] The present disclosure provides a method and device for optimizing a power system based on the site selection of biomass energy power generation facilities, which are used to at least partially solve one of the above-mentioned technical problems.

[0005] (II) Technical solution

[0006] According to a first aspect of the present disclosure, a method for optimizing an electric power system based on the site selection of a biomass energy power generation facility is provided, the method comprising: marking existing power generation facility data on a grid; determining a first area for constructing a biomass energy power generation facility based on power supply and demand data related to the existing power generation facility data; simulating power generation costs under different scenarios according to a preset function, and determining the best site selection area for constructing a biomass energy power generation facility in the first area based on the power generation cost.

[0007] According to the embodiments of the present disclosure, the scheduling order of existing power generation facilities is fixed units, wind power generation and photovoltaic power generation, nuclear power and hydropower, and other thermal power. The scheduling order of biomass energy power generation is between fixed unit power generation and wind power generation and photovoltaic power generation.

[0008] According to an embodiment of the present disclosure, the fixed unit is an existing power generation facility that must be operated, and the first area for constructing the biomass energy power generation facility is determined based on the power supply and demand data, including: obtaining the power supply data of the fixed unit power generation facilities in each grid and the power demand data of the grid; when the relationship between the power supply data and the power demand data of the grid meets the first condition, the grid is determined as the first area for constructing the biomass energy power generation facility.

[0009] According to an embodiment of the present disclosure, the first condition is that the power supply data of the fixed unit power generation facility is less than the power demand data of the grid.

[0010] According to an embodiment of the present disclosure, a biomass energy power generation facility includes a raw material supply area, an intermediate storage area, and a terminal power generation area.

[0011] According to an embodiment of the present disclosure, the power generation cost in different scenarios is simulated according to a preset function, and the optimal site selection area for constructing a biomass energy power generation facility is determined in the first area based on the power generation cost, including: determining a division scheme for the first area based on geographic information, wherein the division scheme includes alternative addresses for a raw material supply area, alternative addresses for an intermediate storage area, and alternative addresses for a terminal power generation area; respectively calculating the power generation cost, the operating cost, and the link cost between the alternative addresses for each alternative address; and determining the optimal site selection area for constructing a biomass energy power generation facility based on the calculation results.

[0012] According to an embodiment of the present disclosure, the link costs between the candidate addresses include the grid connection costs between the biomass energy power generation facilities and the existing power generation facilities, the costs of new transmission lines and the power storage costs.

[0013] According to an embodiment of the present disclosure, the optimal site selection area for constructing a biomass energy power generation facility is determined based on calculation results, including: calculating the total cost of biomass energy power generation and other power generation settings for each site selection scheme under different scenarios based on a preset function; and determining the optimal site selection area for the biomass energy power generation facility based on the total cost of each site selection scheme under different scenarios.

[0014] According to an embodiment of the present disclosure, the expression of the preset function is:

[0015]

[0016] Among them, FG is the annual cost of fixed units to generate electricity for the number of hours they must run, BMF is the annual cost of the raw material supply area for biomass energy power generation, BMS is the annual cost of the intermediate storage area for biomass energy power generation, BMG is the annual cost of the terminal power generation area for biomass energy power generation, WG is the annual cost of wind power generation, SG is the annual cost of photovoltaic power generation, NG is the annual cost of nuclear power generation, HG is the annual cost of hydropower generation, FG is the annual cost of the remaining thermal power generation, PS is the annual cost of power storage, and ET is the annual cost of power transmission.

[0017] According to a second aspect of the present disclosure, there is provided a power system optimization device based on the siting of biomass energy power generation facilities, the device comprising: a labeling module for labeling existing power generation facility data on a grid; a first determination module for determining a first area for constructing a biomass energy power generation facility based on power supply and demand data related to the existing power generation facility data; and a second determination module for simulating power generation costs under different scenarios according to a preset function, and determining the best site selection area for constructing a biomass energy power generation facility in the first area based on the power generation cost.

[0018] (III) Beneficial effects

[0019] The power system optimization method based on biomass energy power generation facility site selection provided by the present disclosure includes at least the following beneficial effects:

[0020] By establishing an objective function, the total cost of different power dispatching sequences can be calculated under preset scenario conditions to achieve the optimal power system layout. By dividing the region into the raw material supply area, intermediate storage area, and terminal power generation area for biomass energy power generation, the site selection of biomass energy power generation facilities was preliminarily screened. Under the constraints of carbon neutrality and minimum cost, the objective function simulation can determine the best area to build biomass power generation facilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0022] Figure 1 A flowchart of a power system optimization method based on biomass energy power generation facility site selection according to an embodiment of the present disclosure is schematically shown;

[0023] Figure 2 The technical roadmap of the power system optimization method based on the site selection of biomass energy power generation facilities according to the embodiment of the present disclosure is schematically shown;

[0024] Figure 3 The structural block diagram of the power system optimization device based on the site selection of biomass energy power generation facilities according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0026] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0027] In the present disclosure, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0028] In the description of the present disclosure, it is necessary to understand that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the subsystem or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0029] Throughout the drawings, the same elements are represented by the same or similar reference numerals. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present disclosure. The shapes, sizes, and positional relationships of the components in the drawings do not reflect the actual size, proportion, and actual positional relationship. In addition, in the claims, any reference symbol between brackets shall not be construed as a limitation to the claims.

[0030] Similarly, in order to simplify the present disclosure and help understand one or more of the various disclosed aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. The description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0031] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present disclosure, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0032] The disclosed embodiment provides a method for optimizing an electric power system based on the site selection of a biomass energy power generation facility, including: marking existing power generation facility data on a grid; determining a first area for constructing a biomass energy power generation facility based on power supply and demand data related to the existing power generation facility data; simulating power generation costs under different scenarios according to a preset function, and determining the best site selection area for constructing a biomass energy power generation facility in the first area based on the power generation cost.

[0033] Figure 1 A flow chart of a method for optimizing a power system based on site selection of biomass energy power generation facilities according to an embodiment of the present disclosure is schematically shown.

[0034] Figure 2 The technical roadmap of the power system optimization method based on the site selection of biomass energy power generation facilities according to the embodiment of the present disclosure is schematically shown.

[0035] like Figure 1 As shown, the power system optimization method based on the site selection of biomass energy power generation facilities in this embodiment includes operations S110 to S130. Figure 2 The power system optimization method of this embodiment is further introduced.

[0036] In operation S110 , existing power generation facility data is marked on the grid.

[0037] In some embodiments, the study area is divided into several grids, and various existing power facilities that must be operated are marked on the grids to determine the fixed units. Among them, the existing power generation facilities can include, for example, fixed units, wind power generation and photovoltaic power generation, nuclear power and hydropower, and other thermal power. Among them, the scheduling order of power generation facilities can be, for example: fixed units, biomass energy power generation, wind power generation and photovoltaic power generation, nuclear power and hydropower, and other thermal power.

[0038] In operation S120, a first region for constructing a biomass energy power generation facility is determined based on power supply and demand data related to existing power generation facility data.

[0039] In some embodiments, a first area for constructing a biomass energy power generation facility can be determined based on power supply and demand data related to existing power generation facilities, wherein the existing power generation facilities are power generation facilities that are scheduled before biomass energy, such as fixed units.

[0040] In a specific implementation process, the power supply and demand data may include, for example, the power supply data corresponding to the fixed unit power generation facilities in the grid and the power demand data of the grid. When the relationship between the power supply data and the power demand data in the grid meets the first condition, the grid is determined as the first area for constructing biomass energy power generation facilities.

[0041] The power supply data can be collected through the power monitoring platform or related databases to obtain the power generation facility data of the existing fixed units in each grid, which may include, for example, installed capacity, actual power generation, power generation efficiency, etc. The power demand data of each grid can be determined based on the historical power demand data of each grid, where the historical demand data may include, for example, power consumption in different time dimensions (such as annual, monthly, and daily) and change data of power demand data. In addition, the future power demand of the grid can be predicted by using appropriate forecasting methods (such as time series analysis, regression analysis, etc.) in combination with local economic and social development plans, population growth trends, industrial structure adjustments and other factors, and the forecast results can be combined with historical power demand to obtain the power demand data of the grid.

[0042] According to the principle of power supply and demand balance, a reasonable first condition is set. For example, the first condition can be set to that the power supply data of the fixed unit power generation facilities of the grid is less than the power demand data of the grid. The power supply and demand ratio of each grid can also be calculated to reflect the adequacy of power supply. For example, a grid with a power supply and demand ratio below a certain threshold can be used as a preferred area for the construction of biomass energy power generation facilities. In addition, the first condition can also include the growth trend of power demand of each grid into the reference range. For example, when the power supply data is greater than the power demand data, the first condition can be further defined as: when the difference between the power supply data and the power demand data is less than the preset threshold and the future power demand growth trend of the grid is obvious (that is, the growth rate is greater than the preset threshold), the power supply and demand data of the grid meets the preset conditions.

[0043] In operation S130, power generation costs in different scenarios are simulated according to a preset function, and an optimal site selection area for constructing a biomass energy power generation facility is determined in the first area based on the power generation cost.

[0044] In some embodiments, biomass energy power generation facilities can be divided into raw material supply areas, intermediate storage areas and terminal power generation areas. The raw material supply area is mainly responsible for collecting and providing biomass fuels, wherein the raw materials for biomass power generation include agricultural waste (such as crop straw), forestry waste (such as forest residues), animal manure, urban organic waste and special energy crops, etc. These raw materials usually come from farmland, woodland, farms and other areas around the project. Therefore, townships and towns can be set as raw material supply areas, which are close to raw material production areas such as farmland and forest farms for easy acquisition. The intermediate storage area is mainly responsible for the temporary storage and pretreatment of biomass raw materials. Since the supply of biomass raw materials is seasonal and regional, it is necessary to establish storage facilities near the power plant or between the field and the power plant to ensure the stable supply and continuous use of biomass raw materials. For example, it can be selected to be located in the middle of the township, town and city levels for easy transportation and storage. The terminal power generation area is the core area of ​​biomass energy power generation facilities, which is mainly responsible for converting biomass raw materials into electrical energy. Biomass raw materials generate heat energy through combustion, gasification or anaerobic fermentation in the terminal power generation area, and then convert the heat energy into mechanical energy and electrical energy. Generally, cities can be set as terminal power generation areas. These areas often have power load centers, which can facilitate the connection of new power facilities to the grid or the transformation of old power generation facilities.

[0045] In some embodiments, operation S130 may further include operations S1301 to S1303.

[0046] In operation S1301, a division scheme of the first area is determined according to geographic information, wherein the division scheme includes candidate addresses of a raw material supply area, candidate addresses of an intermediate storage area, and candidate addresses of a terminal power generation area.

[0047] In some embodiments, geographic information in the first area is collected, and alternative addresses that can be used as raw material supply areas, intermediate storage areas, and terminal power generation areas are determined in the first area based on the geographic information. Among them, the geographic information may include, for example, topography, landforms, climate, transportation, population distribution, biomass resource distribution, etc. The geographic information is processed and analyzed to extract key elements related to the site selection of biomass energy power generation facilities. According to the distribution of biomass resources, the target area is divided into a raw material supply area, an intermediate storage area, and a terminal power generation area. Among them, the raw material supply area should be an area with rich biomass resources and low collection costs, the intermediate storage area should be an area with convenient transportation and convenient for the transportation and storage of biomass raw materials, and the terminal power generation area should be an area close to the power grid and convenient for power output.

[0048] In operation S1302, the power generation cost and the operation cost of each candidate address and the link cost between the candidate addresses are calculated respectively.

[0049] In some embodiments, for biomass energy power generation facilities, the costs in different areas may be different. For the raw material supply area, the cost mainly comes from the raw material acquisition cost and transportation cost, etc.; for the intermediate storage area, the cost mainly comes from the construction cost, maintenance cost and management cost of the reserve facilities, etc.; for the terminal power generation area, the cost mainly comes from the cost of new facilities or the cost of existing coal-fired power transformation. The link costs between the alternative addresses include the grid connection costs between the biomass energy power generation facilities and the existing power generation facilities, the cost of new transmission lines and the cost of power storage, etc. In addition, for the remaining power generation layers, the costs should also include the installation cost and operation cost of the generator.

[0050] In operation S1303, the best site selection area for constructing the biomass energy power generation facility is determined according to the calculation results.

[0051] In some embodiments, the total cost of biomass energy power generation and other power generation settings for each site selection scheme under different scenarios is calculated based on a preset function; the optimal site selection area for biomass energy power generation facilities is determined based on the total cost of each site selection scheme under different scenarios. Among them, the optimal site selection area can minimize the installation cost and operating cost of new generators on the basis of retaining existing power generation facilities and infrastructure. This result is limited by the balance of power supply and demand per unit time, the available power generation of fixed units that must be operated per unit time, the available power generation of biomass energy per unit time, the available power generation of other power generation facilities (wind power, photovoltaic power, nuclear power, hydropower, thermal power) per unit time, and the transmission distance.

[0052] The expression of the preset function can be:

[0053]

[0054] Among them, FG is the annual cost of fixed units to generate electricity for the number of hours they must run, BMF is the annual cost of the raw material supply area for biomass energy power generation, BMS is the annual cost of the intermediate storage area for biomass energy power generation, BMG is the annual cost of the terminal power generation area for biomass energy power generation, WG is the annual cost of wind power generation, SG is the annual cost of photovoltaic power generation, NG is the annual cost of nuclear power generation, HG is the annual cost of hydropower generation, FG is the annual cost of the remaining thermal power generation, PS is the annual cost of power storage, and ET is the annual cost of power transmission.

[0055] The total cost size under different scenarios is calculated through preset functions. Among them, the scenario preset can be determined according to the goals of different years. The cost size is calculated under floating conditions to determine the scheduling order of the grid, and then determine the optimal site selection area for biomass energy power generation facilities.

[0056] By establishing an objective function, the present disclosure can calculate the total cost of different power dispatching sequences under preset scenario conditions, realize the accurate site selection of biomass energy power generation facilities, and preliminarily screen the site selection of biomass energy power generation facilities by dividing the area into raw material supply area, intermediate storage area, and terminal power generation area for biomass energy power generation. Under the constraints of carbon neutrality and minimum cost, the objective function simulation is carried out to effectively determine the best area for establishing biomass power generation facilities.

[0057] Based on the above-mentioned power system optimization method based on biomass energy power generation facility site selection, the present disclosure also provides a power system optimization device based on biomass energy power generation facility site selection. Figure 3 The device is described in detail.

[0058] Figure 3 The structural block diagram of the power system optimization device based on the site selection of biomass energy power generation facilities according to an embodiment of the present disclosure is schematically shown.

[0059] like Figure 3 As shown, the power system optimization device 300 based on the site selection of biomass energy power generation facilities in this embodiment includes a labeling module 310 , a first determination module 320 and a second determination module 330 .

[0060] The marking module 310 is used to mark the existing power generation facility data on the grid. In one embodiment, the marking module 310 can be used to perform the operation S110 described above, which will not be described in detail here.

[0061] The first determination module 320 is used to determine the first area for constructing biomass energy power generation facilities based on the power supply and demand data related to the existing power generation facility data. In one embodiment, the first determination module 320 can be used to perform the operation S120 described above, which will not be repeated here.

[0062] The second determination module 330 is used to simulate the power generation cost under different scenarios according to a preset function, and determine the best site selection area for building a biomass energy power generation facility in the first area based on the power generation cost. In one embodiment, the second determination module 330 can be used to perform the operation S130 described above, which will not be repeated here.

[0063] According to an embodiment of the present disclosure, any multiple modules of the annotation module 310, the first determination module 320, and the second determination module 330 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the annotation module 310, the first determination module 320, and the second determination module 330 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the annotation module 310, the first determination module 320, and the second determination module 330 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0064] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all be included in the scope of protection of the present disclosure.

Claims

1. A method for optimizing the power system based on the site selection of biomass energy power generation facilities, characterized in that: The method comprises: Label the existing power generation facility data on the grid; determining a first region for constructing a biomass energy power generation facility based on power supply and demand data associated with existing power generation facility data; The power generation costs under different scenarios are simulated according to a preset function, and the best site selection area for constructing a biomass energy power generation facility is determined in the first area based on the power generation costs.

2. The power system optimization method according to claim 1, characterized in that: The scheduling order of the existing power generation facilities is fixed units, wind power generation and photovoltaic power generation, nuclear power and hydropower, and other thermal power. The scheduling order of biomass energy power generation is between the fixed unit power generation and the wind power generation and photovoltaic power generation.

3. The power system optimization method according to claim 2, characterized in that: The fixed unit is an existing power generation facility that must be operated. The first area for constructing the biomass energy power generation facility is determined based on the power supply and demand data, including: Obtaining power supply data of fixed unit power generation facilities in each grid and power demand data of the grid; In a case where the relationship between the power supply data and the power demand data of the grid satisfies a first condition, the grid is determined as a first area for constructing a biomass energy power generation facility.

4. According to the power system optimization method of claim 3, the first condition is that the power supply data of the fixed unit power generation facility is less than the power demand data of the grid.

5. The power system optimization method according to claim 1, characterized in that: The biomass energy power generation facility includes a raw material supply area, an intermediate storage area, and a terminal power generation area.

6. The power system optimization method according to claim 5, characterized in that: The simulating the power generation costs in different scenarios according to the preset function and determining the best site selection area for constructing the biomass energy power generation facility in the first area based on the power generation costs includes: Determining a division scheme of the first area based on geographic information, wherein the division scheme includes an alternative address of a raw material supply area, an alternative address of an intermediate storage area, and an alternative address of a terminal power generation area; Calculate the power generation cost, operation cost of each candidate address and the link cost between the candidate addresses respectively; The optimal site selection area for building biomass energy power generation facilities is determined based on the calculation results.

7. The power system optimization method according to claim 5, characterized in that: The link costs between the candidate addresses include the grid connection costs between the biomass energy power generation facilities and the existing power generation facilities, the costs of new transmission lines and the power storage costs.

8. The power system optimization method according to claim 6, characterized in that: The optimal site selection area for building biomass energy power generation facilities is determined based on the calculation results, including: Calculate the total cost of biomass energy generation and other power generation settings for each site selection scheme under different scenarios based on a preset function; Based on the total cost of each site selection plan under different scenarios, the optimal site selection area for biomass energy power generation facilities is determined.

9. The power system optimization method according to claim 8, characterized in that: The expression of the preset function is: Among them, FG is the annual cost of fixed units to generate electricity for the number of hours they must run, BMF is the annual cost of the raw material supply area for biomass energy power generation, BMS is the annual cost of the intermediate storage area for biomass energy power generation, BMG is the annual cost of the terminal power generation area for biomass energy power generation, WG is the annual cost of wind power generation, SG is the annual cost of photovoltaic power generation, NG is the annual cost of nuclear power generation, HG is the annual cost of hydropower generation, FG is the annual cost of the remaining thermal power generation, PS is the annual cost of power storage, and ET is the annual cost of power transmission.

10. A power system optimization device based on the site selection of biomass energy power generation facilities, characterized in that: The device comprises: A labeling module, used to label the existing power generation facility data on the grid; A first determination module, for determining a first area for constructing a biomass energy power generation facility based on power supply and demand data related to existing power generation facility data; The second determination module is used to simulate the power generation costs under different scenarios according to a preset function, and determine the best site selection area for constructing biomass energy power generation facilities in the first area based on the power generation costs.

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