Multi-energy complementary park planning and design method, device, terminal equipment and storage medium

Abstract

The present invention discloses a multi-energy complementary park planning and design method, device, terminal equipment and storage medium. The method includes: constructing an objective function based on the park planning cost and conditional risk value; constructing constraint conditions, and solving the objective function under the constraint conditions; and using the solution results to design a multi-energy complementary park planning scheme. The multi-energy complementary park planning and design method provided by the present invention establishes an objective function with the goal of minimizing the total cost, and considers the influence of conditional risk factors, which can effectively measure the park system risk, thereby formulating a reasonable, reliable and risk-avoiding planning scheme. The present invention can provide scientific and objective guidance for the planning and design of regional multi-energy complementary parks, which is conducive to promoting the development of park energy Internet.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and in particular to a multi-energy complementary park planning and design method, device, terminal equipment and storage medium. Background Art

[0002] The multi-energy complementary park is formed by closely coupling the electricity, gas and thermal systems, and implementing organic coordination and optimization of different energy links in the planning and operation process, thereby forming an integrated energy production, supply and consumption system with electricity as the core. The reasonable planning of the multi-energy complementary park is not only an important prerequisite for the system to give full play to the advantages of multi-energy complementarity and cascade utilization, but also a strong guarantee for the future construction of energy Internet and the attraction of investment in the construction of multi-energy complementary parks.

[0003] Considering the differences between different energy types, the planning of multi-energy complementary parks still faces many difficulties. For example, the current multi-energy complementary park models and methods mainly focus on the coordinated optimization of investment and operation strategies, lacking consideration of system risk management. Not only are the risk indicators unclear, but there is also a lack of unified standards for system risk issues. Therefore, there is an urgent need for a multi-energy complementary park planning and design method that can effectively measure system risks and thus assist in formulating reasonable and reliable planning schemes. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-energy complementary park planning and design method, device, terminal equipment and storage medium to solve the problem that the existing multi-energy complementary park model lacks consideration of risk management and unified standards, which leads to the inability of park planning to effectively avoid risks and lacks reliability and rationality.

[0005] To achieve the above object, the present invention provides a multi-energy complementary park planning and design method, comprising:

[0006] Construct an objective function based on the park planning cost and conditional risk value;

[0007] Constructing constraint conditions and solving the objective function under the constraint conditions;

[0008] The solution results are used to design a multi-energy complementary park planning scheme.

[0009] Further, as a preferred embodiment, the objective function is constructed based on the park planning cost and conditional risk value, including:

[0010] The objective function is constructed using investment cost, transaction cost, maintenance cost, load shedding cost and conditional risk value:

[0011]

[0012]

[0013] Where, IC, TC s , MC s , LC s They represent investment cost, transaction cost on a typical day, maintenance cost on a typical day, and load shedding cost on a typical day, respectively; β and α represent risk index and credibility, respectively; CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; p s represents the probability of different typical days; [·] + Indicates the part where ·≥0.

[0014] Further, preferably, the construction constraint conditions include:

[0015] Determine the equipment energy conversion model:

[0016]

[0017] According to the equipment energy conversion model, the first constraint condition is determined:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] In the formula, the superscripts i and j represent the jth capacity selection of the ith equipment; the superscripts s and t represent the time t of the sth typical day; the superscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; P is the input power of the equipment; is the energy conversion coefficient of the equipment, the subscript he indicates that electrical energy is converted into thermal energy, L is the output power of the equipment; LOAD indicates the load power; L SHED represents the load shedding power; u is a binary variable.

[0024] Furthermore, preferably, the construction constraint condition further includes:

[0025] The second constraint is determined using the energy storage system model:

[0026]

[0027]

[0028]

[0029] In the formula, Binary variables representing charging and discharging states, respectively. n represents the energy storage type, which can be any one of electrical energy e, thermal energy h, and cold energy c. Respectively represent charging power and discharging power; Z n Integer variable for energy storage system planning module; They represent the maximum charging power and the maximum discharging power respectively.

[0030] Furthermore, preferably, the construction constraint condition further includes:

[0031] The third constraint is determined using the energy storage system model:

[0032]

[0033]

[0034]

[0035] In the formula, Respectively represent the charge state at time t and t-1; Indicates the maximum capacity of a single module; Respectively represent the initial and final charge states; η ch,n , η dis,n They respectively represent the efficiency of charging and discharging of the energy storage system.

[0036] Furthermore, preferably, the construction constraint condition further includes:

[0037] Establish the power balance formula between demand and supply of multi-energy complementary parks:

[0038]

[0039]

[0040]

[0041] In the formula, the subscripts s and t represent the time t of the sth typical day; the subscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; the subscripts ch and dis represent charging and discharging respectively; P is the charging and discharging power of the energy storage device; L is the output power of the multi-energy device; LOAD represents the load power; L SHED Indicates load shedding power.

[0042] The present invention also provides a multi-energy complementary park planning and design device, comprising:

[0043] An objective function construction unit, used to construct an objective function based on the park planning cost and conditional risk value;

[0044] A constraint condition construction unit, used for constructing constraint conditions and solving the objective function under the constraint conditions;

[0045] The planning scheme design unit is used to design a multi-energy complementary park planning scheme using the solution results.

[0046] Further, preferably, the objective function construction unit is further used for:

[0047] The objective function is constructed using investment cost, transaction cost, maintenance cost, load shedding cost and conditional risk value:

[0048]

[0049]

[0050] Where, IC, TC s , MC s , LC s They represent investment cost, transaction cost on a typical day, maintenance cost on a typical day, and load shedding cost on a typical day, respectively; β and α represent risk index and credibility, respectively; CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; p s represents the probability of different typical days; [·] + Indicates the part where ·≥0.

[0051] The present invention also provides a terminal device, comprising:

[0052] one or more processors;

[0053] A memory, coupled to the processor, for storing one or more programs;

[0054] When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-energy complementary park planning and design method as described in any one of the above items.

[0055] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the multi-energy complementary park planning and design method as described in any one of the above items is implemented.

[0056] Compared with the prior art, the beneficial effects of the present invention are:

[0057] The present invention discloses a multi-energy complementary park planning and design method, device, terminal equipment and storage medium. The method includes: constructing an objective function based on the park planning cost and conditional risk value; constructing constraint conditions, and solving the objective function under the constraint conditions; and using the solution results to design a multi-energy complementary park planning scheme. The multi-energy complementary park planning and design method provided by the present invention establishes an objective function with the goal of minimizing the total cost, and considers the influence of conditional risk factors, which can effectively measure the park system risk, thereby formulating a reasonable, reliable and risk-avoiding planning scheme. The present invention can provide scientific and objective guidance for the planning and design of regional multi-energy complementary parks, which is conducive to promoting the development of park energy Internet. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 It is a flowchart of a multi-energy complementary park planning and design method provided by a certain embodiment of the present invention;

[0060] Figure 2 It is a schematic diagram of the topological structure of a regional multi-energy complementary park system provided by an embodiment of the present invention;

[0061] Figure 3 It is a schematic diagram of the principle of investment cost and its changes under different credibility and risk preferences provided by a certain embodiment of the present invention;

[0062] Figure 4 It is a schematic diagram of the principle of total cost and its changes under different credibility and risk preferences provided by a certain embodiment of the present invention;

[0063] Figure 5 It is a structural schematic diagram of a multi-energy complementary park planning and design device provided by a certain embodiment of the present invention;

[0064] Figure 6 It is a schematic diagram of the structure of a terminal device provided by a certain embodiment of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0067] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0068] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0069] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0070] See also Figure 1 , a certain embodiment of the present invention provides a multi-energy complementary park planning and design method. Figure 1 As shown, the multi-energy complementary park planning and design method includes steps S10 to S30. The specific steps are as follows:

[0071] S10. Construct the objective function based on the park planning cost and conditional risk value.

[0072] In this step, when constructing the objective function, the system risk factor is taken into account, and the corresponding objective function is established with the goal of minimizing the cost.

[0073] Specifically, in this embodiment, the park planning cost includes: investment cost, transaction cost, maintenance cost and load shedding cost; the expression of the objective function constructed by using the park planning cost and the conditional risk value is:

[0074]

[0075]

[0076] In formula (1), IC, TC s , MC s , LC s They represent investment cost, transaction cost of typical day s, maintenance cost of typical day s, and load shedding cost of typical day s respectively; β and α represent risk index and credibility respectively; represents the trade-off between transaction cost, maintenance cost, load shedding cost and conditional risk value; p srepresents the probability of different typical days; [·] + Indicates the part where ·≥0.

[0077] In formula (2), CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; Assuming α = 0.95, CVaR 0.95 It represents the expected loss in the worst 5% of cases, such as CVaR 0.95 = 12 million yuan, indicating that the expected loss in the worst 5% of cases is 12 million yuan, or there is a 95% probability that the expected loss will not exceed 12 million yuan. The risk index β represents the investment cost that investors are willing to pay for unit risk. Its calculation method is shown in (3), where Loss is the total investment loss of the investor in the past three years, and Capital is the total investment of the investor in the past three years. The value of β is between 0 and 1. The closer it is to 1, the more investors value risk, indicating that they are less willing to accept investment projects with high losses.

[0078]

[0079] ψ(x,Exp Loss )={Exp Loss |f(x)≤Exp Loss} (4)

[0080] VaR α =min{Exp Loss |ψ(x,Exp Loss )≥α} (5)

[0081] In formula (4), x represents a specific investment plan, f(x) represents the loss function of the investment plan x, ψ(x,Exp Loss ) is the cumulative distribution function of f(x), which means that when the expected loss is less than Exp Loss The probability of. In formula (5) is the risk value VaR α Regarding the definition of credibility α, the value of α is usually close to 1. For example, when its value is 0.95, it means that the planning result is 95% credible. Loss ) is a continuous and increasing function, so the value of α is unique.

[0082] Furthermore, the calculation methods of investment cost, transaction cost, maintenance cost and load shedding cost are described as follows. First, the calculation formula of investment cost IC is:

[0083]

[0084]

[0085]

[0086] Formula (6) represents the investment cost of the regional multi-energy complementary park, which is expressed as the sum of the investment costs of equipment with different alternative capacities and different types of energy storage modules with conversion factors. Formulas (7)-(8) respectively represent the corresponding conversion factors of equipment with different alternative capacities and different types of energy storage modules amortized over their life cycle.

[0087] Furthermore, the calculation formulas of transaction cost TC, maintenance cost MC and load shedding cost LC are as follows:

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095] Where, formula (9) is the transaction cost, pr t e ,pr g Respectively represent the electricity price and gas price at time t. The transaction cost includes the external electricity cost and external gas cost of all equipment in each scenario in the regional multi-energy complementary park, corresponding to formulas (10) and (11) respectively. Formula (12) represents the maintenance cost, λ i ,λ n They represent the unit maintenance cost of device i and the unit charging and discharging cost of energy storage device n respectively. The maintenance cost is related to the input power of each device and the charging and discharging mileage of the energy storage, and are expressed by formulas (13) and (14) respectively. Formula (15) shows that the load shedding cost is the product of the unit power load shedding cost and the load shedding power under each typical day, μ m Indicates the unit load shedding cost of shedding energy type m load.

[0096] S20: Construct constraint conditions, and solve the objective function under the constraint conditions.

[0097] Specifically, in this step, the equipment energy conversion model is first determined:

[0098]

[0099] In formula (16), the subscripts i and j represent the jth capacity selection of the i-th equipment; the subscripts s and t represent the time t of the s-th typical day; the subscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; P is the input power of the equipment; is the energy conversion coefficient of the equipment; the subscript AB indicates that energy A is converted into energy B, A, B∈{e,g,h,c}, for example, the subscript he indicates that electrical energy is converted into thermal energy; L is the output power of the equipment; LOAD indicates the load power; L SHED represents the load shedding power; u is a binary variable.

[0100] Furthermore, according to the equipment energy conversion model, the first constraint condition is determined:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106] Formulas (17)-(18) are the equipment input power constraints. The equipment selection is modeled using a binary variable u. If the candidate option j of a certain equipment i is selected, its value is equal to 1, otherwise it is 0. Formulas (19)-(21) indicate that the maximum load shedding power cannot exceed the load power.

[0107] In a specific implementation, in order to increase the flexibility of the planning scheme,

[0108] The step S20 of constructing the constraint conditions also includes:

[0109] The second constraint is determined using the energy storage system model:

[0110]

[0111]

[0112]

[0113] Wherein, formula (22) is used to ensure that the energy storage system cannot charge and discharge energy at the same time; Binary variables representing charging and discharging states, respectively. n represents the energy storage type, which can be any one of electrical energy e, thermal energy h, and cold energy c. Respectively represent charging power and discharging power; Zn Integer variable for energy storage system planning module; They represent the maximum charging power and the maximum discharging power respectively.

[0114] In a specific embodiment, the construction constraint condition in step S20 further includes:

[0115] The third constraint is determined using the energy storage system model:

[0116]

[0117]

[0118]

[0119] In the formula, Respectively represent the charge state at time t and t-1; Indicates the maximum capacity of a single module; Respectively represent the initial and final charge states; η ch,n , η dis,n Respectively represent the efficiency of energy storage system charging and discharging. It should be noted that the charging and discharging power of the energy storage system is limited by the investment options in formulas (23)-(24), where the upper limit is the integer variable Z representing the energy storage system planning module. n And the maximum charge and discharge power P of a single module max Joint decision.

[0120] Formula (25) indicates that the maximum SOC (state of charge) is represented by the number of energy storage planning modules Z n , the maximum capacity of a single module Jointly determined; Formula (26) represents the SOC operating formula of the energy storage system; Formula (27) is used to ensure that the initial value and final value of the SOC in a typical day are the same.

[0121] In a specific embodiment, the construction constraint condition in step S20 further includes:

[0122] Establish the power balance formula between demand and supply of multi-energy complementary parks:

[0123]

[0124]

[0125]

[0126] In the formula, the subscripts s and t represent the time t of the sth typical day; the subscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; the subscripts ch and dis represent charging and discharging respectively; P is the charging and discharging power of the energy storage device; L is the output power of the multi-energy device; LOAD represents the load power; L SHED It should be noted that constraints (28)-(30) are the power balance formulas between the demand and supply of the regional multi-energy complementary park, in which the supply and demand of the power load should be strictly equal, and the heating load and cooling load can be appropriately relaxed according to the actual application situation.

[0127] S30. Use the solution results to design a multi-energy complementary park planning scheme.

[0128] It can be understood that the objective function in step S10 can be solved by the constraint conditions in step S20, and in step S30, it is only necessary to plan the multi-energy complementary park according to the solution result, which can effectively reduce the risk of the planning system and generate a reasonable and reliable planning scheme.

[0129] In summary, the multi-energy complementary park planning and design method provided by the embodiment of the present invention establishes an objective function with the goal of minimizing the total cost, and takes into account the influence of conditional risk factors. It can effectively measure the system risk of the park, thereby formulating a reasonable, reliable and risk-avoiding planning scheme, so as to provide scientific and objective guidance for the planning and design of regional multi-energy complementary parks, which is conducive to promoting the development of park energy Internet.

[0130] In a specific implementation manner, in order to help understand the solution of the present invention and the effects that can be achieved, the solution provided by the present invention is described in detail by taking a multi-energy complementary park in a certain area in southern China as an example:

[0131] First, the system topology and equipment composition are as follows Figure 2 As shown. The planning of the multi-energy complementary park considers combined cooling, heating and power (CCHP), gas boiler (GB), air conditioning (AC), electric energy storage system (BESS), thermal energy storage system (TESS) and cold energy storage system (CESS). In order to be realistic and verify the rationality of the model, the annual discount rate of funds is set to 5%, and the annual growth rates of electric load, heat load and cold load are 5%, 3% and 2% respectively. The operation scenario is considered at an hourly granularity with a time span of 10 years. K-means clustering is used for scenario reduction to reduce the typical day from 3650 days to 100 days, thereby avoiding heavy and unnecessary computational burden. The example is based on the YALMIP toolbox in MATLABR2019B for modeling, and the commercial solver Gurobi 9.0.0 is used for solving.

[0132] Furthermore, the operating parameters of other equipment in the system are shown in Table 1:

[0133] Table 1 Equipment operating parameters

[0134]

[0135]

[0136] As shown in Table 1, the maximum charging and discharging power of the energy storage equipment is 25% of the rated capacity. Combined with the actual local tiered electricity price policy, the peak electricity price is from 11:00 to 15:00 and 19:00 to 21:00, the valley electricity price is from 0:00 to 7:00, and the remaining time is the flat electricity price. Among them, the energy prices of different types and time periods are shown in Table 2:

[0137] Table 2 Energy prices of different types and time periods

[0138]

[0139] Further, the investment decision is analyzed: Since the present invention takes the investment cost into consideration, different planning schemes can be designed for different risk preferences. Generally speaking, the value of the risk index indicates the investor's aversion to risk. Investors with a risk index greater than 0.5 are "risk-averse investors", investors with a risk index lower than 0.5 are "risk-preference investors", and investors with a risk index of 0.5 are "risk-neutral investors". Among them, the investment cost and its changes under different credibility and risk preferences are as follows: Figure 3 As shown in Figure 2. Among them, the investment cost and its change chart under different credibility and risk index can provide decision-making basis for investors with different risk preferences. Figure 3 In the figure, since BESS benefits from the arbitrage of the peak-valley-flat electricity price policy, it is more inclined to invest in BESS. In the case of higher risk aversion and higher credibility requirements, investment decisions tend to choose more ESS (including BESS, TESS and CESS) rather than energy supply facilities with larger capacity (CCHP, GB, AC). This figure can be used as an auxiliary tool to provide investment plans for different types of investors.

[0140] Finally, in this embodiment, a total cost analysis is also performed. In the objective function formula (1), the investment decision variables of the first-stage equipment limit the power operating range of the second-stage multi-energy equipment and energy storage. Specifically, Figure 4 The surface of the total cost of fitting varies with the risk index and credibility. Figure 4 It can be seen that the fitting surface of total cost, credibility and risk index is close to a plane. As investors become more "risk-averse", capital investment results require higher certainty requirements, and the total cost increases almost linearly. This surface can also be used as an investment reference to provide different investors with a rough range of total costs considering operating costs.

[0141] Therefore, by considering investment costs, operating costs and conditional risk factors, it is possible to develop reasonable, reliable and risk-avoiding planning schemes that match decision makers with different risk preferences, which is conducive to promoting the development of park energy Internet.

[0142] See also Figure 5 A certain embodiment of the present invention further provides a multi-energy complementary park planning and design device, comprising:

[0143] Objective function construction unit 01, used to construct an objective function based on the park planning cost and conditional risk value;

[0144] A constraint condition construction unit 02, used for constructing constraint conditions and solving the objective function under the constraint conditions;

[0145] The planning scheme design unit 03 is used to design a multi-energy complementary park planning scheme using the solution results.

[0146] In a specific embodiment, the objective function construction unit 01 is further used to:

[0147] The objective function is constructed using investment cost, transaction cost, maintenance cost, load shedding cost and conditional risk value:

[0148]

[0149]

[0150] Where, IC, TC s , MC s , LC s They represent investment cost, transaction cost on a typical day, maintenance cost on a typical day, and load shedding cost on a typical day, respectively; β and α represent risk index and credibility, respectively; CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; p s represents the probability of different typical days; [·] + Indicates the part where ·≥0.

[0151] In a specific embodiment, the constraint condition construction unit 02 is further used for:

[0152] Determine the equipment energy conversion model:

[0153]

[0154] According to the equipment energy conversion model, the first constraint condition is determined:

[0155]

[0156]

[0157]

[0158]

[0159]

[0160] In the formula, the superscripts i and j represent the jth capacity selection of the ith equipment; the superscripts s and t represent the time t of the sth typical day; the superscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; P is the input power of the equipment; is the energy conversion coefficient of the equipment, the subscript he indicates that electrical energy is converted into thermal energy, L is the output power of the equipment; LOAD indicates the load power; L SHED represents the load shedding power; u is a binary variable.

[0161] In a specific embodiment, the constraint condition construction unit 02 is further used for:

[0162] The second constraint is determined using the energy storage system model:

[0163]

[0164]

[0165]

[0166] In the formula, Binary variables representing charging and discharging states, respectively. n represents the energy storage type, which can be any one of electrical energy e, thermal energy h, and cold energy c. Respectively represent charging power and discharging power; Z n Integer variable for energy storage system planning module; They represent the maximum charging power and the maximum discharging power respectively.

[0167] In a specific embodiment, the constraint condition construction unit 02 is further used for:

[0168] The third constraint is determined using the energy storage system model:

[0169]

[0170]

[0171]

[0172] In the formula, Respectively represent the charge state at time t and t-1; Indicates the maximum capacity of a single module; Respectively represent the initial and final charge states; η ch,n , η dis,n They respectively represent the efficiency of charging and discharging of the energy storage system.

[0173] In a specific embodiment, the constraint condition construction unit 02 is further used for:

[0174] Establish the power balance formula between demand and supply of multi-energy complementary parks:

[0175]

[0176]

[0177]

[0178] In the formula, the subscripts s and t represent the time t of the sth typical day; the subscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; the subscripts ch and dis represent charging and discharging respectively; P is the charging and discharging power of the energy storage device; L is the output power of the multi-energy device; LOAD represents the load power; L SHED Indicates load shedding power.

[0179] It is understandable that the multi-energy complementary park planning and design device provided in the embodiment of the present invention is used to execute the multi-energy complementary park planning and design method as described in any of the above embodiments. This embodiment can effectively measure the park system risk by establishing an objective function with the goal of minimizing the total cost and considering the influence of conditional risk factors, so as to formulate a reasonable, reliable and risk-avoiding planning scheme, so as to provide scientific and objective guidance for the planning and design of regional multi-energy complementary parks, which is conducive to promoting the development of park energy Internet.

[0180] See also Figure 6 , a certain embodiment of the present invention provides a terminal device, including:

[0181] one or more processors;

[0182] A memory, coupled to the processor, for storing one or more programs;

[0183] When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-energy complementary park planning and design method as described above.

[0184] The processor is used to control the overall operation of the terminal device to complete all or part of the steps of the above-mentioned multi-energy complementary park planning and design method. The memory is used to store various types of data to support the operation of the terminal device, and these data may include, for example, instructions for any application or method used to operate on the terminal device, as well as application-related data. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0185] In an exemplary embodiment, the terminal device can be implemented by one or more application-specific integrated circuits (Application Specific Integrated Circuit, ASC), digital signal processors (Digital Signal Processor, DSP), digital signal processing devices (Digital Signal Processing Device, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field Programmable Gate Array, FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the multi-energy complementary park planning and design method described in any of the above embodiments and achieve the same technical effect as the above method.

[0186] In another exemplary embodiment, a computer-readable storage medium including a computer program is also provided, and when the computer program is executed by a processor, the steps of the multi-energy complementary park planning and design method as described in any of the above embodiments are implemented. For example, the computer-readable storage medium can be the above-mentioned memory including the computer program, and the above-mentioned computer program can be executed by the processor of the terminal device to complete the multi-energy complementary park planning and design method as described in any of the above embodiments, and achieve the same technical effect as the above method.

[0187] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A multi-energy complementary park planning and design method, characterized in that: include: Construct an objective function based on the park planning cost and conditional risk value; Constructing constraint conditions and solving the objective function under the constraint conditions; Use the solution results to design a multi-energy complementary park planning scheme; The objective function is constructed based on the park planning cost and conditional risk value, including: The objective function is constructed using investment cost, transaction cost, maintenance cost, load shedding cost and conditional risk value: Where, IC, TC s , MC s , LC s They represent investment cost, transaction cost on a typical day, maintenance cost on a typical day, and load shedding cost on a typical day, respectively; β and α represent risk index and credibility, respectively; CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; p s represents the probability of different typical days; [·] + represents the part ≥0; The construction constraints include: Determine the equipment energy conversion model: According to the equipment energy conversion model, the first constraint condition is determined: In the formula, the superscripts i and j represent the jth capacity selection of the ith equipment; the superscripts s and t represent the time t of the sth typical day; the superscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; P is the input power of the equipment; is the energy conversion coefficient of the equipment, the subscript he indicates that electrical energy is converted into thermal energy, L is the output power of the equipment; LOAD indicates the load power; L SHED represents the load shedding power; u is a binary variable.

2. The multi-energy complementary park planning and design method according to claim 1 is characterized in that: The construction constraints also include: The second constraint is determined using the energy storage system model: In the formula, Binary variables representing charging and discharging states, respectively. n represents the energy storage type, which can be any one of electrical energy e, thermal energy h, and cold energy c. Respectively represent charging power and discharging power; Z n Integer variable for energy storage system planning module; They represent the maximum charging power and the maximum discharging power respectively.

3. The multi-energy complementary park planning and design method according to claim 2 is characterized in that: The construction constraints also include: The third constraint is determined using the energy storage system model: In the formula, Respectively represent the charge state at time t and t-1; Indicates the maximum capacity of a single module; Respectively represent the initial and final charge states; η ch,n , η dis,n They respectively represent the efficiency of charging and discharging of the energy storage system.

4. The multi-energy complementary park planning and design method according to claim 3 is characterized in that: The construction constraints also include: Establish the power balance formula between demand and supply of multi-energy complementary parks: In the formula, the subscripts s and t represent the time t of the sth typical day; the subscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; the subscripts ch and dis represent charging and discharging respectively; P is the charging and discharging power of the energy storage device; L is the output power of the multi-energy device; LOAD represents the load power; L SHED Indicates load shedding power.

5. A multi-energy complementary park planning and design device, characterized in that: include: An objective function construction unit, used to construct an objective function based on the park planning cost and conditional risk value; A constraint condition construction unit, used for constructing constraint conditions and solving the objective function under the constraint conditions; Planning scheme design unit, used to design a multi-energy complementary park planning scheme using the solution results; Wherein, the objective function construction unit is also used for: The objective function is constructed using investment cost, transaction cost, maintenance cost, load shedding cost and conditional risk value: Where, IC, TC s , MC s , LC s They represent investment cost, transaction cost on a typical day, maintenance cost on a typical day, and load shedding cost on a typical day, respectively; β and α represent risk index and credibility, respectively; CVaR α Represents the weighted conditional value at risk for different typical days; VaR α Indicates the calculation of CVaR α Auxiliary variables; p s represents the probability of different typical days; [·] + represents the part ≥0; The construction constraints include: Determine the equipment energy conversion model: According to the equipment energy conversion model, the first constraint condition is determined: In the formula, the superscripts i and j represent the jth capacity selection of the ith equipment; the superscripts s and t represent the time t of the sth typical day; the superscripts e, g, h, and c represent electricity, natural gas, heat, and cold energy respectively; P is the input power of the equipment; is the energy conversion coefficient of the equipment, the subscript he indicates that electrical energy is converted into thermal energy, L is the output power of the equipment; LOAD indicates the load power; L SHED represents the load shedding power; u is a binary variable.

6. A terminal device, characterized in that: include: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-energy complementary park planning and design method as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the multi-energy complementary park planning and design method as described in any one of claims 1 to 4 is implemented.

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