Power market panoramic analogue simulation method considering multiple subjects and related device

Abstract

The invention discloses a power market panoramic analogue simulation method considering multiple subjects and a related device. The method comprises the following steps: respectively calculating operation utility parameters of an offshore wind power subject, a natural gas power generation subject and a demand side response subject; according to the operation utility parameter of each main body, constructing a target function with the operation cost minimization as a target, and according to the operation characteristic of each main body, constructing the operation constraint and the system coupling operation constraint of each main body, and obtaining a market clearing model; and solving the market clearing model to obtain a simulation scheduling result of each main body. According to the method, differential operation characteristics of multiple types of resources such as offshore wind power, natural gas power generation and demand side response are comprehensively considered, the flexible adjustment capability of power generation side and demand side scheduling resources is fully excavated, and a multi-subject scheduling result under a power market panoramic simulation result is predicted in advance; space-time complementation among different types of resources is realized to the greatest extent, and the reliability of a simulation scheduling result is improved.

Description

Technical Field

[0001] The present application relates to the technical field of power market simulation, and in particular to a method and related apparatus for panoramic simulation of a power market taking into account multiple subjects. Background Art

[0002] Offshore wind power output exhibits significant random fluctuations and anti-peak characteristics, posing significant challenges to the supply-demand balance and security and stability of the power system. As the proportion of renewable energy generation continues to increase, flexible regulation resources on the generation side, such as natural gas-fired power generation, and on the user side, such as demand-side response, will gradually become key means of accommodating offshore wind power during off-peak loads and providing guaranteed power during peak loads. With renewable energy fully participating in power market clearing, comprehensive power market simulations, encompassing operational parameter declaration simulations, market clearing simulation calculations, and dispatch result simulation evaluations, are necessary to predict market clearing outcomes in advance, identify operational risks for the power system and market participants, and optimize operational boundaries and dispatch decisions to better balance power system supply and demand and ensure the high-proportion absorption of large-scale offshore wind power. However, existing power market simulation methods primarily focus on the market clearing phase, failing to cover the entire power market operation process. They also fail to consider the coordinated operation and coupled modeling of multiple dispatching entities, such as offshore wind power, natural gas-fired power generation, and demand-side response, resulting in technical challenges such as low reliability of simulation results. Summary of the Invention

[0003] In order to solve the above problems, the present application provides a method and related devices for panoramic simulation of the electricity market taking into account multiple subjects.

[0004] In view of this, the first aspect of the present application provides a method for panoramic simulation of a power market taking into account multiple agents, including:

[0005] Calculate the operating utility parameters of offshore wind power entities, natural gas power generation entities, and demand-side response entities respectively;

[0006] Based on the operating utility parameters of each entity, an objective function with the goal of minimizing operating costs is constructed. Based on the operating characteristics of each entity, the operating constraints of each entity and the system coupling operating constraints are constructed to obtain a market clearing model.

[0007] The market clearing model is solved to obtain simulation scheduling results of offshore wind power entities, natural gas power generation entities, and demand-side response entities.

[0008] Optionally, the objective function is:

[0009]

[0010] Where T represents the total number of time periods considered in the market clearing model, Indicates the total number of offshore wind power entities, Indicates the total number of natural gas power generation entities, Indicates the total number of demand-side response entities; represents the security utility parameter of the w-th offshore wind power entity, represents the guaranteed output variable of the w-th offshore wind power entity in period t, represents the competitive utility parameter of the w-th offshore wind power entity, represents the competitive output variable of the w-th offshore wind power entity in time period t; represents the utility parameter of the sth segment of the gth natural gas power generation entity, represents the output variable of the g-th natural gas power generation entity in the s-th segment of time period t, represents the startup cost of the g-th natural gas power generation entity, Indicates the total number of segments of the operating utility parameters of the natural gas power generation entity; represents the operating utility parameter of the kth segment of the dth demand-side response entity, represents the k-th demand response output variable of the d-th demand side response in time period t, Indicates the total number of segments of the declared parameters of the demand-side response subject.

[0011] Optionally, the constraints include:

[0012] Operational constraints of offshore wind power entities:

[0013]

[0014]

[0015] Where, represents the predicted output of the w-th offshore wind power entity in time period t, represents the guaranteed power generation ratio of the wth offshore wind power entity;

[0016] Operational constraints of natural gas power generation entities:

[0017]

[0018]

[0019]

[0020]

[0021]

[0022] represents the overall output of the g-th natural gas power generation entity; represents the start / stop state variable of the g-th natural gas power generation entity in time period t, 1 represents start and 0 represents stop; and They represent the maximum technical output and minimum technical output of the g-th natural gas power generation entity respectively; The duration of the startup process is UD1, which represents the duration of the cold startup process, UD2, which represents the duration of the warm startup process, and UD3, which represents the duration of the hot startup process. The duration of the shutdown process; and 0-1 variables indicating whether the natural gas power generation entity is switched to the start state or the shutdown state, Represents the startup curve of time period tt, Represents the shutdown curve of time period tt; superscripts 1, 2, and 3 represent cold state, warm state, and hot state respectively;

[0023] Coupling constraints of the start-stop state variables and start-stop switching variables of the natural gas power generation entity:

[0024]

[0025]

[0026]

[0027] Ramping constraints of natural gas power generation entities:

[0028]

[0029]

[0030] in, Indicates the maximum ramp rate of the natural gas power generation entity g, Indicates the maximum ramp-down rate of the natural gas power generation entity g;

[0031] Constraints on the start and stop time of natural gas power generation entities:

[0032]

[0033]

[0034] in, and are the minimum continuous start-up time and minimum continuous shutdown time of the g-th natural gas power generation entity respectively; is the time that the g-th natural gas power generation entity has been continuously started in period t, Indicates the time that the g-th natural gas power generation entity has been continuously shut down in time period t;

[0035] Operational constraints of demand-side response entities:

[0036]

[0037]

[0038] in, represents the overall output of the dth demand-side response entity in time period t, Indicates the state of the demand-side response subject d participating in the demand response in period t, Express participation, Indicates non-participation; It represents the maximum response capacity of the demand-side response entity d that can win the bid in time period t;

[0039] Duration constraints for demand-side response entities to participate in demand response:

[0040]

[0041] in, The minimum duration for the demand-side response subject d to participate in demand response; The maximum duration for the demand-side response subject d to participate in demand response; is the duration of the demand-side response subject d in period t;

[0042] System load balance constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response:

[0043]

[0044] Among them, N T Indicates the total number of tie lines, T j,t N represents the planned power of tie line j in time period t; L represents the total number of load nodes, represents the load of the lth node in time period t;

[0045] Transmission section power flow constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response:

[0046]

[0047] in, 、 is the power flow transmission limit of transmission section s, is the generator output power transfer distribution factor of the node w where the offshore wind power main body is located on the section s, is the generator output power transfer distribution factor of the node where the natural gas power generation entity g is located on the section s, is the load power transfer distribution factor of load node l to section s; is the tie line output power transfer distribution factor for the section s at the node where the tie line j is located.

[0048] Optionally, the method further includes:

[0049] Constructing a dispatch utility evaluation model for an offshore wind power entity, a natural gas power generation entity, and a demand-side response entity, inputting the simulated dispatch results of each entity into the dispatch utility evaluation model of the corresponding entity for calculation, and obtaining a dispatch utility evaluation value for each entity;

[0050] The operation utility parameters of each subject are adjusted according to the dispatch utility evaluation value of each subject.

[0051] Optionally, the scheduling utility evaluation model for offshore wind power entities is:

[0052]

[0053] in, represents the dispatch utility evaluation value of the offshore wind power entity w, T represents the total number of time periods considered by the market clearing model, represents the marginal clearing utility of offshore wind power entity w in period t, represents the security utility parameter of the offshore wind power entity w, represents the guaranteed power generation ratio of the offshore wind power entity w, represents the predicted output of offshore wind power entity w in time period t, represents the competitive utility parameter of the offshore wind power entity w, It represents the competitive output value of the offshore wind power entity w in the scheduling result during time period t.

[0054] Optionally, the dispatch utility evaluation model for natural gas power generation entities is:

[0055]

[0056] in, represents the utility evaluation value of the natural gas power generation entity g, T represents the total number of time periods considered by the market clearing model, represents the overall output of the g-th natural gas power generation entity, represents the marginal clearing utility of natural gas power generation entity g in period t, represents the utility parameter of the sth segment of the natural gas power generation entity g, It represents the output value of the natural gas power generation entity g in the sth segment of time period t.

[0057] Optionally, the dispatch utility evaluation model of the demand-side response entity is:

[0058]

[0059] in, represents the utility evaluation value of the demand-side response subject d, T represents the total number of time periods considered in the market clearing model, represents the overall output of the demand-side response entity d in period t, represents the marginal clearing utility of the demand-side responding entity d in period t, Indicates the total number of segments of the declared parameters of the demand-side response subject. represents the operating utility parameter of the kth segment of the demand-side response entity d, It represents the output value of the dispatch result executed by the demand-side response entity d in the kth segment of time period t.

[0060] The second aspect of the present application provides a panoramic simulation system for a power market taking into account multiple agents, including:

[0061] A calculation unit, used to respectively calculate the operating utility parameters of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity;

[0062] A model building unit is used to build an objective function with the goal of minimizing operating costs based on the operating utility parameters of each entity, and to build the operating constraints of each entity and the system coupling operating constraints based on the operating characteristics of each entity, thereby obtaining a market clearing model;

[0063] The model solving unit is used to solve the market clearing model to obtain simulation scheduling results of offshore wind power entities, natural gas power generation entities and demand-side response entities.

[0064] A third aspect of the present application provides an electronic device, the device comprising a processor and a memory;

[0065] The memory is used to store program code and transmit the program code to the processor;

[0066] The processor is used to execute any one of the methods for panoramic simulation of a power market considering multiple agents described in the first aspect according to the instructions in the program code.

[0067] In a fourth aspect, the present application provides a computer-readable storage medium for storing program code. When the program code is executed by a processor, the method for panoramic simulation of a power market considering multiple subjects described in any one of the first aspects is implemented.

[0068] It can be seen from the above technical solutions that this application has the following advantages:

[0069] The present application provides a method for panoramic simulation of the electricity market taking into account multiple subjects. By comprehensively considering the differentiated operating characteristics of multiple types of resources such as offshore wind power, natural gas power generation, and demand-side response, it fully taps the flexible adjustment capabilities of the power generation and demand-side dispatching resources, and predicts the multi-subject dispatching results under the panoramic simulation results of the electricity market in advance. It maximizes the temporal and spatial complementarity between different types of resources and improves the reliability of the simulation dispatching results. A multi-operation coupling constraint market clearing model is constructed, which takes into account the security characteristics and competitiveness of offshore wind power, covers the operating characteristics of natural gas generators in cold, warm, and hot start-up and shutdown states, simulates the load response capability and duration of demand-side response resources, and realizes the coordinated dispatching of multiple market subjects through load balancing and transmission section flow coupling constraints. It can reduce the impact of offshore wind power output uncertainty on the supply and demand of the power system and improve the system's operating efficiency and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0071] Figure 1 A schematic flow chart of a method for panoramic simulation of a power market taking into account multiple agents provided in an embodiment of the present application;

[0072] Figure 2 A schematic diagram of the structure of a market clearing model with multiple running constraints coupled according to an embodiment of the present application;

[0073] Figure 3 Another flowchart of a method for panoramic simulation of a power market considering multiple agents provided in an embodiment of the present application;

[0074] Figure 4 A schematic diagram of the structure of a multi-agent scheduling result evaluation and decision optimization model provided in an embodiment of the present application;

[0075] Figure 5 A structural diagram of a panoramic simulation system for a power market taking into account multiple agents provided in an embodiment of the present application. DETAILED DESCRIPTION

[0076] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 those skilled in the art without creative work are within the scope of protection of this application.

[0077] For easier understanding, please refer to Figure 1 The embodiment of the present application provides a method for simulating a panoramic view of a power market taking into account multiple agents, including:

[0078] Step 110: Calculate the operating utility parameters of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity respectively;

[0079] The corresponding operational utility parameters are constructed from the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity. The operational utility parameters of the offshore wind power entity are divided into guarantee utility parameters and competitive utility parameters:

[0080]

[0081]

[0082] in, represents the security utility parameter of the w-th offshore wind power entity, represents the competitive utility parameter of the w-th offshore wind power entity, represents the marginal operating cost of the w-th offshore wind power entity, It represents the guaranteed operation benefit of the w-th offshore wind power entity.

[0083] Taking into account factors such as fuel prices and variable power generation costs, the rated capacity is divided equally to generate the segmented operation utility parameters of the natural gas power generation entity:

[0084]

[0085] in, represents the utility parameter of the sth segment of the gth natural gas power generation entity, represents the rated capacity of the g-th natural gas power generation entity, a represents the fuel consumed per MW of natural gas generator set, R represents the unit fuel cost, Indicates the total number of segments of the operating utility parameters of the natural gas power generation entity.

[0086] Considering the scenario of tight power supply, the difference between the upper limit of parameter declaration and the upper limit of clearing result is used as the segment interval, which is equally divided to generate the operating utility parameters of the demand-side response entity:

[0087]

[0088] in, represents the operating utility parameter of the dth demand-side response entity in the kth segment, Indicates the upper limit value of parameter declaration. Indicates the upper limit of the clearing result. Indicates the total number of segments of the parameters declared by the demand-side response entity.

[0089] Step 120: construct an objective function with the goal of minimizing operating costs based on the operating utility parameters of each entity, and construct the operating constraints of each entity and the system coupling operating constraints based on the operating characteristics of each entity to obtain a market clearing model;

[0090] Please refer to Figure 2 The embodiment of this application considers the operating characteristics of offshore wind power entities, natural gas power generation entities, and demand-side response entities, and constructs an objective function with the minimum sum of offshore wind power generation costs, natural gas power generation costs, and demand-side response operating costs as the optimization goal. Based on the operating characteristics of each entity, the operating constraints of each entity and the system coupling operating constraints are constructed to obtain a market clearing model with multiple operating constraints coupled. The objective function is:

[0091]

[0092] Where T represents the total number of time periods considered in the market clearing model, Indicates the total number of offshore wind power entities, Indicates the total number of natural gas power generation entities, Indicates the total number of demand-side response entities; represents the security utility parameter of the w-th offshore wind power entity, represents the guaranteed output variable of the w-th offshore wind power entity, represents the competitive utility parameter of the w-th offshore wind power entity, represents the competitive output variable of the w-th offshore wind power entity; represents the utility parameter of the sth segment of the gth natural gas power generation entity, represents the output variable of the g-th natural gas power generation entity in the s-th segment of time period t, represents the startup cost of the g-th natural gas power generation entity, Indicates the total number of segments of the operating utility parameters of the natural gas power generation entity; represents the operating utility parameter of the kth segment of the dth demand-side response entity, represents the k-th demand response output variable of the d-th demand side response in time period t, Indicates the total number of segments of the declared parameters of the demand-side response subject.

[0093] The operational constraints of offshore wind power entities are constructed using an interval optimization model. The guaranteed output is determined according to a fixed ratio, and the competitive output is optimized and solved by the market clearing model. The corresponding constraints are as follows:

[0094]

[0095]

[0096] Where, represents the predicted output of the w-th offshore wind power entity in time period t, represents the guaranteed power generation ratio of the wth offshore wind power entity;

[0097] Establish the operating constraints of the natural gas power generation entity. The overall output of the natural gas power generation entity should be equal to the sum of the segmented outputs. Its output should not exceed its maximum output upper limit constraint and should not be lower than its minimum output. In addition, it must meet specific start-up and shutdown curves during the start-up and shutdown process:

[0098]

[0099]

[0100]

[0101]

[0102]

[0103] represents the overall output of the g-th natural gas power generation entity; represents the start / stop state variable of the g-th natural gas power generation entity in time period t, 1 represents start and 0 represents stop; and They represent the maximum technical output and minimum technical output of the g-th natural gas power generation entity respectively; The duration of the startup process is UD1, which represents the duration of the cold startup process, UD2, which represents the duration of the warm startup process, and UD3, which represents the duration of the hot startup process. The duration of the shutdown process; and 0-1 variables indicating whether the natural gas power generation entity is switched to the start state or the shutdown state, Represents the startup curve of time period tt, Indicates the shutdown curve of time period tt; superscripts 1, 2, 3 indicate cold state, warm state, and hot state;

[0104] The start-stop state variables and start-stop switching variables of the natural gas power generation entity must also satisfy the following coupling relationship:

[0105]

[0106]

[0107]

[0108] The natural gas power generation entity must meet the ramp rate requirements when climbing up or down. The corresponding ramp constraints can be described as:

[0109]

[0110]

[0111] in, Indicates the maximum ramp rate of the natural gas power generation entity g, Indicates the maximum ramp-down rate of the natural gas power generation entity g;

[0112] Due to the physical properties and actual operation requirements of natural gas generator sets, natural gas generator sets are required to meet the minimum continuous start / stop time. The start / stop time constraints of natural gas power generation entities are:

[0113]

[0114]

[0115] in, and are the minimum continuous start-up time and minimum continuous shutdown time of the g-th natural gas power generation entity respectively; is the time that the g-th natural gas power generation entity has been continuously started in period t, Indicates the time that the g-th natural gas power generation entity has been shut down continuously in period t, and the start-stop state variable can be used To express:

[0116]

[0117]

[0118] Establish the operational constraints of the demand-side response entity. The overall output of the demand-side response is equal to the sum of the segmented outputs and cannot exceed the upper limit of the declared responsive capacity. The specific constraints are as follows:

[0119]

[0120]

[0121] in, represents the overall output of the dth demand-side response entity in time period t, Indicates the state of the demand-side response subject d participating in the demand response in period t, Express participation, Indicates non-participation; It represents the maximum response capacity of the demand-side response entity d that can win the bid in time period t;

[0122] Demand-side response must also meet the minimum duration and maximum duration constraints. The duration constraints for demand-side response entities to participate in demand response are:

[0123]

[0124] in, The minimum duration for the demand-side response subject d to participate in demand response; The maximum duration for the demand-side response subject d to participate in demand response; is the time that the demand-side response subject d has lasted in period t, and the available state variables To express:

[0125]

[0126] Constructing system load balancing constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response:

[0127]

[0128] Among them, N T Indicates the total number of tie lines, T j,t N represents the planned power of tie line j in period t; L represents the total number of load nodes, represents the load of the lth node in time period t;

[0129] Constructing transmission section power flow constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response:

[0130]

[0131] in, 、 is the power flow transmission limit of transmission section s, is the generator output power transfer distribution factor of the node w where the offshore wind power main body is located on the section s, is the generator output power transfer distribution factor of the node where the natural gas power generation entity g is located on the section s, is the load power transfer distribution factor of load node l to section s; is the tie line output power transfer distribution factor for the section s at the node where the tie line j is located.

[0132] Step 130: Solve the market clearing model to obtain simulation scheduling results of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity.

[0133] By solving the market-clearing model, we obtain simulated dispatch results for offshore wind power entities, natural gas power generation entities, and demand-side response entities at each time period. These results include each entity's marginal clearing utility and winning bid output. Based on these simulated dispatch results, we can make dispatch decisions to ensure a high proportion of large-scale offshore wind power is consumed.

[0134] This application comprehensively considers the differentiated operating characteristics of multiple types of resources such as offshore wind power, natural gas power generation, and demand-side response, fully taps the flexible adjustment capabilities of the power generation side and demand-side dispatching resources, and predicts the multi-agent dispatching results under the panoramic simulation results of the power market in advance, so as to maximize the temporal and spatial complementarity between different types of resources. A multi-agent operation utility parameter declaration model is constructed to ensure that the operation utility parameters fully cover the marginal operation costs and provide flexible parameter declaration strategies for multiple subjects. A multi-operation coupling constraint market clearing model is constructed, which takes into account the security characteristics and competitiveness of offshore wind power, covers the operating characteristics of natural gas power generation units in cold, warm, and hot start-up and shutdown states, simulates the load response capability and duration of demand-side response resources, and realizes the coordinated dispatch of multiple market entities through load balancing and transmission section flow coupling constraints, which can reduce the impact of offshore wind power output uncertainty on the supply and demand of the power system and improve the system's operating efficiency and reliability.

[0135] Please refer to Figure 3 The present application also provides another embodiment of a method for panoramic simulation of a power market considering multiple agents, the method comprising:

[0136] Step 210: Calculate the operating utility parameters of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity respectively;

[0137] Step 220: construct an objective function with the goal of minimizing operating costs based on the operating utility parameters of each entity, and construct operating constraints of each entity and system coupling operating constraints based on the operating characteristics of each entity to obtain a market clearing model;

[0138] Step 230: Solve the market clearing model to obtain simulation scheduling results for the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity;

[0139] The specific contents of steps 210 to 230 are consistent with the specific contents of steps 110 to 130 in the aforementioned method embodiment, and will not be repeated here.

[0140] Step 240: Construct a dispatch utility evaluation model for the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity. Input the simulated dispatch results of each entity into the dispatch utility evaluation model of the corresponding entity for calculation to obtain a dispatch utility evaluation value for each entity. Adjust the operating utility parameters of each entity based on the dispatch utility evaluation value of each entity.

[0141] Please refer to Figure 4 The embodiment of the present application constructs a scheduling utility evaluation model for offshore wind power entities, natural gas power generation entities, and demand-side response entities, inputs the simulated scheduling results of each entity into the scheduling utility evaluation model of the corresponding entity for calculation, and obtains the scheduling utility evaluation value of each entity.

[0142] Among them, the scheduling utility evaluation model of offshore wind power entities is:

[0143]

[0144] in, represents the dispatch utility evaluation value of the offshore wind power entity w, T represents the total number of time periods considered by the market clearing model, represents the marginal clearing utility of offshore wind power entity w in period t, represents the security utility parameter of the offshore wind power entity w, represents the competitive utility parameter of the offshore wind power entity w, It represents the competitive output value of the offshore wind power entity w in the scheduling result during time period t.

[0145] Based on the dispatch utility evaluation value of offshore wind power entities, a corresponding decision optimization model is constructed to adjust the operational utility parameters of offshore wind power entities:

[0146]

[0147]

[0148] in, represents the adjusted security utility parameter of the w-th offshore wind power entity, represents the adjusted competitive utility parameter of the w-th offshore wind power entity.

[0149] The dispatch utility evaluation model of natural gas power generation entities is:

[0150]

[0151] in, represents the utility evaluation value of the natural gas power generation entity g, T represents the total number of time periods considered by the market clearing model, represents the marginal clearing utility of natural gas power generation entity g in period t, represents the utility parameter of the sth segment of the gth natural gas power generation entity, It represents the output value of the natural gas power generation entity g in the sth segment of time period t.

[0152] Based on the dispatch utility evaluation value of the natural gas power generation entity, a corresponding decision optimization model is constructed to adjust the operating utility parameters of the natural gas power generation entity:

[0153]

[0154] in, It represents the operating utility parameter of the g-th natural gas power generation entity after the s-th segment adjustment.

[0155] The dispatch utility evaluation model of the demand-side response entity is:

[0156]

[0157] in, represents the utility evaluation value of the demand-side response subject d, T represents the total number of time periods considered in the market clearing model, represents the overall output of the demand-side response entity d in period t, represents the marginal clearing utility of the demand-side responding entity d in period t, Indicates the total number of segments of the declared parameters of the demand-side response subject. represents the operating utility parameter of the kth segment of the demand-side response entity d, It represents the output value of the demand-side response entity d in the kth segment of time period t;

[0158] Based on the dispatch utility evaluation value of the demand-side response subject, a corresponding decision optimization model is constructed to adjust the operation utility parameters of the demand-side response subject:

[0159]

[0160] in, It represents the operational utility parameter of the kth segment after adjustment of the dth demand-side response.

[0161] This application comprehensively considers the differentiated operating characteristics of multiple types of resources such as offshore wind power, natural gas power generation, and demand-side response, fully taps the flexible adjustment capabilities of the power generation and demand-side dispatching resources, and predicts the multi-agent dispatching results under the panoramic simulation results of the power market in advance, so as to maximize the temporal and spatial complementarity between different types of resources. A multi-operation coupling constraint market clearing model is constructed, which takes into account the security characteristics and competitiveness of offshore wind power, covers the operating characteristics of natural gas generators in different start-up and shutdown states of cold, warm, and hot, simulates the load response capability and duration of demand-side response resources, and realizes the coordinated dispatch of multiple market entities through load balancing and transmission section flow coupling constraints, which can reduce the impact of offshore wind power output uncertainty on the supply and demand of the power system and improve the system's operating efficiency and reliability. A multi-agent dispatching result evaluation and decision optimization model is constructed to provide a utility evaluation tool for the simulated dispatching results of offshore wind power entities, natural gas power generation entities, and demand-side response entities, and provide auxiliary decision-making for adjusting the entity's declared parameters.

[0162] Please refer to Figure 5 The embodiment of the present application further provides a panoramic simulation system for a power market taking into account multiple agents, including:

[0163] A calculation unit 510 is used to calculate the operating utility parameters of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity respectively;

[0164] A model building unit 520 is used to build an objective function with the goal of minimizing operating costs based on the operating utility parameters of each entity, and to build operating constraints of each entity and system coupling operating constraints based on the operating characteristics of each entity to obtain a market clearing model;

[0165] The model solving unit 530 is used to solve the market clearing model and obtain the simulation scheduling results of the offshore wind power entity, the natural gas power generation entity and the demand-side response entity.

[0166] As a further improvement, the system further includes:

[0167] The utility evaluation and optimization unit is used to construct a dispatch utility evaluation model for the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity. The simulated dispatch results of each entity are input into the dispatch utility evaluation model of the corresponding entity for calculation to obtain the dispatch utility evaluation value of each entity.

[0168] The operation utility parameters of each entity are adjusted according to the dispatch utility evaluation value of each entity.

[0169] This application comprehensively considers the differentiated operating characteristics of multiple types of resources such as offshore wind power, natural gas power generation, and demand-side response, fully taps the flexible adjustment capabilities of the power generation and demand-side dispatching resources, and predicts the multi-agent dispatching results under the panoramic simulation results of the power market in advance, so as to maximize the temporal and spatial complementarity between different types of resources. A multi-operation coupling constraint market clearing model is constructed, which takes into account the security characteristics and competitiveness of offshore wind power, covers the operating characteristics of natural gas generators in different start-up and shutdown states of cold, warm, and hot, simulates the load response capability and duration of demand-side response resources, and realizes the coordinated dispatch of multiple market entities through load balancing and transmission section flow coupling constraints, which can reduce the impact of offshore wind power output uncertainty on the supply and demand of the power system and improve the system's operating efficiency and reliability. A multi-agent dispatching result evaluation and decision optimization model is constructed to provide a utility evaluation tool for the simulated dispatching results of offshore wind power entities, natural gas power generation entities, and demand-side response entities, and provide auxiliary decision-making for adjusting the entity's declared parameters.

[0170] An embodiment of the present application further provides an electronic device, the device including a processor and a memory;

[0171] The memory is used to store program codes and transmit the program codes to the processor;

[0172] The processor is used to execute the panoramic simulation method of the power market considering multiple agents in the aforementioned method embodiment according to the instructions in the program code.

[0173] An embodiment of the present application also provides a computer-readable storage medium, which is used to store program code. When the program code is executed by a processor, it implements the panoramic simulation method of the electricity market considering multiple subjects in the aforementioned method embodiment.

[0174] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0175] In the specification of this application and the above-mentioned drawings, the terms "first," "second," "third," "fourth," etc. (if any) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or elements is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not explicitly listed or inherent to such process, method, product, or apparatus.

[0176] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or plural.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0178] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0179] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0180] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the method described in each embodiment of the present application through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name: Read-Only Memory, English abbreviation: ROM), random access memory (full name: Random Access Memory, English abbreviation: RAM), disk or optical disk, and other media that can store program code.

[0181] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A panoramic simulation method of the power market considering multiple agents, characterized in that: include: Calculate the operating utility parameters of offshore wind power entities, natural gas power generation entities, and demand-side response entities respectively; Based on the operating utility parameters of each entity, an objective function with the goal of minimizing operating costs is constructed. Based on the operating characteristics of each entity, the operating constraints of each entity and the system coupling operating constraints are constructed to obtain a market clearing model. The market clearing model is solved to obtain simulation scheduling results of offshore wind power entities, natural gas power generation entities, and demand-side response entities.

2. The method for panoramic simulation of the power market considering multiple agents according to claim 1 is characterized in that: The objective function is: Where T represents the total number of time periods considered in the market clearing model, Indicates the total number of offshore wind power entities, Indicates the total number of natural gas power generation entities, Indicates the total number of demand-side response entities; represents the security utility parameter of the w-th offshore wind power entity, represents the guaranteed output variable of the w-th offshore wind power entity in period t, represents the competitive utility parameter of the w-th offshore wind power entity, represents the competitive output variable of the w-th offshore wind power entity in time period t; represents the utility parameter of the sth segment of the gth natural gas power generation entity, represents the output variable of the g-th natural gas power generation entity in the s-th segment of time period t, represents the startup cost of the g-th natural gas power generation entity, Indicates the total number of segments of the operating utility parameters of the natural gas power generation entity; represents the operating utility parameter of the kth segment of the dth demand-side response entity, represents the k-th demand response output variable of the d-th demand side response in time period t, Indicates the total number of segments of the declared parameters of the demand-side response subject.

3. The method for panoramic simulation of the power market considering multiple agents according to claim 2 is characterized in that: The constraints include: Operational constraints of offshore wind power entities: Where, represents the predicted output of the w-th offshore wind power entity in time period t, represents the guaranteed power generation ratio of the wth offshore wind power entity; Operational constraints of natural gas power generation entities: represents the overall output of the g-th natural gas power generation entity; represents the start / stop state variable of the g-th natural gas power generation entity in time period t, 1 represents start and 0 represents stop; and They represent the maximum technical output and minimum technical output of the g-th natural gas power generation entity respectively; The duration of the startup process is UD1, which represents the duration of the cold startup process, UD2, which represents the duration of the warm startup process, and UD3, which represents the duration of the hot startup process. The duration of the shutdown process; and 0-1 variables indicating whether the natural gas power generation entity is switched to the start state or the shutdown state, Represents the startup curve of time period tt, Represents the shutdown curve of time period tt; superscripts 1, 2, and 3 represent cold state, warm state, and hot state respectively; Coupling constraints of the start-stop state variables and start-stop switching variables of the natural gas power generation entity: Ramping constraints of natural gas power generation entities: in, Indicates the maximum ramp rate of the natural gas power generation entity g, Indicates the maximum ramp-down rate of the natural gas power generation entity g; Constraints on the start and stop time of natural gas power generation entities: in, and are the minimum continuous start-up time and minimum continuous shutdown time of the g-th natural gas power generation entity respectively; is the time that the g-th natural gas power generation entity has been continuously started in period t, Indicates the time that the g-th natural gas power generation entity has been continuously shut down in time period t; Operational constraints of demand-side response entities: in, represents the overall output of the dth demand-side response entity in time period t, Indicates the state of the demand-side response subject d participating in the demand response in period t, Express participation, Indicates non-participation; It represents the maximum response capacity of the demand-side response entity d that can win the bid in time period t; Duration constraints for demand-side response entities to participate in demand response: in, The minimum duration for the demand-side response subject d to participate in demand response; The maximum duration for the demand-side response subject d to participate in demand response; is the duration of the demand-side response subject d in period t; System load balance constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response: Among them, N T Indicates the total number of tie lines, T j,t N represents the planned power of tie line j in time period t; L represents the total number of load nodes, represents the load of the lth node in time period t; Transmission section power flow constraints for the coupled operation of offshore wind power, natural gas power generation, and demand-side response: in, 、 is the power flow transmission limit of transmission section s, is the generator output power transfer distribution factor of the node w where the offshore wind power main body is located on the section s, is the generator output power transfer distribution factor of the node where the natural gas power generation entity g is located on the section s, is the load power transfer distribution factor of load node l to section s; is the tie line output power transfer distribution factor for the section s at the node where the tie line j is located.

4. The method for panoramic simulation of the power market considering multiple agents according to claim 1 is characterized in that: The method further comprises: Constructing a dispatch utility evaluation model for an offshore wind power entity, a natural gas power generation entity, and a demand-side response entity, inputting the simulated dispatch results of each entity into the dispatch utility evaluation model of the corresponding entity for calculation, and obtaining a dispatch utility evaluation value for each entity; The operation utility parameters of each subject are adjusted according to the dispatch utility evaluation value of each subject.

5. The method for panoramic simulation of the power market considering multiple agents according to claim 4 is characterized in that: The scheduling utility evaluation model of offshore wind power entities is: in, represents the dispatch utility evaluation value of the offshore wind power entity w, T represents the total number of time periods considered by the market clearing model, represents the marginal clearing utility of offshore wind power entity w in period t, represents the security utility parameter of the offshore wind power entity w, represents the guaranteed power generation ratio of the offshore wind power entity w, represents the predicted output of offshore wind power entity w in time period t, represents the competitive utility parameter of the offshore wind power entity w, It represents the competitive output value of the offshore wind power entity w in the scheduling result during time period t.

6. The method for panoramic simulation of the power market considering multiple agents according to claim 4 is characterized in that: The dispatch utility evaluation model of natural gas power generation entities is: in, represents the utility evaluation value of the natural gas power generation entity g, T represents the total number of time periods considered by the market clearing model, represents the overall output of the g-th natural gas power generation entity, represents the marginal clearing utility of natural gas power generation entity g in period t, represents the utility parameter of the sth segment of the natural gas power generation entity g, It represents the output value of the natural gas power generation entity g in the sth segment of time period t.

7. The method for panoramic simulation of the power market considering multiple agents according to claim 4 is characterized in that: The dispatch utility evaluation model of the demand-side response entity is: in, represents the utility evaluation value of the demand-side response subject d, T represents the total number of time periods considered in the market clearing model, represents the overall output of the demand-side response entity d in period t, represents the marginal clearing utility of the demand-side responding entity d in period t, Indicates the total number of segments of the declared parameters of the demand-side response subject. represents the operating utility parameter of the kth segment of the demand-side response entity d, It represents the output value of the dispatch result executed by the demand-side response entity d in the kth segment of time period t.

8. A panoramic simulation system of the power market considering multiple agents, characterized by: include: A calculation unit, used to respectively calculate the operating utility parameters of the offshore wind power entity, the natural gas power generation entity, and the demand-side response entity; A model building unit is used to build an objective function with the goal of minimizing operating costs based on the operating utility parameters of each entity, and to build the operating constraints of each entity and the system coupling operating constraints based on the operating characteristics of each entity, thereby obtaining a market clearing model; The model solving unit is used to solve the market clearing model to obtain simulation scheduling results of offshore wind power entities, natural gas power generation entities and demand-side response entities.

9. An electronic device, characterized in that: The device includes a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the panoramic simulation method of the power market considering multiple agents according to any one of claims 1-7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store program code, and when the program code is executed by a processor, it implements the panoramic simulation method of the power market considering multiple agents as described in any one of claims 1-7.

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