A method for constructing a game decision framework for source-grid-load planning

Abstract

A method for constructing a source-grid-load planning game decision framework includes the following steps: Step 1) The power generation company proposes its own power site selection and capacity determination plan (X Gen ,N Gen ), and power generation quotation information #imgabs0# Step 2); the transmission company makes a decision to formulate a line upgrade plan to form a new grid structure; Step 3) the transmission company also determines the transmission rate #imgabs1# and sends the grid structure information (X Tra ,N Tra ) is passed to the power generation company, the transmission rate information is passed to the large power users, and the transmission network parameters (line length #imgabs2# line capacity #imgabs3# transmission flow constraints) are passed to the ISO; Step 4) The large power users are based on the transmission rate determined by the transmission company and the node marginal price SP calculated by the ISO pi Formulate power purchase and DG investment plan (X Use ,N Use ) and feeds back its purchased electricity information to the transmission company and ISO; Step 5) ISO transmits the node marginal electricity price information to the power generation company and large power users.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and in particular relates to a method for constructing a source-grid-load planning game decision-making framework. Background Art

[0002] The continuous advancement of electricity market reforms around the world has brought a series of opportunities and challenges to the development of the power industry. On the one hand, traditional transmission planning does not have the flexibility to adjust electricity price strategies in a timely manner according to user needs when calculating transmission utility; on the other hand, when constructing a planning model based on the overall perspective of the electricity market, the resource allocation capabilities of the power system can be fully improved. Therefore, the research focus of traditional planning methods is on how to solve problems such as new energy consumption and demand-side response in the system planning process. Although this method can improve the efficiency of system investment planning to a certain extent, it neither fully simulates the full-dimensional game decision-making process including ISO and source-grid-load planning entities, nor lacks the vitality of resource allocation. Therefore, the following problems still exist:

[0003] 1) In a mature electricity market, the utility of different entities (especially transmission companies) such as source, grid and load depends not only on the node electricity price, but also on the market operation mechanism (ISO decision, transmission organization, congestion and other factors). Therefore, this method of directly using the node marginal electricity price results as the decision-making information of each entity is often only for the decision of a single or part of the planning entities in planning. Therefore, the ISO decision considered also only involves its information interaction with some market entities (other market information is generally fixed). In fact, in a mature electricity market, the source, grid, load and ISO constitute a complete information interaction and game interaction relationship. The decision information provided by ISO includes not only the node electricity price but also the unit output and the unit utility rate parameters of the transmission company. In the game process, the update of the planning scheme of any investment entity of the source, grid and load will also lead to the change of the ISO decision boundary conditions. Therefore, only by establishing a full-dimensional decision-making framework including ISO can the accurate simulation of electricity market planning decisions be achieved;

[0004] 2) Traditional planning methods provide a relatively simplistic calculation of transmission company utility (simply calculating investment and operating rates or utility), essentially failing to consider the planned utility and rates of transmission companies from the perspective of the actual electricity market. In a mature electricity market, the utility of different entities (source, network, and load) (especially for transmission companies) depends not only on the node electricity price but also on uncertainties (ISO decisions, transmission organization, congestion, and other factors). Only by fully considering all market factors in the transmission company planning model can the planning results be guaranteed to effectively alleviate congestion, reduce node marginal electricity prices, and further improve the planning and investment efficiency of the entire power system.

[0005] Therefore, in this context, studying a dynamic game behavior that can comprehensively analyze the source-grid-load and ISO complete market elements has important theoretical and practical significance for achieving accurate simulation of power market planning decisions and improving the planning and investment efficiency of the entire power system. Summary of the Invention

[0006] The purpose of the present invention is to provide a source-grid-load multi-agent game planning method and a method for constructing a source-grid-load planning game decision-making framework that can achieve more accurate simulation of power market planning decisions.

[0007] The purpose of the present invention is achieved by adopting the following technical solutions:

[0008] A multi-agent game planning method for power generation, grid and load considering all dimensions of the power market includes the following steps:

[0009] Step 1: Introduce a transmission utility calculation method that considers the characteristics of transmission regulation and construct a transmission company planning model that considers monopoly regulation and market operation;

[0010] Step 2: Using the construction of new power sources and the commissioning of distributed power sources as decision variables, a source-grid-load planning model that considers multiple market players is constructed;

[0011] Step 3: Propose a source-grid-load planning game decision framework that considers the operation of the electricity market;

[0012] Step 4: Solve the Nash equilibrium and obtain the planning scheme of the final model.

[0013] In step 1, when introducing the transmission utility calculation method that takes into account the characteristics of transmission regulation and constructing the transmission company planning model, its objective function is composed of transmission service revenue and reliability costs, and the line operation rate is calculated based on the electricity price flow data on a line-by-line basis to ensure reasonable market guidance for transmission line planning.

[0014] The above objective function is specifically shown in formula (1):

[0015]

[0016] Where, is a vector set of planned transmission line projects, where ,L mT∈Ω mT Both are 0-1 variables, indicating whether the planned transmission line project is newly constructed; represents the planned expansion capacity set of the transmission company's lines; ,L mT∈Ω mT Indicates the expansion capacity of each planned line; Ω mT represents a collection of planned transmission line projects; is the transmission rate of the lth line; U Tra Total utility for the transmission company; Revenue from electricity transmission services to transmission companies; For operation and maintenance purposes; For operational utility; For communication and other services; is the reliability utility of line l in year t; ψ es Unit power outage loss; EENS l,t is the expected value of power shortage of line l in year t; Ω l is a collection of lines;

[0017] Among them, the operation and maintenance utility of the transmission service revenue of the transmission company Operational Utility Communication and other service utilities The solution formula is shown in formula (2):

[0018]

[0019] Where, is the maximum power flowing through line l in year t; is the capacity of line l; is the length of line l; Modeling and analyzing rates for transmission company unit capacity; is the operating rate per unit active power of the transmission company; σ m is the unit capacity transmission line operating rate; σ c is the rate for other services such as transmission line communication per unit length; the relevant parameters involved in the specific utility calculation are as follows σ m and σ c All are derived by ISO during the decision-making stage;

[0020] Constraints include new line investment constraints, branch line power flow constraints, and safety constraints;

[0021] (1) Constraints on the number of new lines

[0022]

[0023] (2) Branch flow constraints

[0024]

[0025] Where: P i.t and Q i.t are the active power and reactive power of node i at time t; U i.t and U j.tare the voltage amplitudes of nodes i and j at time t; G ij and B ij are the conductance and susceptance of branch ij respectively; θ ij is the phase angle difference between the voltages at nodes i and j;

[0026] (3) Safety constraints

[0027]

[0028] Where: U i.min and U i.max are the lower and upper limits of the voltage amplitude of node i at any typical time t; P ij.t and P ij.max are the transmission power of branch ij at any typical time t and its upper limit respectively.

[0029] In step 2, the power generation company selects the location and capacity of the new units in the power system planning. The objective function of its planning model is composed of the electricity sales utility and operating rate of the existing units, and the decision variables are the location and capacity of the new units.

[0030] In step 2, the objective function is as shown in formula (6);

[0031]

[0032] Where U Gen represents the total utility of the power generation company; is a vector set of planned generator project, where ,L mG∈Ω mG Both are 0-1 variables, indicating whether the generator project is newly built, Ω mG To plan the collection of power generation project; represents the planned capacity set of units of the power generation company, where ,L mG∈Ω mG Indicates the planned capacity of each power generation unit project; is the power generation quotation information; pn represents the node marginal electricity price at node n; The electricity sales utility of the power generation company's units; is the operating cost of the power generation company's unit; r is the discount rate; T is the year of project operation; is the electricity sales of node n at time t; Ω t is the set of typical peak load moments t in the Tth year; Ω T is the planning period set; Ω N is a set of nodes; is the unit operating rate of the generator set;

[0033] Constraints include the number of newly built generating units that can generate electricity and the upper and lower limits of the output of newly built generating units:

[0034] (1) Constraints on the number of new generating units that can generate electricity

[0035]

[0036] (2) Upper and lower output limits of newly built generator sets

[0037]

[0038] Where, The output of the newly built generators upper and lower bound constraints.

[0039] If the planning model is constructed for a large power user company, its objective function is shown as (9):

[0040]

[0041] Where, is a vector set for planning DG projects, where ,L mU∈Ω mU Both are 0-1 variables, indicating whether the planned DG project is newly constructed; A vector set representing the number of planned distributed generation units of large power users; ,L Represents the total distributed power construction capacity of each planning scheme; mU∈Ω mU Indicates the collection of planned new DG projects; The amount of electricity purchased by users from the main network; U Use Cost-effectiveness of electricity consumption for users; Cost utility of electricity purchase for users; Cost utility of purchasing electricity from the main grid for users; Revenue from distributed power generation; Cost effectiveness for equipment operation and maintenance; is the output of distributed power source c at node n at time t; Ω c is the set of distributed power sources c at n nodes; is the operation and maintenance rate per unit DG output;

[0042] Among them, the cost-effectiveness of electricity purchase by large electricity users The calculation formula of the main grid power purchase fee and distributed power generation income is shown in formula (10):

[0043]

[0044] Where, f n,t is the peak load of node n at time t during the planning period;

[0045] The constraints of the planning model for large power users mainly include the number of DG candidate nodes connected, DG penetration rate constraints, and DG output constraints;

[0046] (1) Limitation on the number of DG candidate nodes

[0047]

[0048] Where: N i.min and N i.max are the lower and upper limits of the number of DGs connected to the candidate node i, respectively;

[0049] (2) Node power balance constraints

[0050]

[0051] Where: q n,t is the amount of electricity purchased by node n at time t during the peak load period; is the power generation of the distributed generation at node n at time t; is the total load of n nodes at time t;

[0052] (3) DG output constraints

[0053]

[0054] Where: and are the lower and upper limits of DG output respectively;

[0055] (4) The new DG capacity of large power users is subject to the following equality constraints:

[0056]

[0057] In step 4, for the proposed dynamic game model, the Nash equilibrium is solved by an iterative search method. The specific solution steps are as follows:

[0058] 1) Input original data and parameters: Initialize the data required to establish the game model, including load information, parameters of the units to be newly built, parameters of the lines to be newly built, parameters of the distributed power generation to be newly built, quotations of each unit of the power generation company, parameters related to power market operation, original network topology parameters, and other necessary parameters for calculating the utility of participants;

[0059] 2) Generate a set of game participant strategies: The power generation company generates a set of power generation company planning strategies based on the set of new units to be selected. The transmission company generates a set of grid planning strategies based on the set of transmission lines to be selected The user generates a set of distributed power construction strategies based on the set of distributed power candidates. m G. m T and m U is the total number of elements in the strategy sets of generation companies, transmission companies, and large electricity users, respectively;

[0060] 3) Randomly extract a set of planning strategy schemes from the three participants' strategy sets as the initial value of the planning scheme;

[0061] 4) Set the initial iteration value δ = 2;

[0062] 5) Participants optimize their plans: Each participant makes another decision, verifies, and calculates their own plan based on the information of other participants in the previous round. After calculating the power flow and electricity price, the final utility of the three parties in this game round is obtained;

[0063] 6) Determine whether equilibrium has been reached: If the utility of two consecutive game rounds is the same, equilibrium is considered to have been reached and the process proceeds to step 7); if not, set k = k + 1 and return to step 4.5;

[0064] 7) Output model equilibrium solution and the ultimate utility of all parties.

[0065] A method for constructing a source-grid-load planning game decision framework includes the following steps:

[0066] Step 1) The power generation company proposes its own power site selection and capacity determination plan based on the grid structure plan obtained by the transmission company and the power output plan calculated by the ISO (X Gen ,N Gen ), and power generation quotation information

[0067] Step 2) The power generation company transmits the power source location and capacity information to the transmission company, which then forwards the power generation quotation information to the ISO. The transmission company calculates the unit rate utility parameters based on the ISO's previous unit rate utility, combined with the power source location and capacity information provided by the power generation company and the power purchase information of large power users. Decision-making and formulation of line upgrade plans to form a new grid structure;

[0068] Step 3) The transmission company also determines the transmission rate And the grid structure information (X Tra ,N Tra ) to the power generation company, transmit the transmission rate information to the large power users, and transmit the transmission network parameters (line length Line capacity Transmission flow constraints) are passed to the ISO;

[0069] Step 4) Large power users pay the transmission rate determined by the transmission company and the node marginal price SP calculated by ISO. pi Formulate power purchase and DG investment plan (X Use ,N Use ) and feed back its purchased electricity information to the transmission company and ISO;

[0070] Step 5) ISO makes decisions by collecting information from the three parties of source, grid and load, formulates unit rate utility calculation parameters based on the transmission network parameters of the transmission company and transmits them to the transmission company, and formulates the output plan P of the power generation company. g At the same time, the node marginal electricity price is calculated, and finally the node marginal electricity price information is transmitted to the power generation company and large electricity users.

[0071] The objective function of the above large power user planning model is shown in (15):

[0072]

[0073] Where, is a vector set for planning DG projects, where ,L mU∈Ω mU Both are 0-1 variables, indicating whether the planned DG project is newly constructed; A vector set representing the number of planned distributed generation units of large power users; ,L Represents the total distributed power construction capacity of each planning scheme; mU∈Ω mU Indicates the collection of planned new DG projects; The amount of electricity purchased by users from the main network; U Use Cost-effectiveness of electricity consumption for users; Cost utility of electricity purchase for users; Cost utility of purchasing electricity from the main grid for users; Revenue from distributed power generation; Cost effectiveness for equipment operation and maintenance; is the output of distributed power source c at node n at time t; Ω c is the set of distributed power sources c at n nodes; is the operation and maintenance rate per unit DG output;

[0074] Among them, the cost-effectiveness of electricity purchase by large electricity users The calculation formula for the main grid power purchase fee and distributed power generation income is shown in formula (16):

[0075]

[0076] Where, f n,t is the peak load of node n at time t during the planning period;

[0077] The constraints of the planning model for large power users mainly include the number of DG candidate nodes connected, DG penetration rate constraints, and DG output constraints;

[0078] (1) Limitation on the number of DG candidate nodes

[0079]

[0080] Where: N i.min and N i.max are the lower and upper limits of the number of DGs connected to the candidate node i, respectively;

[0081] (2) Node power balance constraints

[0082]

[0083] Where: q n,t is the amount of electricity purchased by node n at time t during the peak load period; is the power generation of the distributed generation at node n at time t; is the total load of n nodes at time t;

[0084] (3) DG output constraints

[0085]

[0086] Where: and are the lower and upper limits of DG output respectively;

[0087] (4) The new DG capacity of large power users is subject to the following equality constraints:

[0088]

[0089] Where, Ω w is the set of generator sets w; P gw is the output of the generator set w; P g =[P g1 ,P g2 ,L,P gw ] is the vector set of the output of each generator set; f pw (·) is the scheduling function.

[0090] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0091] 1) The present invention can achieve more accurate simulation of power market planning decisions;

[0092] 2) The present invention can technically improve the planning and investment efficiency of the entire power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 It is a diagram of the transfer relationship between the subjects;

[0094] Figure 2 It is a dynamic game behavior analysis diagram of each subject;

[0095] Figure 3 It is a schematic diagram of planning results;

[0096] Figure 4 This is a comparison chart of the power flowing into each line at peak load using the two methods. DETAILED DESCRIPTION

[0097] A multi-agent game planning method for sources, grids and loads that considers all dimensions of the electricity market mainly includes the following steps:

[0098] 1) Based on the overall perspective of power market operation, the independent system operator (ISO) is incorporated into the game planning system. At the same time, a transmission utility calculation method that considers the characteristics of transmission regulation is introduced to construct a transmission company planning model that considers monopoly regulation and market operation.

[0099] 2) Taking the construction of new power sources and the commissioning of distributed power sources as decision variables, a source-grid-load planning model that considers multiple market players is constructed;

[0100] 3) Considering the game relationship between various entities, a source-grid-load planning game decision-making framework considering the operation of the power market is proposed;

[0101] 4) Use the iterative search method to solve the Nash equilibrium and obtain the planning scheme of the final model.

[0102] Furthermore, in step 1), the transmission company mainly plans the transmission network in the power system planning, with the goal of maximizing its own utility, and the decision variable is the line construction and expansion plan. The present invention introduces a transmission utility calculation method that takes into account the characteristics of transmission control to construct a planning model for the transmission company. Its objective function is composed of transmission service revenue and reliability costs. In order to give full play to the resource allocation advantages and improve planning efficiency while supervising the transmission company, the transmission company's utility is referenced by the transmission utility calculation method of the mature power market in the United States. The utility calculation project is specifically subdivided into three utility calculation methods: operation and maintenance, operation management, and service revenue. On this basis, the planning and profitability of the transmission company are guaranteed. At the same time, the line operation rate is calculated based on the electricity price flow data on a line-by-line basis. The unit utility rate calculation parameters involved in the utility calculation are all obtained by the ISO during the market clearing stage, thereby ensuring the reasonable market guidance of transmission line planning. The objective function is specifically shown in formula (1).

[0103] The objective function is specifically shown in formula (1).

[0104]

[0105] Where, is a vector set of planned transmission line projects, where ,L mT∈Ω mT Both are 0-1 variables, indicating whether the planned transmission line project is newly constructed; represents the planned expansion capacity set of the transmission company's lines; ,L mT∈Ω mT Indicates the expansion capacity of each planned line; Ω mT represents a collection of planned transmission line projects; is the transmission rate of the lth line; U Tra Total utility for the transmission company; Revenue from electricity transmission services to transmission companies; For operation and maintenance purposes; For operational utility; For communication and other services; is the reliability utility of line l in year t; ψ es Unit power outage loss; EENS l,t is the expected value of power shortage of line l in year t; Ω l A collection of lines.

[0106] Among them, the operation and maintenance utility of the transmission service revenue of the transmission company Operational Utility Communication and other service utilities The solution formula is shown in formula (2):

[0107]

[0108] Where, is the maximum power flowing through line l in year t; is the capacity of line l; is the length of line l; Modeling and analyzing rates for transmission company unit capacity; is the operating rate per unit active power of the transmission company; σ m is the unit capacity transmission line operating rate; σ c is the rate for other services such as transmission line communication per unit length; the relevant parameters involved in the specific utility calculation are as follows σ m and σ c All are arrived at by ISO during the decision-making stage.

[0109] Constraints include new line investment constraints, branch power flow constraints, and safety constraints.

[0110] (1) Constraints on the number of new lines

[0111]

[0112] (2) Branch flow constraints

[0113]

[0114] Where: P i.t and Q i.t are the active power and reactive power of node i at time t; U i.t and U j.t are the voltage amplitudes of nodes i and j at time t; G ij and B ij are the conductance and susceptance of branch ij respectively; θ ij is the phase angle difference between the voltages at nodes i and j.

[0115] (3) Safety constraints

[0116]

[0117] Where: U i.min and U i.max are the lower and upper limits of the voltage amplitude of node i at any typical time t; P ij.t and P ij.max are the transmission power of branch ij at any typical time t and its upper limit respectively.

[0118] In step 2), the power generation company primarily determines the location and capacity of new units in power system planning. The objective function of its planning model is composed of the electricity sales utility and operating rate of existing units, and the decision variables are the location and capacity of the new units.

[0119] The specific objective function is shown in formula (6).

[0120]

[0121] Where U Gen represents the total utility of the power generation company; is a vector set of planned generator project, where ,L mG∈Ω mG Both are 0-1 variables, indicating whether the generator project is newly built, Ω mG To plan the collection of power generation project; represents the planned capacity set of units of the power generation company, where ,L mG∈Ω mG Indicates the planned capacity of each power generation unit project; is the power generation quotation information; pn represents the node marginal electricity price at node n; The electricity sales utility of the power generation company's units; is the operating cost of the power generation company's unit; r is the discount rate; T is the year of project operation; is the electricity sales of node n at time t; Ω t is the set of typical peak load moments t in the Tth year; Ω T is the planning period set; Ω N is a set of nodes; is the unit operating rate of the generator set.

[0122] Constraints include the number of newly built generating units that can generate electricity and the upper and lower limits of the output of newly built generating units:

[0123] (1) Constraints on the number of new generating units that can generate electricity

[0124]

[0125] (2) Upper and lower output limits of newly built generator sets

[0126]

[0127] Where, The output of the newly built generators upper and lower bound constraints.

[0128] In step 2), large power users meet their power load in two ways: 1) purchasing electricity from power generators and then transmitting it through the transmission network, where the electricity settlement method is the node marginal price of the node, and the transmission rate is charged by the transmission company at a certain rate based on the peak load of the node; 2) by building new distributed power sources, they reduce their dependence on power generation companies and transmission companies, and the investment and operation rates of distributed power sources are borne by the power users themselves. In the power system planning, large power users mainly plan their own power consumption plans, with the goal of minimizing their own power consumption rates, and the decision variables are the distributed power construction plans. The planning model of large power user companies constructed by the present invention has an objective function composed of the user's power purchase costs and DG operation and maintenance costs. The specific calculation formula is shown in (9):

[0129]

[0130] Where, is a vector set for planning DG projects, where ,L mU∈Ω mU Both are 0-1 variables, indicating whether the planned DG project is newly constructed; A vector set representing the number of planned distributed generation units of large power users; ,L Represents the total distributed power construction capacity of each planning scheme; mU∈Ω mU Indicates the collection of planned new DG projects; The amount of electricity purchased by users from the main network; U Use Cost-effectiveness of electricity consumption for users; Cost utility of electricity purchase for users; Cost utility of purchasing electricity from the main grid for users; Revenue from distributed power generation; Cost effectiveness for equipment operation and maintenance; is the output of distributed power source c at node n at time t; Ω c is the set of distributed power sources c at n nodes; It is the operation and maintenance rate per unit DG output.

[0131] Among them, the cost-effectiveness of electricity purchase by large electricity users The calculation formula of the main grid power purchase fee and distributed power generation income is shown in formula (10):

[0132]

[0133] Where, f n,t is the peak load of node n at time t during the planning period.

[0134] The constraints of the planning model for large power users mainly include the number of DG candidate nodes connected, DG penetration rate constraints, and DG output constraints.

[0135] (1) Limitation on the number of DG candidate nodes

[0136]

[0137] Where: N i.min and N i.max are the lower and upper limits of the number of DGs connected to the candidate node i, respectively.

[0138] (2) Node power balance constraints

[0139]

[0140] Where: q n,t is the amount of electricity purchased by node n at time t during the peak load period; is the power generation of the distributed generation at node n at time t; is the total load of n nodes at time t.

[0141] (3) DG output constraints

[0142]

[0143] Where: and are the lower and upper limits of DG output respectively.

[0144] (4) The new DG capacity of large power users is subject to the following equality constraints:

[0145]

[0146] The decision model for ISO power generation output planning in step 2) is the optimal economic dispatch model, and the specific formula is:

[0147]

[0148] Where, Ω w is the set of generator sets w; P gw is the output of the generator set w; P g =[P g1 ,P g2 ,L,P gw ] is the vector set of the output of each generator set; f pw (·) is the dispatch rate function.

[0149] The calculation formula for ISO's dispatching fee is as follows:

[0150]

[0151] Where N G is the total number of connected generators; c pw 、b pw 、a pw is the quoted parameter of generator set w.

[0152] The constraints of the ISO power generation planning decision model are:

[0153] (1) The equality constraint is:

[0154]

[0155] Where, P gw ,Q gw are respectively the active and reactive power generation capacity of generator w; P dw ,Q dw are respectively the active and reactive loads of generator w; U i ,U j are the voltage amplitudes of nodes i and j respectively; θ i ,θ j are the voltage phase angles of nodes i and j respectively; Y ij is the node admittance matrix element; δ ij is the admittance phase angle.

[0156] (2) Inequality constraints

[0157]

[0158] Where, P gwmax ,P gwmin They are respectively the active output of generator w and P gw Upper and lower limit constraints; Q gwmax ,Q gwmin They are respectively the reactive output of generator w and Q gw Upper and lower limit constraints; U imax ,U imin are the voltage amplitude U at node i i Upper and lower limit constraints; P l is the active power flowing through line l; P lmax is the upper limit constraint of the active power of line l; It represents the distribution of power generation capacity transmitted by line l to power node n.

[0159] According to the marginal rate pricing theory, the node marginal price is the slight increase rate of the system rate on the power injected into each node. Based on formulas (15)-(18), by introducing slack variables and barrier functions, the Lagrangian function introduced into the power flow equation is constructed as follows:

[0160]

[0161] Where λ, β, ω are Lagrange multiplier vectors; o, u are slack variables, where o, u are both greater than 0; P is the vector dimension of o and u; h(x) is the equality constraint in formula (17); g(x) = g(P gw ,Q gw ,U i ,P l ) is the inequality constraint in formula (18); μ is the barrier factor and is greater than 0.

[0162] Among them, the barrier function term is introduced, and the extended objective function is obtained as follows:

[0163]

[0164] The equality constraints introduced into the Lagrangian function are:

[0165]

[0166] The node marginal price of active node n is obtained as follows:

[0167]

[0168] In the formula, * represents the optimal solution.

[0169] The transfer relationship between the various subjects involved in the full-dimensional source-grid-load planning game decision model in step 3) during planning decision-making is as follows: Figure 1 shown.

[0170] In the decision-making process, the power generation company proposes its own power site selection and capacity determination plan based on the grid structure plan obtained by the transmission company and the power output plan calculated by the ISO (X Gen ,N Gen ), and power generation quotation information The location and capacity information of the power source is transmitted to the transmission company, and the power generation quotation information is transferred to the ISO. The transmission company calculates the unit rate utility parameters transmitted by the ISO on the previous day, and combines the power source location and capacity information provided by the power generation company and the power purchase information of large power users. Decision-making and formulation of line upgrade plans to form a new grid structure;

[0171] Determine the transmission rate And the grid structure information (X Tra ,N Tra ) to the power generation company, transmit the transmission rate information to the large power users, and transmit the transmission network parameters (line length Line capacity Transmission flow constraints) are passed to the ISO;

[0172] Large electricity users pay the transmission rate determined by the transmission company and the node marginal price SP calculated by ISO. pi Formulate power purchase and DG investment plan (X Use ,N Use ) and feeds back its purchased electricity information to the transmission company and ISO; ISO is the independent decision-making body of the electricity market;

[0173] It makes decisions by collecting information from the three parties of source, grid and load, formulates unit rate utility calculation parameters according to the transmission network parameters of the transmission company and transmits them to the transmission company, and formulates the output plan P of the power generation company. g At the same time, the node marginal electricity price is calculated, and finally the node marginal electricity price information is transmitted to the power generation company and large electricity users.

[0174] Of the three aforementioned market players, power generation and transmission companies must undergo safety verification in their decisions. This verification, considered from a holistic perspective, requires information from every link in the power grid, from sources to grids and loads. Therefore, their decisions are centered around safety verification and are directly influenced and constrained by the decisions of other stakeholders involved in the power grid, thus creating a power-game dynamic. For users, their decisions are influenced both directly and indirectly by the transmission company. Specifically, before setting transmission rates, transmission companies first conduct a safety verification of the transmission network based on information such as the planned grid structure. This prevents the transmission of inadequate safety strategies to the generation and user sides, which would then be passed on to users after verification and influence their electricity rates and decisions. Power generation companies, on the other hand, first submit their generation rates to the ISO for decision-making. The ISO then independently optimizes its operational decisions to calculate node-level marginal prices, which influence user rates and decisions. Generally speaking, the decisions of the above three market players are independent of each other but mutually constrained, and decision-making information is fully shared, thus forming a complete information game relationship.

[0175] Since it is necessary to jointly complete the planning and construction of the power system under the premise of independent decision-making, the power generation company, the transmission company and the large power users have all the strategic information of each other during the planning process. In the game process, the actions of the three parties have a sequence. The game behavior diagram is shown below. Figure 2 shown.

[0176] exist Figure 2In the game round shown, the ISO, as a special entity independent of the source, grid, and load, is integrated into the game planning system and serves as an information relay between power generation companies and large power consumers. After receiving the power generation company's unit bid information and the large power consumer's electricity consumption plan, the ISO provides node marginal prices and dispatch plans. After receiving the electricity price and transmission rate information, the large power consumer determines its power purchase plan and distributed generation (DG) construction plan, targeting the minimum electricity rate, and then provides feedback to the ISO and the transmission company. Based on the large power consumer's power purchase plan and the power generation company's power generation plan from the previous round, the transmission company adjusts its line construction plan to maximize the total utility of the transmission network. Simultaneously, based on the transmission company's new line decision-making plan from the previous round and the large power consumer's electricity consumption plan, the generation company adjusts the site selection and sizing of new generators to maximize the power sales utility of the generation company. After updating the site selection and sizing of the new generators, network topology, and power purchase plan, the next game round begins.

[0177] During the game, when any of the power generation company, transmission company, and large power user cannot gain more utility by changing their strategy, the game reaches equilibrium, which can be described as follows:

[0178]

[0179] Where: are all the optimal strategies of one party when the other party chooses the optimal strategy. Under this strategy combination, the power generation company, the transmission company, and the large power user can all achieve the maximum utility in the equilibrium sense. argmax(·) is the set of variables that maximizes the value of the objective function.

[0180] In step 4), the Nash equilibrium of the proposed dynamic game model is solved by an iterative search method. The specific solution steps are as follows:

[0181] 4.1) Input original data and parameters. Initialize the data required to establish the game model, including load information, parameters of the units to be newly built, parameters of the lines to be newly built, parameters of the distributed power generation systems to be newly built, quotes from each unit of the power generation company, parameters related to power market operation, original network topology parameters, and other necessary parameters for calculating the utility of participants;

[0182] 4.2) Generate a set of game participant strategies. The power generation company generates a set of power generation company planning strategies based on the set of candidate units for new generation. The transmission company generates a set of grid planning strategies based on the set of transmission lines to be selected The user generates a set of distributed power construction strategies based on the set of distributed power candidates. m G. m T and mU is the total number of elements in the strategy sets of generation companies, transmission companies, and large electricity users, respectively.

[0183] 4.3) Randomly select a set of planning strategy solutions from the three participants' strategy sets as the initial planning strategy values;

[0184] 4.4) Set the initial iteration value δ = 2;

[0185] 4.5) Participants optimize their plans. Each participant, based on the information from other participants in the previous round, makes another decision, verifies, and calculates their own plan. After calculating the power flow and electricity price, the final utility of the three parties in this round of the game is obtained. This invention is based on the ISO scheduling model and uses the primal-dual interior point method to calculate the node marginal electricity price of the system.

[0186] 4.6) Determine whether equilibrium has been reached. If the utility of two consecutive game rounds is the same, equilibrium is considered reached and the process proceeds to step 4.7. If not, set k = k + 1 and return to step 4.5.

[0187] 4.7) Output model equilibrium solution and the ultimate utility of all parties.

[0188] Example:

[0189] 1. Parameter settings

[0190] This paper uses a modified IEEE 30-node system as a simulation example. The market pricing mechanism in this example is assumed to be the node marginal price, the decision-making mechanism is unit commitment with safety constraints, and the planning period is 20 years. Assuming that as load increases, the power generation company needs to build new power sources at nodes 1-6, the relevant parameters of the new power sources are shown in Table 1. It should be noted that the volatility mentioned in Table 1 and below is the utility volatility.

[0191] Table 1 Power generation company can add power supply parameters

[0192]

[0193] The transmission company formulates a transmission expansion plan based on load changes within the power grid and its own development needs. The set of lines to be upgraded and renovated during the planning period is {2, 6, 16, 28, 35, 32}, and their utility fluctuations are {0.4, 0.41, 0.38, 0.23, 0.29, 0.32}. The technical parameters of the newly expanded lines are shown in Table 2.

[0194] Table 2 Transmission company's expandable line parameters

[0195]

[0196] Table 3 shows the parameters for newly built distributed power sources for large power users.

[0197] Table 3 Parameters of new distributed power generation for large power users

[0198]

[0199] At the same time, in order to verify the correctness and effectiveness of the method of the present invention, two different methods are added to solve the example of the present invention, and their results are compared and analyzed with the method of the present invention. These methods are as follows.

[0200] Method 1: Traditional planning methods that do not consider all dimensions. This is a planning model that does not consider the dynamic impact of ISO decisions and the utility of transmission companies.

[0201] Method 2: A full-dimensional planning approach, that is, a planning model that considers the dynamic impact of ISO decisions and the utility of transmission companies.

[0202] 2. Simulation results

[0203] Two methods are used to perform simulation calculations in the above example, and the planning decision-making results of each market player are shown in Table 4.

[0204] Table 4 Planning schemes and total utility of different market players under each method

[0205]

[0206] As shown in Table 4, the power generation company's plan is to build a new 10MW power source at nodes 1, 3, and 5; the transmission company's plan is to upgrade and renovate lines 6, 2, 16, and 35, all using Type 2 lines; and the large power user's plan is to build a new 5MW distributed power source at nodes 8, 19, 21, and 30. The planning results are shown in the following figure. Figure 4 shown.

[0207] 3. Comparative Analysis

[0208] 1) Transmission companies

[0209] First, the reliability costs, total revenue, and total utility of the transmission company obtained by Method 1 and Method 2 are compared. The calculation results are shown in Table 5.

[0210] Table 5 Comparison of calculation results of two methods for transmission companies (10,000 yuan)

[0211] Table 5 shows that, in terms of the overall utility and costs of transmission lines, Method 2 increases total revenue by 2.9537 million yuan and reduces reliability costs by 3 million yuan compared to Method 1, resulting in a total utility increase of 5.9537 million yuan. This is primarily due to the fact that, unlike Method 1, Method 2 does not simply optimize based on node marginal price differences and cost-utility, but instead considers the optimal operation of the entire power market. Consequently, it expands one additional line compared to Method 1. This line strengthens the overall transmission network structure. This optimizes grid flow, reduces losses for transmission companies, and thus reduces reliability costs. Furthermore, from the perspective of the entire power market, it reduces electricity costs for consumers and increases electricity sales, thereby increasing the utility of transmission companies.

[0212] This shows that, compared to Method 1, Method 2, because it constructs a planning model that considers the characteristics of the transmission network market, encourages transmission companies to make planning decisions from a macro perspective of overall market utility. While ensuring total project revenue, it effectively strengthens the transmission company's overall grid structure, increases overall electricity sales revenue, and reduces operating expenses, thereby effectively improving the transmission company's overall utility.

[0213] 2) Power generation companies

[0214] Comparing the total operating expenses, total revenue and total utility of the power generation company obtained by Method 1 and Method 2, the calculation results are shown in Table 6.

[0215] Table 6 Comparison of calculation results of two methods for power generation companies (10,000 yuan)

[0216]

[0217] Table 6 shows that Method 2 increases the total operating costs and total revenue of all generating units of a power generation company by RMB 345 million and RMB 329 million, respectively, compared to Method 1, resulting in a total utility increase of RMB 363.5 million for the power generation company. This is because, on the one hand, Method 2 optimizes the transmission network structure from a holistic perspective, facilitating the acceptance of more generating units by the entire power market; on the other hand, Method 2 incorporates ISO decisions into the planning and game system, ensuring that the power generation company's accounting and power market dynamics are reflected in the planning and decision-making process. This allows the company to increase power sales by reducing the system's node marginal electricity price based on the dynamic game of the power market, thereby improving the power generation company's total utility.

[0218] It can be seen that in addition to using node marginal electricity price information to guide the planning of different entities, Method 2 also incorporates the ISO as an independent entity into the planning system, so that power generation companies will fully consider the issue of resource allocation optimization in the decision-making process. While ensuring the utility of the project, they make decisions from the perspective of optimizing the electricity costs of the entire power market, and maximize the total utility by enhancing their own market competitiveness.

[0219] 3) Large electricity users

[0220] Comparing the project investment and operating costs, income of new projects of large power users obtained by Method 1 and Method 2, as well as the total operating costs, total income and utility of large power users excluding new projects, the calculation results are shown in Table 7. The electricity costs of large power users are composed of total income and electricity purchase costs, and the marginal electricity prices of some nodes at peak load are shown in Table 8.

[0221] Table 7 Comparison of calculation results of two methods for large power users (10,000 yuan)

[0222]

[0223] Table 8 Node marginal electricity price at peak load of some nodes (yuan)

[0224]

[0225]

[0226] Table 7 shows that both the total operating costs and total revenue for large electricity users are zero. This is primarily due to the fact that, prior to the construction of the new project, these users had no existing distributed generation (DG) capacity. Method 2 reduces both the power purchase cost and the total electricity cost for large electricity users by 665.2163 million yuan compared to Method 1. This is primarily due to the fact that Method 2 considers the entire power market in its planning and decision-making process, incorporating the influence of ISO decisions and dynamically feeding back information about the user's DG construction to other market players, thus fostering market competition. This encourages transmission companies to consider the overall power market perspective, strengthening the grid structure. It also enables generation companies to adjust their planning and decision-making based on the dynamics of the power market, effectively reducing the marginal price at the node. This allows power users to adjust their DG investment plans based on the node price, thereby objectively reducing their total electricity costs.

[0227] It can be seen from this that Method 2 introduces ISO into the planning system, which can dynamically feed back the planning information of power generation companies and transmission companies to large power users in the form of node marginal electricity prices in each round of game. This allows large power users to achieve a dynamic optimal balance between purchasing electricity and building their own distributed power sources based on changing market information during the decision-making process, and feed back relevant information to the market in real time through ISO, thereby guiding the decision-making of other entities in the planning process and effectively improving the planning benefits of each entity.

[0228] Compared to Method 1, Method 2 increases the transmission power of Lines 1, 7, and 10. This improves the equipment utilization of the transmission lines and, in turn, the overall utility of the transmission company. The primary reason for this is that Method 1 opts to expand Lines 2 and 35, but not Line 16, which has a higher marginal price at nearby nodes. This is because Method 1 directly uses the marginal price difference at the node as the utility calculation model for transmission network planning and fails to consider dynamic market feedback from the ISO and other market participants during the planning process. This planning approach makes planning decisions based on the short-term project utility of the transmission network, and Line 16, due to its higher construction costs, is not included in the planning scheme. This results in higher electricity prices at some nodes compared to Method 2, directly increasing users' electricity purchase costs and further leading them to expand the scale of new distributed generation (DG) installations, thereby reducing the transmission power of some lines and lowering the utilization of transmission equipment. Unlike Method 1, Method 2 incorporates ISO decision-making into a multi-agent game framework. Furthermore, it introduces a transmission utility calculation method that considers the characteristics of transmission regulation, prompting transmission companies to optimize the grid from the perspective of the overall power market. Therefore, in addition to expanding Lines 2 and 35, the more expensive Line 16 was also expanded. This alleviates congestion while increasing the grid capacity and utility of power generation companies. Furthermore, the line expansion and increased generation units effectively reduce the marginal electricity price at nodes and increase the amount of electricity purchased by users, further increasing the transmission power of some lines and improving the utilization rate of transmission equipment, thereby improving the overall utility of transmission companies.

[0229] In summary, the idea of ​​fully considering all dimensions in the planning process proposed in the present invention can effectively improve the planning benefits of each entity and is correct and effective.

Claims

1. A method for constructing a source-grid-load planning game decision framework, characterized in that: The following steps are involved: Step 1) The power generation company proposes its own power site selection and capacity determination plan based on the grid structure plan obtained by the transmission company and the power output plan calculated by the ISO (X Gen ,N Gen ), and power generation quotation information Step 2) The power generation company transmits the power source location and capacity information to the transmission company, which then forwards the power generation quotation information to the ISO. The transmission company calculates the unit rate utility parameters based on the ISO's previous unit rate utility, combined with the power source location and capacity information provided by the power generation company and the power purchase information of large power users. Decision-making and formulation of line upgrade plans to form a new grid structure; Step 3) The transmission company also determines the transmission rate And the grid structure information (X Tra ,N Tra ) to the power generation company, transmit the transmission rate information to the large power users, and transmit the transmission network parameters to the ISO, the transmission network parameters including line length Line capacity Transmission flow constraints; Step 4) Large power users pay the transmission rate determined by the transmission company and the node marginal price SP calculated by ISO. pi Formulate power purchase and DG investment plan (X Use ,N Use ) and feed back its purchased electricity information to the transmission company and ISO; Step 5) ISO makes decisions by collecting information from the three parties of source, grid and load, formulates unit rate utility calculation parameters based on the transmission network parameters of the transmission company and transmits them to the transmission company, and formulates the output plan P of the power generation company. g At the same time, the node marginal electricity price is calculated, and finally the node marginal electricity price information is transmitted to the power generation company and the large power users; From the above steps, the objective function of the large power user planning model is obtained as shown in formula (15): Where, is a vector set for planning DG projects, where Both are 0-1 variables, indicating whether the planned DG project is newly constructed; A vector set representing the number of planned distributed generation units of large power users; Indicates the total distributed power construction capacity of each planning scheme; mU∈Ω mU Indicates the collection of planned new DG projects; The amount of electricity purchased by users from the main network; U Use Cost-effectiveness of electricity consumption for users; Cost utility of electricity purchase for users; Cost utility of purchasing electricity from the main grid for users; Revenue from distributed power generation; Cost effectiveness for equipment operation and maintenance; is the output of distributed power source c at node n at time t; Ω c is the set of distributed power sources c at n nodes; Ω T is the planning period set; Ω t is the set of typical peak load moments t in the Tth year; Ω N is a set of nodes; is the operation and maintenance rate per unit DG output; The objective function of the transmission company planning model is shown in formula (1): Where, is a vector set of planned transmission line projects, where Both are 0-1 variables, indicating whether the planned transmission line project is newly constructed; represents the planned expansion capacity set of the transmission company's lines; Indicates the expansion capacity of each planned line; Ω mT represents a collection of planned transmission line projects; is the transmission rate of the lth line; U Tra Total utility for the transmission company; Revenue from electricity transmission services to transmission companies; For operation and maintenance purposes; For operational utility; Utility for communication services; is the reliability utility of line l in year t; ψ es Unit power outage loss; EENS l,t is the expected value of power shortage of line l in year t; Ω l is a collection of lines; The objective function of the power generation company planning model obtained is shown in formula (6): Where U Gen represents the total utility of the power generation company; is a vector set of planned generator project, where Both are 0-1 variables, indicating whether the generator project is newly built, Ω mG To plan the collection of power generation project; represents the planned capacity set of units of the power generation company, where Indicates the planned capacity of each power generation unit project; is the power generation quotation information; pn represents the node marginal electricity price at node n; The electricity sales utility of the power generation company's units; is the operating cost of the power generation company's unit; r is the discount rate; T is the year of project operation; is the electricity sales of node n at time t; Ω t is the set of typical peak load moments t in the Tth year; Ω T is the planning period set; Ω N is a set of nodes; is the unit operating rate of the generator set.

2. The method for constructing a source-grid-load planning game decision framework according to claim 1, characterized in that: The cost-effectiveness of electricity purchases by large electricity users The calculation formula for the main grid power purchase fee and distributed power generation income is shown in formula (16): Where, f n,t is the peak load of node n at time t during the planning period; The constraints of the planning model for large power users mainly include the number of DG candidate nodes connected, DG penetration rate constraints, and DG output constraints; (1) Limitation on the number of DG candidate nodes Where: N i.min and N i.max are the lower and upper limits of the number of DGs connected to the candidate node i, respectively; (2) Node power balance constraints Where: q n,t is the amount of electricity purchased by node n at time t during the peak load period; is the power generation of the distributed generation at node n at time t; is the total load of n nodes at time t; (3) DG output constraints Where: and are the lower and upper limits of DG output respectively; (4) The new DG capacity of large power users is subject to the following equality constraints: Where, Ω w is the set of generator sets w; P gw is the output of the generator set w; P g =[P g1 ,P g2 ,…,P gw ] is the vector set of the output of each generator set; f pw (·) is the scheduling function.

3. The method for constructing a source-grid-load planning game decision framework according to claim 1, characterized in that: Operation and maintenance utility in transmission service revenue of transmission companies Operational Utility Communication service utility The solution formula is shown in formula (2): Where, is the maximum power flowing through line l in year t; is the capacity of line l; is the length of line l; Modeling and analyzing rates for transmission company unit capacity; is the operating rate per unit active power of the transmission company; σ m is the unit capacity transmission line operating rate; σ c is the communication service rate per unit length of transmission line; the relevant parameters involved in the specific utility calculation are as follows σ m and σ c All are derived by ISO during the decision-making stage; Constraints include new line investment constraints, branch line power flow constraints, and safety constraints; (1) Constraints on the number of new lines (2) Branch flow constraints Where: P i.t and Q i.t are the active power and reactive power of node i at time t; U i.t and U j.t are the voltage amplitudes of nodes i and j at time t; G ij and B ij are the conductance and susceptance of branch ij respectively; θ ij is the phase angle difference between the voltages at nodes i and j; (3) Safety constraints Where: U i.min and U i.max are the lower and upper limits of the voltage amplitude of node i at any typical time t; and P ij.max are the transmission power of branch ij at any typical time t and its upper limit respectively.

4. The method for constructing a source-grid-load planning game decision framework according to claim 1, characterized in that: The constraints of the power generation company planning model include the number of new generating units that can generate electricity and the upper and lower limits of the output of new generating units: (1) Constraints on the number of new generating units that can generate electricity (2) Upper and lower output limits of newly built generator sets Where, The output of the newly built generators upper and lower bound constraints.

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