Game theory-based reactive power joint optimization method, system, equipment and medium for main and distribution networks

Abstract

The invention discloses a main and distribution network reactive power joint optimization method, system and device based on the game theory and a medium. The method comprises the following steps: constructing a reactive power demand level index; constructing a plurality of typical fault scenes according to the reactive power demand level indexes; the reactive power demand of the main and distribution networks in each typical fault scene is analyzed, a joint optimization model considering the reactive power demand is constructed, and the goal of comprehensively maximizing the electric energy quality, the new energy utilization rate and the economic benefit is achieved through transmission and distribution cooperation; the joint optimization model comprises a main distribution network reactive power demand objective function, a main distribution network electric energy quality objective function and a distribution network new energy utilization rate objective function; and constructing a three-objective game model based on a main and distribution network reactive power demand objective function, a main and distribution network electric energy quality objective function and a distribution network new energy utilization rate objective function, and solving the three-objective game model by adopting a Bayesian-Nash equilibrium theory in a game theory to obtain a final result of main and distribution network reactive power joint optimization. The stability and economic benefits of the power grid are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of joint optimization dispatching of power grids, and in particular relates to a method, system, equipment and medium for joint optimization of reactive power of main and distribution networks based on game theory. Background Art

[0002] In recent years, with the large number of distributed wind power and photovoltaic power generation connected to the grid, the penetration rate of new energy has continued to increase, and the reactive power and voltage control of the power system have encountered challenges. New energy often generates a large amount of reactive power while generating active power, but the utilization rate of this reactive power is very small. How to effectively utilize the large amount of reactive power resources generated by new energy power generation in the distribution network, provide reactive power support for the main network, reduce the investment in reactive equipment, and improve the stability and economic benefits of the power grid is an urgent problem to be solved. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides a method, system, device and medium for joint optimization of reactive power of main and distribution networks based on game theory. The method for joint optimization of reactive power of main and distribution networks based on game theory considers making full use of a large amount of reactive resources generated by new energy power generation in the distribution network, constructs RPDL indicators and a variety of typical fault scenarios, constructs a joint optimization model that comprehensively considers the reactive power demand of the main and distribution networks, and uses the Bayesian-Nash equilibrium theory in game theory to solve the problem, thereby obtaining the final result of joint optimization of reactive power of main and distribution networks.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] A method for joint optimization of reactive power of main and distribution networks based on game theory comprises the following steps:

[0006] S1. Construct reactive power demand level index;

[0007] S2. Construct a variety of typical fault scenarios based on reactive power demand level indicators;

[0008] S3. Analyze the reactive power demand of the main distribution network under various typical fault scenarios, build a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goal of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function;

[0009] S4. Construct a three-objective game model based on the reactive power demand objective function of the main distribution network, the power quality objective function of the main distribution network and the new energy utilization rate objective function of the distribution network. Use the Bayesian-Nash equilibrium theory in game theory to solve the three-objective game model and obtain the final result of the joint optimization of the reactive power of the main distribution network.

[0010] To optimize the above technical solutions, the specific measures taken also include:

[0011] Furthermore, the reactive power demand level index is constructed as follows:

[0012] Construct the main network reactive power demand level indicator as follows:

[0013]

[0014] In the formula, a MN The reactive power demand level value of the main network; Q D,MN The reactive power required after a main network failure. When the value is 0, it means there is no failure and the network is operating normally. R,MN Reactive power reserve for the main grid;

[0015] Construct the distribution network reactive power demand level indicator as follows:

[0016]

[0017] In the formula, a DN Q is the reactive power demand level value of the distribution network; D,DN It is the reactive power required after the distribution network fails. When its value is 0, it means there is no failure and the network is operating normally. R,DN Reactive power reserve owned by the distribution network;

[0018] Combined with the main grid reactive power demand level index a MN And distribution network reactive power demand level index a DN , construct the comprehensive reactive power demand level index a of the main grid and distribution network RPDL , as shown below:

[0019] a RPDL =(a MN ,a DN )

[0020] The comprehensive reactive power demand level index of the main grid and distribution network is a two-dimensional array, and each number has three values: 0, 1, and 2, for a total of 9 values.

[0021] Furthermore, S2 is specifically:

[0022] When the comprehensive reactive power demand level index of the main grid distribution network is (0, 0), it means that there is no fault in the power grid;

[0023] When the comprehensive reactive power demand level index of the main network and distribution network is (0, 1), it means that there is no fault in the main network and a slight fault occurs in the distribution network;

[0024] When the comprehensive reactive power demand level index of the main network and distribution network is (0, 2), it means that there is no fault in the main network, but a major fault has occurred in the distribution network;

[0025] When the comprehensive reactive power demand level index of the main network and distribution network is (1, 0), it means that a minor fault has occurred in the main network, but no fault has occurred in the distribution network;

[0026] When the comprehensive reactive power demand level index of the main network and distribution network is (1, 1), it means that both the main network and the distribution network have minor faults;

[0027] When the comprehensive reactive power demand level index of the main network and distribution network is (1, 2), it means that a minor fault has occurred in the main network and a major fault has occurred in the distribution network;

[0028] When the comprehensive reactive power demand level index of the main network and distribution network is (2, 0), it means that a major fault has occurred in the main network, but no fault has occurred in the distribution network;

[0029] When the comprehensive reactive power demand level index of the main network and distribution network is (2, 1), it means that a major fault has occurred in the main network and a minor fault has occurred in the distribution network;

[0030] When the comprehensive reactive power demand level index of the main grid and distribution network is (2, 2), it means that major faults have occurred in both the main grid and the distribution network.

[0031] Furthermore, in S3, the main distribution network reactive power demand objective function f 1 , as shown below:

[0032] f 1 =min{max(Q MN ,Q DN1 ,Q DN2 ,...,Q DN i)}

[0033] In the formula, Q DNi is the reactive power demand when the ith distribution network fails; Q MN The reactive power demand when the main grid fails; the overall objective function of the reactive power demand of the main distribution network represents the minimization of the reactive power reserve provided by the additional equipment required in the scenario with the maximum reactive power demand through the coordinated optimization of transmission and distribution;

[0034] The main distribution network power quality objective function f 2 As shown below:

[0035]

[0036] In the formula, z MN The power quality of the main grid, The average value of the power quality of the main grid plus all distribution grids, N is the number of distribution grids; i is the power quality of the ith distribution network, V ai is the actual voltage of the ith distribution network; V ni is the rated voltage of the ith distribution network; f aiis the actual frequency of the ith distribution network; f ni is the rated frequency of the ith distribution network; V is the weight coefficient of voltage deviation in power quality, λ f is the weight coefficient of frequency deviation in power quality, λ V +λ f =1;

[0037] The distribution network new energy utilization rate objective function f 3 As shown below:

[0038]

[0039] Where N is the number of distribution networks, h i is the utilization rate of new energy in the i-th distribution network; is the average value of the renewable energy utilization rate of all distribution networks; a DN is the reactive power demand level value of the distribution network, Q D,DN is the reactive power required after the distribution network fails, m i is the proportion of reactive power demand of the ith distribution network used to support the main network; a MN is the reactive power demand level value of the main network, Q D,MN is the reactive power required after the main network fails, Q NEWi It is the reactive power reserve brought by the renewable energy power generation in the i-th distribution network.

[0040] Furthermore, S4 specifically includes:

[0041] S41. Establish a strategy set based on the strategies that may be selected according to the reactive demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function. According to whether there is cooperation between the objective functions, the strategy set S is recorded as S = {S1 = 0.25, S2 = 0.75}; S1 represents the penalty strategy and S2 represents the cooperation strategy;

[0042] S42, assigning a value to the friendship matrix FD at the initial moment; as shown below:

[0043]

[0044] In the formula, λ aa is the friendliness of the objective function a to itself, λ ab is the friendliness of objective function a to objective function b; a=1,2,3; b=1,2,3; a≠b, a and b represent the serial numbers of the objective functions;

[0045] S43. Use the friendship matrix to obtain the payoff values ​​of all strategies to satisfy the Bayesian-Nash equilibrium;

[0046] S44, using the benefit values ​​of all strategies to solve the optimal strategy for all objective functions, obtain the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration, and use this optimal Bayesian-Nash equilibrium solution as the optimal weight of each objective function, so as to obtain the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function;

[0047] S45, verify whether the iteration number requirement is met, if so, proceed to step S46, otherwise update the friendship matrix and repeat steps S43 and S44;

[0048] The update friendliness matrix is ​​specifically:

[0049] If the strategy of objective function a brings positive benefits to objective function b, then the friendliness of objective function a to objective function b will increase; if the strategy of objective function a brings negative benefits to objective function b, then the friendliness of objective function a to objective function b will decrease. The formula is as follows:

[0050]

[0051] In the formula, u ab represents the benefit that the strategy of the ath objective function brings to the bth objective function, λ ab Indicates the friendliness of the a-th objective function to the b-th objective function;

[0052] S46. Give the optimization result of the three-objective game model as the optimization result of the reactive power reserve demand of the whole system.

[0053] Furthermore, in S43, the benefit values ​​of all strategies are obtained by using the friendship matrix as follows:

[0054] The formula for calculating the revenue value is as follows:

[0055] U a-c-d-e =λ 1a u 1a +λ 2a u 2a +λ 3a u 3a

[0056] Where U a-c-d-e It represents the objective function of the utilization rate of new energy in the distribution network f 3 Taking strategy c, the main distribution network power quality objective function f 2 Taking strategy d, the main distribution network reactive power demand objective function f 1 The total benefit value obtained by the ath objective function when strategy e is adopted; c, d, e∈{1, 2}, where 1 represents a penalty strategy and 2 represents a cooperative strategy; u 1a ,u 2a ,u3a They are respectively the reactive power demand objective function f of the main distribution network 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The benefit of the strategy adopted for the ath objective function, λ 1a ,λ 2a ,λ 3a They are respectively the objective function main distribution network reactive power demand objective function f 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The friendliness of the adopted strategy to the ath objective function.

[0057] Further, S44 is specifically:

[0058] Calculate the penalty strategy S for all objective functions according to the following formula 1 and cooperation strategy 2 Expected total return:

[0059]

[0060] In the formula, is the ath objective function f a Punishment strategy S 1 Expected total return; is the ath objective function f a Cooperation strategy 2 The expected total return of 5 and λ 6 is the weight coefficient, is the ath objective function f a The other two objective functions choose the penalty strategy S 1 When the ath objective function f a Expected earnings; is the ath objective function f a Among the two objective functions other than 1 , another objective function selects the cooperation strategy S 2 When the ath objective function f a Expected earnings; is the ath objective function f a Among the two objective functions other than 2 , another objective function selects the penalty strategy S 1 When the ath objective function f a Expected earnings; is the ath objective function f aThe other two objective functions choose the cooperative strategy S 2 When the ath objective function f a Expected earnings;

[0061] The strategy with the larger expected total benefit obtained from the two strategies is the optimal strategy; the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration is obtained, and this optimal Bayesian-Nash equilibrium solution is used as the optimal weight of each objective function, thereby obtaining the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; the comprehensive objective value f is expressed as follows:

[0062] f=ω 1 f 1 +ω 2 f 2 +ω 3 f 3

[0063] In the formula, ω 1 ,ω 2 ,ω 3 They are respectively the reactive power demand objective function f of the main distribution network 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The optimal weight of .

[0064] The present invention also proposes a main distribution network reactive power joint optimization system based on game theory, comprising:

[0065] An indicator building module, used to build reactive power demand level indicators;

[0066] Scenario construction module, used to construct a variety of typical fault scenarios based on reactive power demand level indicators;

[0067] The joint optimization model building module is used to analyze the reactive power demand of the main distribution network under various typical fault scenarios, build a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goals of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function;

[0068] The game module is used to construct a three-objective game model based on the reactive power demand objective function of the main distribution network, the power quality objective function of the main distribution network, and the new energy utilization rate objective function of the distribution network. The Bayesian-Nash equilibrium theory in game theory is used to solve the three-objective game model and obtain the final result of the joint optimization of the reactive power of the main distribution network.

[0069] The present invention also proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the main and distribution network reactive power joint optimization method based on game theory as described above is implemented.

[0070] The present invention also proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the above-mentioned method for joint optimization of reactive power of a main distribution network based on game theory.

[0071] The beneficial effects of the present invention are:

[0072] The present invention constructs a reactive power demand level (RPDL) index to provide a basis for the classification of typical fault scenarios, so as to facilitate the rapid selection of corresponding models and methods for solving; according to the RPDL index, a variety of typical fault scenarios are constructed, including single fault of distribution network, single fault of main network, simultaneous fault of main and distribution network, etc.; a joint optimization model that comprehensively considers the reactive power demand of the main and distribution network is constructed, and the comprehensive maximum goal of power quality, energy utilization rate and economic benefit is achieved through transmission and distribution coordination while ensuring the safe and stable operation of the power grid; the Bayesian-Nash equilibrium theory in game theory is used for solving, and the final result of the joint optimization of reactive power of the main and distribution network is obtained. The stability and economic benefits of the power grid are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a flow chart of the method for joint optimization of reactive power of main and distribution networks based on game theory of the present invention;

[0074] Figure 2 It is a flow chart for solving the three-objective game model of the present invention. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0076] Embodiment 1

[0077] The present invention proposes a method for joint optimization of main and distribution network reactive power based on game theory. The overall process is as follows: Figure 1 As shown, the following steps are included:

[0078] S1. Construct reactive power demand level (RPDL) indicators; provide a basis for the classification of typical fault scenarios, and facilitate the rapid selection of corresponding models and methods for solving; S1 specifically includes:

[0079] S11, build the main network (MainNetwork) reactive power demand level (MN-RPDL) indicator, S11 is specifically:

[0080] Construct the main network reactive power demand level indicator as follows:

[0081]

[0082] In the formula, α MN The reactive power demand level value of the main network; Q D，MN The reactive power required after a main network failure. When the value is 0, it means there is no failure and the network is operating normally. R，MN The reactive power reserve owned by the main grid.

[0083] S12: Construct the distribution network reactive power demand level (DN-RPDL) indicator. S12 is specifically:

[0084] Construct the distribution network reactive power demand level indicator as follows:

[0085]

[0086] In the formula, α DN Q is the reactive power demand level value of the distribution network; D，DN It is the reactive power required after the distribution network fails. When its value is 0, it means there is no failure and the network is operating normally. R，DN It is the reactive power reserve of the distribution network.

[0087] S13, construct the comprehensive reactive power demand level index of the main grid and distribution network, S13 is specifically:

[0088] Combined with the main grid reactive power demand level index α MN And distribution network reactive power demand level index α DN , construct the comprehensive reactive power demand level index of the main grid and distribution network, namely the RPDL index, as shown below:

[0089] a RPDL =(a MN ,a DN )

[0090] The RPDL indicator is a two-dimensional array, and each number has three values: 0, 1, and 2, for a total of 9 values.

[0091] S2. According to the reactive power demand level index, construct a variety of typical fault scenarios; specifically:

[0092] When the RPDL index is (0, 0), it means that the power grid has no faults and has been operating stably;

[0093] When the RPDL index is (0, 1), it means that the main network has no faults, but the distribution network has a minor fault. In this case, the reactive power reserve of the distribution network provides sufficient reactive power for the regulation of the distribution network, and the reactive power is directly compensated on-site, so that the power grid maintains stable operation;

[0094] When the RPDL index is (0, 2), it means that the main network has no faults, but a major fault has occurred in the distribution network. In this case, the reactive power reserve of the distribution network is not enough to support the stable operation of the distribution network. It is necessary to use the reactive power reserve of the main network to provide corresponding assistance to the distribution network while ensuring the stable operation of the main network;

[0095] When the RPDL index is (1, 0), it means that a minor fault occurred in the main grid, but no fault occurred in the distribution grid. In this case, the reactive power reserve of the main grid provides sufficient reactive power for the regulation of the main grid, and the power grid maintains stable operation;

[0096] When the RPDL index is (1, 1), it means that both the main grid and the distribution grid have a minor fault. In this case, the reactive power reserves of the main grid and the distribution grid each provide sufficient reactive power for the regulation of their own networks, divide and conquer, do not interfere with each other, and the power grid maintains stable operation;

[0097] When the RPDL index is (1, 2), it means that a minor fault has occurred in the main network and a major fault has occurred in the distribution network. In this case, the reactive power reserve of the main network first provides sufficient reactive power for the regulation of the main network, and then uses the remaining reactive power reserve of the main network to provide corresponding assistance to the distribution network;

[0098] When the RPDL index is (2, 0), it means that a major fault has occurred in the main network, but no fault has occurred in the distribution network. In this case, the reactive power reserve of the main network is not enough to support the stable operation of the main network. All reactive power reserves of the distribution network are gathered to provide corresponding assistance to the main network.

[0099] When the RPDL index is (2, 1), it means that a major fault has occurred in the main network and a minor fault has occurred in the distribution network. In this case, the reactive power reserve of the main network is not enough to support the stable operation of the main network. All reactive power reserves of the distribution network are collected to provide corresponding assistance to the main network. The distribution network will be considered after the main network is stable.

[0100] When the RPDL index is (2, 2), it means that both the main network and the distribution network have major faults. The probability of this happening is extremely small. In order to ensure the stability of the power grid, regardless of cost, the fastest on-site compensation is taken to ensure the safety of the power grid.

[0101] S3. Analyze the reactive power demand of the main distribution network under various typical fault scenarios, construct a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goal of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization objective function.

[0102] The reactive power demand objective function f of the main distribution network 1 , as shown below:

[0103] f 1 =min{max(Q MN ,Q DN1 ,Q DN2 ,...,Q DNi )}

[0104] In the formula, Q DNi is the reactive power demand when the ith distribution network fails; Q MN The reactive power demand when the main grid fails; the main distribution network reactive power demand objective function as a whole represents the minimization of the reactive power reserve provided by the additional equipment required under the most serious fault, i.e. the scenario with the largest reactive power demand, through the coordinated optimization of transmission and distribution;

[0105] The power grid should ensure the quality of the output power while ensuring the stability of power transmission. Power quality includes voltage deviation, frequency deviation, harmonic content and other aspects. The present invention focuses on voltage deviation and frequency deviation. The main distribution network power quality objective function f 2 As shown below:

[0106]

[0107] In the formula, z MN The power quality of the main grid, The average value of the power quality of the main grid plus all distribution grids, N is the number of distribution grids; i is the power quality of the ith distribution network, V ai is the actual voltage of the ith distribution network; V ni is the rated voltage of the ith distribution network; f ai is the actual frequency of the ith distribution network; f ni is the rated frequency of the ith distribution network; V is the weight coefficient of voltage deviation in power quality, λ f is the weight coefficient of frequency deviation in power quality, λ V +λ f =1;

[0108] With the incorporation of a large number of distributed wind power and distributed photovoltaic power generation into the distribution network, in order to give full play to the value of these new energy sources, when reactive power compensation is needed, priority will be given to the reactive power they generate. At the same time, variance calculation is introduced. The distribution network new energy utilization rate objective function f 3 As shown below:

[0109]

[0110] Where N is the number of distribution networks, h i is the utilization rate of new energy in the i-th distribution network; is the average value of the renewable energy utilization rate of all distribution networks; a DN is the reactive power demand level value of the distribution network, Q D,DN is the reactive power required after the distribution network fails, m i is the proportion of reactive power demand of the ith distribution network used to support the main network; a MN is the reactive power demand level value of the main network, Q D,MN is the reactive power required after the main network fails, Q NEWi It is the reactive power reserve brought by the renewable energy power generation in the i-th distribution network.

[0111] S4. Construct a three-objective game model based on the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization objective function, and use the Bayesian-Nash equilibrium theory in game theory to solve the three-objective game model and obtain the final result of the main distribution network reactive power joint optimization. Specifically include:

[0112] S41. Establish a strategy set based on the strategies that may be selected according to the reactive demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function. According to whether there is cooperation between the objective functions, the strategy set S is recorded as S = {S1 = 0.25, S2 = 0.75}; S1 represents the penalty strategy and S2 represents the cooperation strategy;

[0113] S42, assigning a value to the friendship matrix FD at the initial moment; as shown below:

[0114]

[0115] In the formula, λ aa is the friendliness of the objective function a to itself, λ ab is the friendliness of objective function a to objective function b; a=1,2,3; b=1,2,3; a≠b, a and b represent the serial numbers of the objective functions;

[0116] S43. Use the friendship matrix to obtain the benefit values ​​of all strategies to satisfy the Bayesian-Nash equilibrium. The calculation formula of the benefit value is as follows:

[0117] U a-c-d-e =λ1a u 1a +λ 2a u 2a +λ 3a u 3a

[0118] Where U a-c-d-e It represents the objective function of the utilization rate of new energy in the distribution network f 3 Taking strategy c, the main distribution network power quality objective function f 2 Taking strategy d, the main distribution network reactive power demand objective function f 1 The total benefit value obtained by the ath objective function when strategy e is adopted; c, d, e∈{1, 2}, where 1 represents a penalty strategy and 2 represents a cooperative strategy; u 1a ,u 2a ,u 3a They are respectively the reactive power demand objective function f of the main distribution network 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The benefit of the strategy adopted for the ath objective function, λ 1a ,λ 2a ,λ 3a They are respectively the objective function main distribution network reactive power demand objective function f 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The friendliness of the adopted strategy to the ath objective function.

[0119] S44, using the benefit values ​​of all strategies to solve the optimal strategy for all objective functions, obtain the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration, and use this optimal Bayesian-Nash equilibrium solution as the optimal weight of each objective function, so as to obtain the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; S44 is specifically:

[0120] Calculate the penalty strategy S for all objective functions according to the following formula 1 and cooperation strategy 2 Expected total return:

[0121]

[0122] In the formula, is the ath objective function f a Punishment strategy S 1 Expected total return; is the ath objective function f a Cooperation strategy 2 The expected total return of5 and λ 6 is the weight coefficient, is the ath objective function f a The other two objective functions choose the penalty strategy S 1 When the ath objective function f a Expected earnings; is the ath objective function f a Among the two objective functions other than 1 , another objective function selects the cooperation strategy S 2 When the ath objective function f a Expected earnings; is the ath objective function f a Among the two objective functions other than 2 , another objective function selects the penalty strategy S 1 When the ath objective function f a Expected earnings; is the ath objective function f a The other two objective functions choose the cooperative strategy S 2 When the ath objective function f a expectation of earnings.

[0123] and The calculation method is as follows:

[0124]

[0125] In the formula, λ 1 and λ 2 is the weight coefficient, U a-1-1-1 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting the penalty strategy, the power quality objective function of the main distribution network is f 2 Adopting the penalty strategy, the reactive power demand objective function f 1 When adopting the penalty strategy, the ath objective function f a The total benefit value obtained, U a-1-1-2 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting the penalty strategy, the power quality objective function of the main distribution network is f 2 Adopting the penalty strategy, the reactive power demand objective function f 1 When adopting the cooperative strategy, the ath objective function f a The total benefit value obtained, U a-1-2-1 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting the penalty strategy, the power quality objective function of the main distribution network is f 2Adopting the cooperative strategy, the reactive power demand objective function f of the main distribution network is 1 When adopting the penalty strategy, the ath objective function f a The total benefit value obtained, U a-1-2-2 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting the penalty strategy, the power quality objective function of the main distribution network is f 2 Adopting the cooperative strategy, the reactive power demand objective function f of the main distribution network is 1 When adopting the cooperative strategy, the ath objective function f a The total revenue value obtained.

[0126] and The calculation method is as follows:

[0127]

[0128] In the formula, λ 3 and λ 4 is the weight coefficient, U a-2-1-1 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting a cooperative strategy, the power quality objective function of the main distribution network is f 2 Adopting the penalty strategy, the reactive power demand objective function f 1 When adopting the penalty strategy, the ath objective function f a The total benefit value obtained, U a-2-1-2 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting a cooperative strategy, the power quality objective function of the main distribution network is f 2 Adopting the penalty strategy, the reactive power demand objective function f 1 When adopting the cooperative strategy, the ath objective function f a The total benefit value obtained, U a-2-2-1 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting a cooperative strategy, the power quality objective function of the main distribution network is f 2 Adopting the cooperative strategy, the reactive power demand objective function f of the main distribution network is 1 When adopting the penalty strategy, the ath objective function f a The total benefit value obtained, U a-2-2-2 It represents the objective function of the utilization rate of new energy in the distribution network f 3 Adopting a cooperative strategy, the power quality objective function of the main distribution network is f 2 Adopting the cooperative strategy, the reactive power demand objective function f of the main distribution network is 1 When adopting the cooperative strategy, the ath objective function f a The total revenue value obtained.

[0129] The expected total return from the two strategies and The strategy with the larger value in is the optimal strategy; the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration is obtained, and this optimal Bayesian-Nash equilibrium solution is used as the optimal weight of each objective function, so as to obtain the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; the comprehensive objective value f is expressed as follows:

[0130] f=ω 1 f 1 +ω 2 f 2 +ω 3 f 3

[0131] In the formula, ω 1 ,ω 2 ,ω 3 They are respectively the reactive power demand objective function f of the main distribution network 1 , the main distribution network power quality objective function f 2 , distribution network new energy utilization rate objective function f 3 The optimal weight of .

[0132] S45, verify whether the iteration number requirement is met, if so, proceed to step S46, otherwise update the friendship matrix and repeat steps S43 and S44;

[0133] The update friendliness matrix is ​​specifically:

[0134] If the strategy of objective function a brings positive benefits to objective function b, then the friendliness of objective function a to objective function b will increase; if the strategy of objective function a brings negative benefits to objective function b, then the friendliness of objective function a to objective function b will decrease. The formula is as follows:

[0135]

[0136] In the formula, u ab represents the benefit that the strategy of the ath objective function brings to the bth objective function, λ ab Indicates the friendliness of the a-th objective function to the b-th objective function;

[0137] S46. Give the optimization result of the three-objective game model as the optimization result of the reactive power reserve demand of the whole system.

[0138] Embodiment 2

[0139] The present invention proposes a main distribution network reactive power joint optimization system based on game theory corresponding to the method of embodiment 1, comprising:

[0140] An indicator building module, used to build reactive power demand level indicators;

[0141] Scenario construction module, used to construct a variety of typical fault scenarios based on reactive power demand level indicators;

[0142] The joint optimization model building module is used to analyze the reactive power demand of the main distribution network under various typical fault scenarios, build a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goals of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function;

[0143] The game module is used to construct a three-objective game model based on the reactive power demand objective function of the main distribution network, the power quality objective function of the main distribution network, and the new energy utilization rate objective function of the distribution network. The Bayesian-Nash equilibrium theory in game theory is used to solve the three-objective game model and obtain the final result of the joint optimization of the reactive power of the main distribution network.

[0144] The implementation methods of each module and module function in the system are completely consistent with the steps of the method in Example 1, so they will not be repeated here.

[0145] Embodiment 3

[0146] The present invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for joint optimization of reactive power of a main distribution network based on game theory as described in Example 1 is implemented.

[0147] Embodiment 4

[0148] The present invention proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the method for joint optimization of reactive power of a main distribution network based on game theory as described in the first embodiment.

[0149] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0150] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0151] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A method for joint optimization of reactive power of main and distribution networks based on game theory, characterized in that: The following steps are involved: S1. Construct reactive power demand level index; S2. Construct a variety of typical fault scenarios based on reactive power demand level indicators; S3. Analyze the reactive power demand of the main distribution network under various typical fault scenarios, build a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goal of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; S4. Construct a three-objective game model based on the reactive power demand objective function of the main distribution network, the power quality objective function of the main distribution network and the new energy utilization rate objective function of the distribution network. Use the Bayesian-Nash equilibrium theory in game theory to solve the three-objective game model and obtain the final result of the joint optimization of the reactive power of the main distribution network.

2. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 1, characterized in that: The reactive power demand level index is specifically constructed as follows: Construct the main network reactive power demand level indicator as follows: In the formula, a MN The reactive power demand level value of the main network; Q D,MN The reactive power required after a main network failure. When the value is 0, it means there is no failure and the network is operating normally. R,MN Reactive power reserve for the main grid; Construct the distribution network reactive power demand level indicator as follows: In the formula, a DN Q is the reactive power demand level value of the distribution network; D,DN It is the reactive power required after the distribution network fails. When its value is 0, it means there is no failure and the network is operating normally. R,DN Reactive power reserve owned by the distribution network; Combined with the main grid reactive power demand level index a MN And distribution network reactive power demand level index a DN , construct the comprehensive reactive power demand level index a of the main grid and distribution network RPDL , as shown below: a RPDL =(a MN ,a DN ) The comprehensive reactive power demand level index of the main grid and distribution network is a two-dimensional array, and each number has three values: 0, 1, and 2, for a total of 9 values.

3. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 1, characterized in that: S2 is specifically: When the comprehensive reactive power demand level index of the main grid distribution network is (0, 0), it means that there is no fault in the power grid; When the comprehensive reactive power demand level index of the main network and distribution network is (0, 1), it means that there is no fault in the main network and a slight fault occurs in the distribution network; When the comprehensive reactive power demand level index of the main network and distribution network is (0, 2), it means that there is no fault in the main network, but a major fault has occurred in the distribution network; When the comprehensive reactive power demand level index of the main network and distribution network is (1, 0), it means that a minor fault has occurred in the main network, but no fault has occurred in the distribution network; When the comprehensive reactive power demand level index of the main network and distribution network is (1, 1), it means that both the main network and the distribution network have minor faults; When the comprehensive reactive power demand level index of the main network and distribution network is (1, 2), it means that a minor fault has occurred in the main network and a major fault has occurred in the distribution network; When the comprehensive reactive power demand level index of the main network and distribution network is (2, 0), it means that a major fault has occurred in the main network, but no fault has occurred in the distribution network; When the comprehensive reactive power demand level index of the main network and distribution network is (2, 1), it means that a major fault has occurred in the main network and a minor fault has occurred in the distribution network; When the comprehensive reactive power demand level index of the main grid and distribution network is (2, 2), it means that major faults have occurred in both the main grid and the distribution network.

4. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 1, characterized in that: In S3, the main distribution network reactive power demand objective function f1 is as follows: f1=min{max(Q MN ,Q DN1 ,Q DN2 ,...,Q DNi )} In the formula, Q DNi is the reactive power demand when the ith distribution network fails; Q MN The reactive power demand when the main grid fails; the overall objective function of the reactive power demand of the main distribution network represents the minimization of the reactive power reserve provided by the additional equipment required in the scenario with the maximum reactive power demand through the coordinated optimization of transmission and distribution; The main distribution network power quality objective function f2 is as follows: In the formula, z MN The power quality of the main grid, The average value of the power quality of the main grid plus all distribution grids, N is the number of distribution grids; i is the power quality of the ith distribution network, V ai is the actual voltage of the ith distribution network; V ni is the rated voltage of the ith distribution network; f ai is the actual frequency of the ith distribution network; f ni is the rated frequency of the ith distribution network; l V is the weight coefficient of voltage deviation in power quality, l f is the weight coefficient of frequency deviation in power quality, l V +l f =1; The distribution network new energy utilization rate objective function f3 is as follows: Where N is the number of distribution networks, h i is the utilization rate of new energy in the i-th distribution network; is the average value of the renewable energy utilization rate of all distribution networks; a DN is the reactive power demand level value of the distribution network, Q D,DN is the reactive power required after the distribution network fails, m i is the proportion of reactive power demand of the ith distribution network used to support the main network; a MN is the reactive power demand level value of the main network, Q D,MN is the reactive power required after the main network fails, Q NEWi It is the reactive power reserve brought by the renewable energy power generation in the i-th distribution network.

5. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 1, characterized in that: S4 specifically includes: S41. Establish a strategy set based on the strategies that may be selected according to the reactive demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function. According to whether there is cooperation between the objective functions, the strategy set S is recorded as S = {S1 = 0.25, S2 = 0.75}; S1 represents the penalty strategy and S2 represents the cooperation strategy; S42, assigning a value to the friendship matrix FD at the initial moment; as shown below: In the formula, l aa is the friendliness of the objective function a to itself, l ab is the friendliness of objective function a to objective function b; a=1,2,3; b=1,2,3; a≠b, a and b represent the serial numbers of the objective functions; S43. Use the friendship matrix to obtain the payoff values ​​of all strategies to satisfy the Bayesian-Nash equilibrium; S44, using the benefit values ​​of all strategies to solve the optimal strategy for all objective functions, obtain the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration, and use this optimal Bayesian-Nash equilibrium solution as the optimal weight of each objective function, so as to obtain the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; S45, verify whether the iteration number requirement is met, if so, proceed to step S46, otherwise update the friendship matrix and repeat steps S43 and S44; The update friendliness matrix is ​​specifically: If the strategy of objective function a brings positive benefits to objective function b, then the friendliness of objective function a to objective function b will increase; if the strategy of objective function a brings negative benefits to objective function b, then the friendliness of objective function a to objective function b will decrease. The formula is as follows: In the formula, u ab represents the benefit that the strategy of the ath objective function brings to the bth objective function, l ab Indicates the friendliness of the a-th objective function to the b-th objective function; S46. Give the optimization result of the three-objective game model as the optimization result of the reactive power reserve demand of the whole system.

6. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 5, characterized in that: In S43, the benefit values ​​of all strategies are obtained by using the friendship matrix as follows: The formula for calculating the revenue value is as follows: And a-c-d-e =l 1a and 1a +l 2a and 2a +l 3a and 3a Where U a-c-d-e It represents the total benefit value obtained by the ath objective function when the distribution network renewable energy utilization rate objective function f3 adopts strategy c, the main distribution network power quality objective function f2 adopts strategy d, and the main distribution network reactive power demand objective function f1 adopts strategy e; c, d, e ∈ {1, 2}, where 1 represents the penalty strategy and 2 represents the cooperation strategy; u 1a ,u 2a ,u 3a They are the main distribution network reactive power demand objective function f1, the main distribution network power quality objective function f2, and the distribution network new energy utilization rate objective function f3. The benefits of the strategy adopted for the ath objective function are: 1a , l 2a , l 3a They are respectively the objective function main distribution network reactive power demand objective function The friendliness of the strategy adopted by the objective function f1, the main distribution network power quality objective function f2, and the distribution network new energy utilization rate objective function f3 to the ath objective function.

7. The method for joint optimization of reactive power of main and distribution networks based on game theory as claimed in claim 5, characterized in that: S44 is specifically: The expected total benefits of all objective functions for the punishment strategy S1 and the cooperation strategy S2 are calculated as follows: In the formula, is the ath objective function f a The expected total payoff for the punishment strategy S1; is the ath objective function f a The expected total benefit of the cooperation strategy S2; λ5 and λ6 are weight coefficients, is the ath objective function f a When the two objective functions other than a Expected earnings; is the ath objective function f a When one objective function chooses the penalty strategy S1 and the other objective function chooses the cooperation strategy S2, the ath objective function f a Expected earnings; is the ath objective function f a Among the two objective functions other than a Expected earnings; is the ath objective function f a When the two objective functions other than a Expected earnings; The strategy with the larger expected total benefit obtained from the two strategies is the optimal strategy; the multi-objective optimal Bayesian-Nash equilibrium solution of this iteration is obtained, and this optimal Bayesian-Nash equilibrium solution is used as the optimal weight of each objective function, thereby obtaining the comprehensive objective value of the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; the comprehensive objective value f is expressed as follows: f=ω1f1+ω2f2+ω3f3 Where ω1, ω2, and ω3 are the optimal weights of the main distribution network reactive power demand objective function f1, the main distribution network power quality objective function f2, and the distribution network new energy utilization rate objective function f3, respectively.

8. A main distribution network reactive power joint optimization system based on game theory, characterized in that: include: An indicator construction module, used to construct reactive power demand level indicators; Scenario construction module, used to construct a variety of typical fault scenarios based on reactive power demand level indicators; The joint optimization model building module is used to analyze the reactive power demand of the main distribution network under various typical fault scenarios, build a joint optimization model that takes reactive power demand into consideration, and achieve the comprehensive maximum goals of power quality, new energy utilization rate and economic benefits through transmission and distribution coordination; the joint optimization model includes the main distribution network reactive power demand objective function, the main distribution network power quality objective function and the distribution network new energy utilization rate objective function; The game module is used to construct a three-objective game model based on the reactive power demand objective function of the main distribution network, the power quality objective function of the main distribution network, and the new energy utilization rate objective function of the distribution network. The Bayesian-Nash equilibrium theory in game theory is used to solve the three-objective game model and obtain the final result of the joint optimization of the reactive power of the main distribution network.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for joint optimization of reactive power of a main distribution network based on game theory as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the main and distribution network reactive power joint optimization method based on game theory as described in any one of claims 1 to 7.

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