CN111476423A - Energy interconnected distribution network fault recovery method - Google Patents
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Abstract
The invention relates to a fault recovery method for an energy interconnection power distribution network, which is characterized in that a model for carrying out dynamic game by using a switching state and a system optimized operation plan in a fault recovery decision as decision makers with different status is established, aiming at the fault recovery problem of the energy interconnection power distribution network under multi-energy complementary coordination, according to the status difference of control variables in the model, the switching state variable formulation and the system operation plan adjustment are used as different decision main bodies, a master-slave game theory is adopted for carrying out modeling, the strategies of a main game player and a slave game player are mutually influenced and coupled, and the switching state set of the system and the optimized operation plan adjustment are formulated through a game process, so that the fault recovery scheme for the energy interconnection power distribution network is higher in reliability and better.
Description
Technical Field
The invention belongs to the field of fault recovery of an energy interconnected power distribution network, and particularly relates to a fault recovery method of an energy interconnected power distribution network.
Background
The energy internet emphasizes comprehensive complementary utilization among various energy forms, but compared with other energy forms, the electric energy has characteristics of instantaneous generation and instantaneous supply, so the energy internet is an energy ecosystem which takes the electric energy as a main body form and takes a smart grid as a main carrier in the future. As an important form and a component module of the energy Internet, the energy interconnection power distribution network is a wider distributed interconnection system. The energy interconnection power distribution network is a regional performance balance system which takes a power system as a center, realizes multi-source complementation of electricity, gas, heat, renewable energy and the like in a transverse mode and realizes high coordination of each link of source network charge storage in a longitudinal mode by means of information equipment. The energy interconnection distribution network deeply couples energy flow, information flow and service flow to form a brand new energy system and form an innovative form of energy application.
At present, a lot of researches are carried out on the fault recovery problem of the power distribution network, on one hand, the researches emphasize that a fault recovery model is established aiming at the specific operating environment and condition of the power distribution network, such as the establishment of a power distribution network fault recovery model based on a grade preference sequence method and load shedding, a power distribution network fault recovery model containing photovoltaic power generation grid connection considering the uncertainty of photovoltaic output, an interval number grey correlation decision method for power distribution network fault recovery and the like; on the other hand, the method focuses on and seeks an efficient solving algorithm for the fault recovery model, such as a heuristic search method, a genetic algorithm, a tabu search algorithm, an ant colony algorithm, a multi-agent theory and other intelligent optimization methods. However, at present, less reasonable methods are provided for the fault recovery problem of the energy interconnection power distribution network, the fault recovery of the energy interconnection power distribution network is a multi-objective and multi-constraint nonlinear optimization problem, and the recovery strategy formulation needs to comprehensively consider the multi-energy complementary coordination among a plurality of energy subnets.
Disclosure of Invention
The invention aims to provide a fault recovery method for an energy interconnection power distribution network.
The technical scheme of the invention is as follows:
a fault recovery method for an energy interconnection power distribution network is characterized in that a switching state and a system optimized operation plan in a fault recovery decision are used as decision makers with different statuses to carry out dynamic game, aiming at the fault recovery problem of the energy interconnection power distribution network under multi-energy complementary coordination, switching state variable formulation and system operation scheme adjustment are used as different decision main bodies according to the difference of control variable statuses in the model, a master-slave game theory is adopted to carry out modeling, strategies of a main game player and a slave game player are mutually influenced and coupled, and the fault recovery of the energy interconnection power distribution network is realized through the switching state set and the optimized operation plan adjustment of the game process formulation system.
Further, the method specifically comprises the following steps:
(1) establishing a fault recovery model framework of the energy interconnection power distribution network based on a master-slave game theory;
(2) establishing a main player model;
(3) establishing a slave player model;
(4) and establishing master-slave game balance points.
Further, in the energy interconnection power distribution network fault recovery model architecture based on the principal and subordinate game theory in the step (1), a principal player serves as a fault recovery module, a game strategy is a switching state set, game payment is system power loss load, reliable power supply is taken as a target, and the established switching state set of the system after the fault occurs is a basis for establishing a strategy by the principal player; and the slave gambler adjusts the optimized operation plan of the system by taking the minimum comprehensive operation cost of the system as the gambling payment on the premise of the switching state set provided by the master gambler, takes the economic operation as a target, and feeds back the power-off load index of the system under the strategy to the master gambler. The strategies of the main player and the subordinate player are mutually influenced and coupled, and the main player indirectly determines the game payment through influencing the strategy of the subordinate player through the strategy of the main player, and the main player is in a dominant position in the whole game process.
Further, the subject gambler model includes gambling strategies and payouts and gambling constraints.
Further, the gaming strategy and payout in the subject gambler model are:
the main player in the fault recovery decision is the system fault recovery center, and the game strategy S thereof1Writing a strategy set of a game main body into a mathematical form shown in a formula (1) for a switching state in an energy interconnection power distribution network;
S1＝[g(1),g(2),…,g(i),…,g(N)](1)
wherein g (i) is the position state of the switch i, and when g (i) is 1, the switch i is in-position, and when g (i) is 0, the switch i is in-position;
paying of the main gambler to minimize the power loss load power within the fault duration is as shown in the formula (2);
wherein T is the number of fault duration periods; u. of1Paying for the game; n is the number of load nodes, r, of the energy interconnected distribution networkj(t) whether the load interruption is carried out on the jth load node in the tth time period after recovery, rjWhen (t) is 1, it indicates that an interrupt is performed, rjWhen (t) is 0, no interruption is performed; c. CjRepresenting the importance degree weight of the jth load node; pj(t) represents the load interruption power of the jth load node during the tth period.
Further, the game constraint conditions in the main player model comprise power distribution network topology constraint, node voltage constraint, branch capacity constraint and switch operation time constraint.
Further, the slave gambler model comprises a gambling strategy and payment and gambling constraints.
Further, the game strategy and payment in the slave player model are as follows:
the slave game player is an energy interconnection power distribution network optimization operation module, and the strategy set of the slave game player is an operation plan of the system in the fault duration period. The strategy set is shown as formula (3):
S2＝[PSB,PEX,HIN,HX,PMT,GIN,GS,PFC,PV](3)
wherein S is2Set of policies for slave gamblers, PSB，PEX，HIN，HX，PMT，GIN，GS，PFC，PVRespectively providing an electric energy storage charging and discharging power plan in an energy interconnection power distribution network, an outer network purchasing and selling power plan, a heat energy outer network purchasing power plan, an energy storage device charging and discharging plan, a combined cooling, heating and power supply micro-combustion engine output plan, an outer network input natural gas amount plan, a gas storage tank charging and discharging plan, a fuel cell output plan and an electric vehicle charging and discharging power plan;
payout from the body gambler is to minimize the system operating cost for the duration of the failure, as shown in equation (4):
wherein u is2Paying for slave game player, T is number of scheduling time segments in fault duration, △ T is length of operation time segment, fMT() And fFC() Fuel cost curves, P, for MT and FC, respectivelyMT(t) and PFC(t) generated powers for t periods MT and FC, respectively; ploss(t) the system electric power loss in a period t; f. ofOM,i() Is the operation and maintenance cost function of the equipment i, K is the number of the equipment, Pi(t) is the operating power of device i during time t; pEX(t) the power of purchasing and selling electricity of the system and the external network in a period t; q (t) is the time-of-use electricity price of the external network in the period t; n is a contaminant speciesCounting;
and
emission coefficients of MT and FC theta pollutants, cθAn environmental cost reduction factor for the theta pollutant; f is a subsidy coefficient of the government to photovoltaic power generation; pPV(t) the photovoltaic power generation output in the period of t, β the load interruption compensation coefficient, Pcut(t) load interruption power for a period of t; hIN(t) heat purchasing power from the heat energy sub-network to the external network, p, during a period of thFor the heat purchase cost coefficient; gIN(t) the gas purchasing power of the gas energy sub-network to the external network in the period of t, cNGIs the natural gas price.
Further, the game constraint conditions in the slave game player model comprise an electric energy sub-network operation constraint, a thermal energy sub-network operation constraint, a gas energy sub-network operation constraint and a traffic sub-network electric vehicle charging strategy adjustment constraint.
Further, the master-slave game comprehensive model is shown as formula (5):
G＝{N；S1,S2；u1,u2} (5)
wherein N ═ {1,2} represents a set of participants in the game, including subject and slave gamblers; s ═ S1,S2Is the strategy set of the gambler, u ═ u1,u2The payment set of the gamblers is; wherein, there are u1＝u1(x, y) and u2＝u2(x, y) and x ∈ S1And y ∈ S2；
When the subject player selects strategy x ∈ S1Then, the response set of the slave gambler to the strategy is shown as the formula (6):
wherein, K (x) is the response set of the slave gambler to the strategy x of the master gambler; the slave gambler will select a strategy from k (x);
the main player knows the answer set of the slave player, so the slave player will adjust its own strategy to x*∈S1So that the formula (7) is established;
selection strategy x for subject gambler*∈S1Next, the slave gambler will select policy y*∈K(x*) Then called (x)*,y*) The Nash balance points are Nash balance points of the master-slave game; outside the equilibrium point for
All have u1(x*,y*)≤u1(x, y) for
All have u2(x*,y*)≤u2(x*,y)。
The invention has the advantages that:
aiming at the problem of fault recovery of the energy interconnection power distribution network, the reliability and the economy of the fault recovery of the power distribution network are considered by adopting a master-slave game model, the switching state set and the system optimization operation plan adjustment are taken as decision variables of different positions, the established method simultaneously considers the formulation of the system switching state set and the support of the adjustment of the multi-energy complementary coordination optimization operation scheme on the fault recovery scheme, the method can be suitable for the formulation of the fault recovery scheme of the energy interconnection power distribution network, the optimal scheme is ensured, compared with the traditional power distribution network scheme, the method can further reduce the power loss load and the comprehensive operation cost, the system operation reliability is improved, and the system operation economy is also improved.
Drawings
Fig. 1 is a fault recovery model architecture of an energy interconnection power distribution network based on a master-slave game theory.
Detailed Description
1. An energy interconnection power distribution network fault recovery model architecture based on a principal and subordinate game theory is established, and is shown in figure 1.
In fig. 1, a main player serves as a fault recovery module, a game strategy of the main player is a switch state set, game payment is a system power-off load, and the established switch state set of the system after a fault occurs is a basis for establishing a strategy by the main player; and the slave gambler adjusts the optimized operation plan of the system by taking the minimum comprehensive operation cost of the system as the gambling payment on the premise of the switching state set provided by the master gambler, and feeds back the power-off load index of the system under the strategy to the master gambler. The strategies of the main player and the subordinate player are mutually influenced and coupled, and the main player indirectly determines the game payment through influencing the strategy of the subordinate player through the strategy of the main player, and the main player is in a dominant position in the whole game process.
2. Principal gambler model
2.1 Game policy and Payment
The main player in the fault recovery decision is the system fault recovery center, and the game strategy S thereof1For the switching state in the energy interconnection power distribution network, the strategy set of the game main body is written into a mathematical form as shown in a formula (1).
S1＝[g(1),g(2),…,g(i),…,g(N)](1)
Where g (i) is the position state of the switch i, and g (i) is 1, and g (i) is 0, and g (i) is a switch i bit.
The payout of the subject gambler is the minimum power loss load power to minimize the fault duration, and is shown in equation (2).
Wherein T is the number of fault duration periods; u. of1Paying for the game; n is the number of load nodes, r, of the energy interconnected distribution networkj(t) whether the load interruption is carried out on the jth load node in the tth time period after recovery, rjWhen (t) is 1, it indicates that an interrupt is performed, rjWhen (t) is 0, no interruption is performed; c. CjRepresenting the importance degree weight of the jth load node; pj(t) represents the load interruption power of the jth load node during the tth period.
2.2 Game constraints
2.2.1 Power distribution network topology constraints
When a main player prepares a switch state change set, radial constraint of a topological structure of a power distribution network needs to be met, and the constraint is shown as a formula (3).
g∈G (3)
And g is a topological structure of the power distribution network after fault recovery, and is formed by formulating a switch state variable by a fault recovery center. G is a distribution network structure set meeting the radial topological structure.
2.2.2 node Voltage constraints
The system after fault recovery needs to satisfy the node voltage constraint as shown in equation (4):
Ui,min≤Ui(t)≤Ui,max,t＝1,…,T (4)
wherein, Ui(t) is the voltage amplitude of the load node i during the t-th period; u shapei,minAnd Ui,maxRespectively, the lower limit and the upper limit of the voltage amplitude of the ith node. The load node voltage in the equation is derived from the system power flow balance constraint that holds true for any fault duration period.
Wherein, PiAnd QiRespectively representing active power and reactive power injected by the ith node, and influenced by the strategy of the slave gambler; gij，BijAndijrespectively, conductance, susceptance, and voltage angle difference of the line between node i and node j. U shapeiAnd UjThe voltage amplitudes of node i and node j, respectively.
2.2.3 Branch Capacity constraints
And (3) obtaining the capacity of each branch of the power distribution network simultaneously through system flow balance, wherein the capacity needs to meet the branch capacity constraint as shown in the formula (7).
Pl≤Pl,max(7)
Wherein, PlActive power of branch l, Pl,maxThe upper capacity limit of branch l.
2.2.4 switch operation times constraint
During fault recovery, the switch will operate frequently in order not to significantly affect the service life of the switch, and the constraint shown in equation (8) needs to be satisfied.
Wherein M is the number of operable switches contained in the power distribution network; rj(t) is whether the switch j has performed the shift operation during the t-th period, and if so, Rj(t) 1 or else Rj(t)＝0；RmaxThe maximum number of operations allowed for the duration of the fault.
3 slave gambler model
3.1 Game policy and Payment
The slave game player is an energy interconnection power distribution network optimization operation module, and the strategy set of the slave game player is an operation plan of the system in the fault duration period. The strategy set is shown in formula (9).
S2＝[PSB,PEX,HIN,HX,PMT,GIN,GS,PFC,PV](9)
Wherein S is2Set of policies for slave gamblers, PSB，PEX，HIN，HX，PMT，GIN，GS，PFC，PVRespectively providing an electric energy storage charging and discharging power plan, an external network electric power purchasing and selling plan, a heat energy external network heat purchasing power plan, an energy storage device heat charging and discharging plan, a combined cooling heating and power supply micro-gas turbine (MT) output plan, an external network natural gas input plan, and a gas storage tank in an energy interconnected power distribution networkA charge and discharge plan, a Fuel Cell (FC) output plan, and an electric vehicle charge and discharge power plan.
Payout from the body gambler is the system operating cost that minimizes the duration of the failure, as shown in equation (10).
Wherein u is2Paying for slave game player, T is number of scheduling time segments in fault duration, △ T is length of operation time segment, fMT() And fFC() Fuel cost curves, P, for MT and FC, respectivelyMT(t) and PFC(t) generated powers for t periods MT and FC, respectively; ploss(t) the system electric power loss in a period t; f. ofOM,i() Is the operation and maintenance cost function of the equipment i, K is the number of the equipment, Pi(t) is the operating power of device i during time t; pEX(t) the power of purchasing and selling electricity of the system and the external network in a period t; q (t) is the time-of-use electricity price of the external network in the period t; n is the number of types of pollutants;
and
emission coefficients of MT and FC theta pollutants, cθAn environmental cost reduction factor for the theta pollutant; f is a subsidy coefficient of the government to photovoltaic power generation; pPV(t) the photovoltaic power generation output in the period of t, β the load interruption compensation coefficient, Pcut(t) load interruption power for a period of t;
HIN(t) heat purchasing power from the heat energy sub-network to the external network, p, during a period of thFor the heat purchase cost coefficient; gIN(t) the gas purchasing power of the gas energy sub-network to the external network in the period of t, cNGIs the natural gas price.
3.2 Game constraints
3.2.1 sub-network of Electrical energy operation constraints
The operation constraint of the electric energy sub-network comprises an electric energy power balance constraint shown as a formula (11) and a micro-power source related operation constraint shown as a formula (12),
wherein, PL(t) is the system electrical load level for a period of t;
charging the load for a time period t after the traffic energy sub-network adopts the charging adjustment strategy.
Wherein, △ PSBThe unit scheduling time interval is used for storing self-consumption electric power, and △ P is providedSB＝△tDSBQSBWherein D isSBIs SB self-discharge coefficient, QSBIs the energy storage capacity; sSB(t) and SSB(t +1) remaining capacity at the end of the periods t and t +1, respectively ηdisAnd ηchDischarge efficiency and charge efficiency, respectively;
△ t is the time period length;
the energy storage charging and discharging minimum value and the energy storage charging and discharging maximum value are respectively.
And
the minimum value and the maximum value of the power generation of the micro-combustion engine are respectively.
And
the minimum value and the maximum value of the generated power of the fuel cell are respectively.
3.2.2 thermal energy sub-network operational constraints
The operation constraints of the heat energy sub-network comprise a heat energy power balance constraint, a cold energy power balance constraint, an energy storage device operation constraint and an external network heat purchasing power constraint as shown in a formula (13).
Wherein, ηMT(t) the power generation efficiency of the micro-combustion engine; cheAnd CcoRespectively representing the heating coefficient and the refrigeration coefficient of the double-effect absorption type unit; phe(t) and Pco(t) thermal load and cold load power levels, respectively, for a period of t; hx(t) the heat charging and discharging power of the energy storage device in the period of t, Hx(t) greater than zero indicates released energy and less than zero indicates absorbed energy; x (t) and X (t-1) are respectively the residual energy of the energy storage device in the t period and the t-1 period, lambdaxη is the energy self-loss coefficient of the energy storage devicexThe heat charge and discharge efficiency is shown; when the energy storage device operates in the heating mode and the cooling mode, the first constraint or the second constraint in the formula is respectively satisfied;
and
the minimum and maximum power of heat is purchased for the heat energy sub-network to the outside network respectively.
3.2.3 gas energy sub-network operational constraints
The operation of the gas energy sub-network needs to meet the natural gas balance constraint, the operation constraint of the gas storage tank and the operation constraint of the gas transmission pipeline as shown in the formula (14).
Wherein G isIN(t) the gas quantity purchased from the system to the outside network in the period t; gs(t) gas release amount of the gas storage tank in time t; gL(t) natural gas load for period t ηFC(t) is the fuel cell power generation efficiency, QLHVIs the heat value of natural gas; qs(t) and Qs(t-1) the residual amount of gas in the gas storage tank in the time period t and the time period t-1 respectively; gs(t) and the amount of gas released from the gas tank, G, at time ts(t) greater than zero indicates deflation;
and
respectively is the minimum value and the maximum value of the gas surplus of the gas storage tank;
and
respectively is the minimum value and the maximum value of the gas release amount of the gas storage tank; gl(t) the gas conveying amount of the first conveying pipeline of the gas network in the period of t;
and
the minimum value and the maximum value of the transported gas quantity of the first transporting pipeline are respectively.
3.2.4 traffic sub-network electric vehicle charging strategy adjustment
Assuming that v (i) is a time period when the electric automobile i needs to be charged, and △ v is the charging duration of the electric automobile, the charging and discharging plan adjustment strategy of the electric automobile in the fault duration state adopted by the traffic sub-network is as follows, for any electric automobile i, if v (i) is less than or equal to T, the charging plan is not adjusted, and if v (i) is more than or equal to T + △ v, the charging load of the electric automobile i is shifted to [ T, T + △ v ]]Within any time period; if T is<v(i)<T + △ v, then the time interval [ v (i) - △ v, T]Charging load in the period [ v (i), T + △ v ] shifted]And (4) the following steps. Assume a charging load after the above adjustment strategy is adopted as
Taking into account power balancing constraints into the electrical energy sub-network.
4, in the master-slave game, the master player knows the strategy of the slave player, and the reaction of the slave player to the strategy is taken into account after the self strategy is prepared, so that the self strategy is further optimized. The master-slave game comprehensive model established by the method can be obtained as shown in a formula (15).
G＝{N；S1,S2；u1,u2} (15)
Wherein N ═ {1,2} represents a set of participants in the game, including subject and slave gamblers; s ═ S1,S2Is the strategy set of the gambler, u ═ u1,u2The payset for the gambler. Wherein, there are u1＝u1(x, y) and u2＝u2(x, y) and x ∈ S1And y ∈ S2。
When the subject player selects strategy x ∈ S1The set of responses from the slave gamblers to the strategy is shown in equation (16).
Wherein, k (x) is the set of responses of the slave gambler to the strategy x of the master gambler. The slave gambler will select a strategy from k (x).
The main player knows the answer set of the slave player, so the slave player will adjust its own strategy to x*∈S1Equation (17) is satisfied.
Selection strategy x for subject gambler*∈S1Next, the slave gambler will select policy y*∈K(x*) Then called (x)*,y*) And the game is the Nash equilibrium point of the master-slave game. At the equilibrium pointOuter pair
All have u1(x*,y*)≤u1(x, y) for
All have u2(x*,y*)≤u2(x*,y)。
The method is characterized in that solving processes of a main player and a slave player are respectively designed based on a chaotic particle swarm algorithm, wherein a main player module is a fault recovery module, and the slave player is an optimized operation module. The main player solving process comprises the following steps:
(1) and inputting a network topology structure and fault information of the energy interconnection power distribution network.
(2) And setting parameters of the chaotic particle swarm algorithm, including inertial weight, learning factors, chaotic search algebra and the like. And initializing the particle population by taking the switch state set as position information.
(3) And detecting whether the fault recovery scheme represented by the initial population meets radial constraint or not, and removing non-conforming individuals.
(4) And calling a solving process of the slave player to obtain the power loss load index corresponding to each particle.
(5) And performing load flow calculation through a system operation scheme fed back by the player of the body game, further obtaining the condition that the constraint condition of the player of the body game is established, and calculating the constraint condition into a target function through a penalty function form to obtain a particle fitness function.
(6) Updating the current global optimal solution, updating the position and the speed of the population, and performing chaotic search on the current global optimal particles in a set range.
(7) If the maximum iteration times is reached, the algorithm is ended, otherwise, whether the global optimal solution is converged is judged. If the convergence is reached, the algorithm finishes outputting the result, otherwise, the algorithm returns to the step (3).
For the main player, the slave player solving process can be called. The solving process of the slave gambler is as follows:
(1) and inputting a network topology structure of the energy interconnection power distribution network and configuration information of energy supply equipment. The subject gambler provides the switch state set information.
(2) And setting parameters of the chaotic particle swarm algorithm, including inertial weight, learning factors, chaotic search algebra and the like. And initializing the particle population for the position information by using the system operation scheme during the fault.
(3) And calculating the operation plan corresponding to each particle by taking the comprehensive operation cost as an objective function, and calculating the constraint condition in a penalty function form to obtain a fitness function.
(4) And updating the global optimal solution, updating the position and the speed of the population, and performing chaotic search on the current global optimal particles in a set range.
(5) If the maximum iteration times is reached, the algorithm is ended, otherwise, whether the global optimal solution is converged is judged. If the result is converged, the algorithm finishes outputting, and the power-loss load index is fed back to the main gambler, otherwise, the step (3) is returned.
Claims (10)
1. A fault recovery method for an energy interconnection power distribution network is characterized in that a switching state and a system optimized operation plan in a fault recovery decision are used as models for decision makers with different status to carry out dynamic games, aiming at the fault recovery problem of the energy interconnection power distribution network under multi-energy complementary coordination, according to the difference of the statuses of control variables in the models, the switching state variable making and the system operation scheme adjustment are used as different decision main bodies, a master-slave game theory is adopted for modeling, strategies of a main game player and a slave game player are mutually influenced and coupled, and the fault recovery of the energy interconnection power distribution network is realized by making a switching state set of the system and optimizing the operation plan adjustment in a game process.
2. The method for recovering the fault of the energy interconnected distribution network according to claim 1, characterized by comprising the following steps:
(1) establishing a fault recovery model framework of the energy interconnection power distribution network based on a master-slave game theory;
(2) establishing a main player model;
(3) establishing a slave player model;
(4) and establishing master-slave game balance points.
3. The method for recovering the fault of the energy interconnection and power distribution network according to claim 2, wherein in the step (1), a main gambler in the fault recovery model architecture of the energy interconnection and power distribution network based on the principal and subordinate gambling theory serves as a fault recovery module, a gambling strategy of the main gambler is a switching state set, gambling payment is a system power loss load, reliable power supply is targeted, and the switching state set of the established system after the fault occurs is a basis for the strategy established by the main gambler; the slave gambler adjusts the optimized operation plan of the system by taking the minimum comprehensive operation cost of the system as the gambling payment on the premise of the switching state set provided by the master gambler, takes the economic operation as a target, and feeds back the power-off load index of the system under the strategy to the master gambler; the strategies of the main player and the subordinate player are mutually influenced and coupled, and the main player indirectly determines the game payment through influencing the strategy of the subordinate player through the strategy of the main player, and the main player is in a dominant position in the whole game process.
4. The method for recovering the fault of the energy interconnection and distribution network as claimed in claim 2, wherein the main player model comprises game strategies and payments and game constraints.
5. The energy interconnection and distribution network fault recovery method according to claim 4, wherein the game strategy and payment in the main player model are as follows:
the main player in the fault recovery decision is the system fault recovery center, and the game strategy S thereof1Writing a strategy set of a game main body into a mathematical form shown in a formula (1) for a switching state in an energy interconnection power distribution network;
S1＝[g(1),g(2),…,g(i),…,g(N)](1)
wherein g (i) is the position state of the switch i, and when g (i) is 1, the switch i is in-position, and when g (i) is 0, the switch i is in-position;
paying of the main gambler to minimize the power loss load power within the fault duration is as shown in the formula (2);
wherein T is the number of fault duration periods; u. of1Paying for the game; n is the number of load nodes, r, of the energy interconnected distribution networkj(t) whether the load interruption is carried out on the jth load node in the tth time period after recovery, rjWhen (t) is 1, it indicates that an interrupt is performed, rjWhen (t) is 0, no interruption is performed; c. CjRepresenting the importance degree weight of the jth load node; pj(t) represents the load interruption power of the jth load node during the tth period.
6. The method for recovering the fault of the energy interconnection distribution network according to claim 4, wherein the game constraint conditions in the main player model comprise distribution network topology constraints, node voltage constraints, branch capacity constraints and switch operation time constraints.
7. The method for recovering the fault of the energy interconnected distribution network as claimed in claim 2, wherein the slave gambler model comprises gambling strategies and payments and gambling constraints.
8. The energy interconnection and distribution network fault recovery method according to claim 7, wherein the gaming strategy and payment in the slave gambler model are as follows:
the slave gambler is an energy interconnection power distribution network optimized operation module, and the strategy set of the slave gambler is an operation plan of the system in the fault duration period; the strategy set is shown as formula (3):
S2＝[PSB,PEX,HIN,HX,PMT,GIN,GS,PFC,PV](3)
wherein S is2Set of policies for slave gamblers, PSB，PEX，HIN，HX，PMT，GIN，GS，PFC，PVRespectively providing an electric energy storage charging and discharging power plan in an energy interconnection power distribution network, an outer network purchasing and selling power plan, a heat energy outer network purchasing power plan, an energy storage device charging and discharging plan, a combined cooling, heating and power supply micro-combustion engine output plan, an outer network input natural gas amount plan, a gas storage tank charging and discharging plan, a fuel cell output plan and an electric vehicle charging and discharging power plan;
payout from the body gambler is to minimize the system operating cost for the duration of the failure, as shown in equation (4):
wherein u is2Paying for slave game player, T is number of scheduling time segments in fault duration, △ T is length of operation time segment, fMT() And fFC() Fuel cost curves, P, for MT and FC, respectivelyMT(t) and PFC(t) generated powers for t periods MT and FC, respectively; ploss(t) the system electric power loss in a period t; f. ofOM,i() Is the operation and maintenance cost function of the equipment i, K is the number of the equipment, Pi(t) is the operating power of device i during time t; pEX(t) the power of purchasing and selling electricity of the system and the external network in a period t; q (t) is the time-of-use electricity price of the external network in the period t; n is the number of types of pollutants;
and
emission coefficients of MT and FC theta pollutants, cθAn environmental cost reduction factor for the theta pollutant; f is a subsidy coefficient of the government to photovoltaic power generation; pPV(t) the photovoltaic power generation output in the period of t, β the load interruption compensation coefficient, Pcut(t) load interruption power for a period of t; hIN(t) heat purchasing power from the heat energy sub-network to the external network, p, during a period of thFor the heat purchase cost coefficient; gIN(t) the gas purchasing power of the gas energy sub-network to the external network in the period of t, cNGIs the natural gas price.
9. The method for recovering the fault of the energy interconnection distribution network according to claim 7, wherein the gaming constraints in the slave gaming person model comprise operation constraints of an electric energy sub-network, operation constraints of a thermal energy sub-network, operation constraints of a gas energy sub-network and adjustment constraints of a charging strategy of an electric vehicle of a transportation sub-network.
10. The method for recovering the fault of the energy interconnection distribution network according to any one of claims 1 to 9, wherein a master-slave game comprehensive model is shown as a formula (5):
G＝{N；S1,S2；u1,u2} (5)
wherein N ═ {1,2} represents a set of participants in the game, including subject and slave gamblers; s ═ S1,S2Is the strategy set of the gambler, u ═ u1,u2The payment set of the gamblers is; wherein, there are u1＝u1(x, y) and u2＝u2(x, y) and x ∈ S1And y ∈ S2；
When the subject player selects strategy x ∈ S1Then, the response set of the slave gambler to the strategy is shown as the formula (6):
wherein, K (x) is the response set of the slave gambler to the strategy x of the master gambler; the slave gambler will select a strategy from k (x);
the main player knows the answer set of the slave player, so the slave player will adjust its own strategy to x*∈S1So that the formula (7) is established;
selection strategy x for subject gambler*∈S1Next, the slave gambler will select policy y*∈K(x*) Then called (x)*,y*) The Nash balance points are Nash balance points of the master-slave game; outside the equilibrium point for
All have u1(x*,y*)≤u1(x, y) for
All have u2(x*,y*)≤u2(x*,y)。
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