CN111476423B - Fault recovery method for energy interconnection power distribution network - Google Patents
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Abstract
The invention relates to a fault recovery method of an energy interconnection power distribution network, which is characterized in that a switching state and a system optimization operation plan in a fault recovery decision are established as models for dynamic games of different position decision makers, aiming at the problem of fault recovery of the energy interconnection power distribution network under the condition of multi-energy complementation coordination, according to the difference of control variable positions in the models, a switching state variable formulation and a system operation scheme are adjusted to serve as different decision bodies, modeling is carried out by adopting a master-slave game theory, strategies of a main game player and a slave game player are mutually influenced and coupled, and the switching state set and the optimization operation plan adjustment of the system are formulated through a game process, so that the reliability of the fault recovery scheme of the energy interconnection power distribution network is higher, and the economy is better.
Description
Technical Field
The invention belongs to the field of fault recovery of an energy interconnection power distribution network, and particularly relates to a fault recovery method of the energy interconnection power distribution network.
Background
The energy internet emphasizes comprehensive complementary utilization among various energy forms, but compared with other energy forms, electric energy has instantaneous and instantaneous supply characteristics, so that the future energy internet is necessarily an energy ecological system taking electric energy as a main body form and taking a smart grid as a main carrier. As an important form and constituent module of the energy internet, the energy interconnection distribution network is a more extensive distributed interconnection system. The energy interconnection distribution network is an regional energy balance system which takes an electric power system as a center, transversely realizes multi-source complementation of electricity, gas, heat, renewable energy sources and the like by means of information equipment and longitudinally realizes high coordination of all links of source network charge storage. The energy interconnection distribution network deeply couples the energy flow, the information flow and the service flow to form a brand new energy system and form an innovative form of energy application.
At present, a plurality of researches are conducted on the fault recovery problem of the power distribution network, and on one hand, the researches are focused on building a fault recovery model of the power distribution network aiming at specific operation environments and conditions of the power distribution network, such as building a power distribution network fault recovery model based on a level preference priority method and load shedding, a power distribution network fault recovery model containing photovoltaic power generation grid connection and accounting for uncertainty of photovoltaic output, a section number gray correlation decision method of power distribution network fault recovery and the like; on the other hand, emphasis is placed on efficient solving algorithms for fault recovery models, such as heuristic search methods, genetic algorithms, tabu search algorithms, ant colony algorithms, multi-agent theory and other intelligent optimization methods. However, at present, a reasonable method is provided for the problem of fault recovery of the energy interconnection power distribution network, the problem of nonlinear optimization of multiple targets and multiple constraints is solved by the fault recovery of the energy interconnection power distribution network, and the recovery strategy formulation must comprehensively consider the multi-energy complementary coordination among multiple energy sub-networks.
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:
according to the fault recovery method of the energy interconnection power distribution network, a switching state and a system optimization operation plan in a fault recovery decision are used as models for dynamic games of different position decision makers, aiming at the problem of fault recovery of the energy interconnection power distribution network under the condition of multi-energy complementary coordination, a switching state variable formulation and a system operation scheme are adjusted to be used as different decision bodies according to the difference of control variable positions in the models, modeling is conducted by adopting a master-slave game theory, 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 achieved by formulating a switching state set and optimizing operation plan adjustment of the system through a game process.
Further, the method specifically comprises the following steps:
(1) Establishing an energy interconnection power distribution network fault recovery model framework based on a master-slave game theory;
(2) Establishing a main game player model;
(3) Establishing a slave gaming player model;
(4) And establishing master-slave game balance points.
Further, in the step (1), a main game player in the energy interconnection power distribution network fault recovery model architecture based on the master-slave game theory is used as a fault recovery module, a game strategy is a switch state set, game payment is a system power loss load, reliable power supply is used as a target, and the established switch state set of the system after the fault occurs is the basis for the slave game player to establish the strategy; on the premise that the slave gaming player provides a switch state set for the master gaming player, the system comprehensive operation cost is used as the game payment to adjust the system optimization operation plan, the economic operation is used as the target, and the system power-loss load index under the strategy is fed back to the master gaming player. The two strategies are mutually influenced and coupled, and the main body player influences the strategy of the subordinate game player through the strategy of the main body player so as to indirectly determine the game payment of the main body player, and the main body player is dominant in the whole game process.
Further, the principal gambler model includes gambling policies and payouts, and gambling constraints.
Further, the gaming strategy and payoff in the master gambler model:
the main gambler in the fault recovery decision is a system fault recovery center and gambling strategy S thereof 1 For the switching state in the energy interconnection power distribution network, writing the strategy set of the game main body into a mathematical formAs shown in formula (1);
S 1 ＝[g(1),g(2),…,g(i),…,g(N)] (1)
wherein g (i) is the position state of the switch i, when g (i) =1 indicates that the switch i is in the closed position, and when g (i) =0 indicates that the switch i is in the open position;
the payment of the main game player is that the power of the power-losing load is minimum in the duration of the minimized fault, and the payment is shown in a formula (2);
wherein T is the number of fault duration time periods; u (u) 1 Paying for the game; n is the number of load nodes of the energy interconnection power distribution network, and r j (t) determining whether the load interruption is performed on the jth load node in the t period after recovery, r j When (t) =1, interrupt is indicated, r j (t) =0, indicating no interruption; c j Importance degree weight of the j-th load node is represented; p (P) j (t) represents the load interrupt power of the jth load node in the t-th period.
Further, game constraint conditions in the main game player model comprise distribution network topology constraint, node voltage constraint, branch capacity constraint and switch operation frequency constraint.
Further, the slave gaming player model comprises a gaming strategy and payment and a gaming constraint condition.
Further, the gaming strategy and payment in the slave gaming player model:
the slave gaming machine optimizes the operation module for the energy interconnection power distribution network, and the strategy set is the operation plan of the system in the fault duration period. The policy set is shown in formula (3):
S 2 ＝[P SB ,P EX ,H IN ,H X ,P MT ,G IN ,G S ,P FC ,P V ] (3)
wherein S is 2 Policy set for slave gambler, P SB ，P EX ，H IN ，H X ，P MT ，G IN ，G S ，P FC ，P V The method comprises the steps of respectively planning electric energy storage charging and discharging power in an energy interconnection power distribution network, planning external network purchase electric power, planning external network purchase heat power to heat energy, planning charging and discharging heat of an energy storage device, planning output of a combined cooling, heating and power micro-combustion engine, planning output of an external network input natural gas quantity, planning charging and discharging gas of a gas storage tank, planning output of a fuel cell and planning charging and discharging power of an electric automobile;
the slave gambler pays for minimizing the system running cost for the duration of the malfunction, as shown in equation (4):
wherein u is 2 Payment for the slave gaming player; t is the number of scheduling periods within the duration of the fault; delta t is the running time length; f (f) MT () And f FC () Fuel cost curves, P, for MT and FC respectively MT (t) and P FC (t) the generated power of the t periods MT and FC, respectively; p (P) loss (t) is the system electrical power loss for period t; f (f) OM,i () For the operation and maintenance cost function of the equipment i, K is the number of the equipment, and P i (t) is the operating power of device i during period t; p (P) EX (t) the electricity purchasing power of the system and the external network in the period of t; q (t) is the time-of-use electricity price of the external network in the period t; n is the number of pollutant species;
and->
Emission coefficient of the theta pollutant of MT and FC respectively, c θ Environmental cost reduction coefficients for the theta-type contaminant; f is the subsidy coefficient of the government for photovoltaic power generation; p (P) PV (t) photovoltaic power generation output at t time period; beta is the load interruption compensation coefficient, P cut (t) load interrupt power for a period t; h IN (t) is the purchase heat power of the thermal energy quantum network to the external network in the period of t, p h Is a coefficient of heat purchasing cost; g IN (t) purchasing gas energy sub-network to external network for t periodGas power, c NG Is the price of natural gas.
Further, the game constraint conditions in the slave game player model comprise an electric energy quantum network operation constraint, a thermal energy quantum network operation constraint, a gas energy quantum network operation constraint and a traffic sub-network electric automobile charging strategy adjustment constraint.
Further, the master-slave game comprehensive model is shown as (5):
G＝{N；S 1 ,S 2 ；u 1 ,u 2 } (5)
wherein n= {1,2} represents the participant set of the game, including the master and slave players; s= { S 1 ,S 2 The policy set of the player, u= { u }, is 1 ,u 2 -a payset for a gambler; wherein u is 1 ＝u 1 (x, y) and u 2 ＝u 2 (x, y) while x ε S 1 And y.epsilon.S 2 ；
When the main game player selects the strategy x epsilon S 1 The response set of the slave gaming machine to the strategy is shown in formula (6):
wherein K (x) is the response set of the slave gaming machine player to the master gaming machine player policy x; the slave gaming player will select a strategy from K (x);
the master gambler knows the response set of the slave gambler, so the slave gambler will adjust its policy to x * ∈S 1 So that the formula (7) is established;
selecting strategy x at subject gambler * ∈S 1 The slave gambler will then select strategy y * ∈K(x * ) Then call (x) * ,y * ) A Nash equilibrium point for the master-slave game; beyond the equilibrium point for
All have u 1 (x * ,y * )≤u 1 (x, y) for->
All have u 2 (x * ,y * )≤u 2 (x * ,y)。
The invention has the advantages that:
aiming at the problem of fault recovery of the energy interconnection power distribution network, the invention adopts a master-slave game model to consider the reliability and economy of fault recovery of the power distribution network, takes a switching state set and a system optimization operation plan adjustment as decision variables of different positions, and the established method simultaneously considers the establishment of the switching state set of the system and the support of the fault recovery scheme by the adjustment of a multi-energy complementary coordination optimization operation scheme, thus being applicable to the establishment of the fault recovery scheme of the energy interconnection power distribution network, ensuring the optimal scheme.
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. And (3) establishing an energy interconnection power distribution network fault recovery model framework based on a master-slave game theory, as shown in fig. 1.
In fig. 1, a main game player is taken as a fault recovery module, a game strategy is a switch state set, game payment is a system power-losing load quantity, and the established switch state set of the system after the fault occurs is the basis for the slave game player to establish the strategy; on the premise that the slave gaming player provides a switch state set for the master gaming player, the system comprehensive operation cost is used as the game payment to adjust the system optimization operation plan, and the system power-loss load index under the strategy is fed back to the master gaming player. The two strategies are mutually influenced and coupled, and the main body player influences the strategy of the subordinate game player through the strategy of the main body player so as to indirectly determine the game payment of the main body player, and the main body player is dominant in the whole game process.
2. Main game player model
2.1 Game strategy and Payment
The main gambler in the fault recovery decision is a system fault recovery center and gambling strategy S thereof 1 And writing the strategy set of the game main body into a mathematical form for the switching state in the energy interconnection power distribution network as shown in a formula (1).
S 1 ＝[g(1),g(2),…,g(i),…,g(N)] (1)
Where g (i) is the position state of switch i, when g (i) =1 indicates that switch i is in position, and when g (i) =0 indicates that switch i is in position.
The principal gambler pays to minimize the loss of electrical payload power for the duration of the malfunction, as shown in equation (2).
Wherein T is the number of fault duration time periods; u (u) 1 Paying for the game; n is the number of load nodes of the energy interconnection power distribution network, and r j (t) determining whether the load interruption is performed on the jth load node in the t period after recovery, r j When (t) =1, interrupt is indicated, r j (t) =0, indicating no interruption; c j Importance degree weight of the j-th load node is represented; p (P) j (t) represents the load interrupt power of the jth load node in the t-th period.
2.2 Game constraints
2.2.1 Power distribution network topology constraints
When the main game player makes a switch state change set, the radial constraint of the power distribution network topological structure needs to be met, and the constraint is shown in a formula (3).
g∈G (3)
G is the 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 power distribution network structure set meeting the radial topological structure.
2.2.2 node voltage constraints
The system after fault recovery needs to meet the node voltage constraint as shown in equation (4):
U i,min ≤U i (t)≤U i,max ,t＝1,…,T (4)
wherein U is i (t) is the voltage magnitude of load node i at time t; u (U) i,min And U i,max The lower limit and the upper limit of the voltage amplitude of the ith node are respectively set. The load node voltage is obtained by the following system load flow balance constraint, and the constraint is satisfied for any fault duration period.
Wherein P is i And Q i Active power and reactive power injected by the ith node are respectively expressed and influenced by the strategy of the slave game player; g ij ，B ij And delta ij The conductance, susceptance and voltage phase angle difference of the line between node i and node j, respectively. U (U) i And U j The voltage amplitudes at node i and node j, respectively.
2.2.3 Branch Capacity constraint
And simultaneously obtaining the capacity of each branch of the power distribution network through system load flow balance, wherein the capacity requirement meets the branch capacity constraint as shown in a formula (7).
P l ≤P l,max (7)
Wherein P is l For the active power of branch l, P l,max Is the upper capacity limit of the branch l.
2.2.4 switch operation times constraint
During the fault recovery process, the switch will be operated frequently, and the constraint shown in formula (8) needs to be satisfied in order not to significantly affect the service life of the switch.
Wherein M is the number of operable switches contained in the power distribution network; r is R j (t) whether the switch j has been subjected to a displacement operation in the t-th period, if so, R j (t) =1 otherwise R j (t)＝0；R max Is the maximum number of operations allowed during the duration of the fault.
3 slave game player model
3.1 Game strategy and Payment
The slave gaming machine optimizes the operation module for the energy interconnection power distribution network, and the strategy set is the operation plan of the system in the fault duration period. The policy set is shown in formula (9).
S 2 ＝[P SB ,P EX ,H IN ,H X ,P MT ,G IN ,G S ,P FC ,P V ] (9)
Wherein S is 2 Policy set for slave gambler, P SB ，P EX ，H IN ，H X ，P MT ，G IN ，G S ，P FC ，P V The method comprises the steps of respectively providing an electric energy storage charging and discharging power plan, an external network purchase electric power plan, a thermal energy external network purchase electric power plan, an energy storage device charging and discharging electric power plan, a micro-cogeneration micro-fuel-Machine (MT) output plan, an external network input natural gas amount plan, a gas storage tank charging and discharging electric power plan, a Fuel Cell (FC) output plan and an electric automobile charging and discharging electric power plan for an energy interconnection power distribution network.
The slave gambler pays as shown in equation (10) to minimize the cost of system operation for the duration of the malfunction.
Wherein u is 2 Payment for the slave gaming player; t is the number of scheduling periods within the duration of the fault; delta t is the running time length; f (f) MT () And f FC () Fuel cost curves, P, for MT and FC respectively MT (t) and P FC (t) the generated power of the t periods MT and FC, respectively; p (P) loss (t) is the system electrical power loss for period t; f (f) OM,i () For the operation and maintenance cost function of the equipment i, K is the number of the equipment, and P i (t) is the operating power of device i during period t; p (P) EX (t) the electricity purchasing power of the system and the external network in the period of t; q (t) is the time-of-use electricity price of the external network in the period t; n is the number of pollutant species;
and->
Emission coefficient of the theta pollutant of MT and FC respectively, c θ Environmental cost reduction coefficients for the theta-type contaminant; f is the subsidy coefficient of the government for photovoltaic power generation; p (P) PV (t) photovoltaic power generation output at t time period; beta is the load interruption compensation coefficient, P cut (t) load interrupt power for a period t;
H IN (t) is the purchase heat power of the thermal energy quantum network to the external network in the period of t, p h Is a coefficient of heat purchasing cost; g IN (t) is the gas purchase power of the gas energy sub-network to the external network in the period of t, c NG Is the price of natural gas.
3.2 Game constraints
3.2.1 electric energy Quantum network operation constraints
The electric energy quantum network operation constraint comprises an electric energy power balance constraint shown in a formula (11) and a micro power supply related operation constraint shown in a formula (12),
wherein P is L (t) is a t-period system electrical load level;
and charging the traffic energy sub-network for a period t after adopting the charging adjustment strategy.
Wherein DeltaP SB Energy-storage self-consumption electric power with delta P for unit scheduling period SB ＝△tD SB Q SB Wherein D is SB Is SB self-discharge coefficient, Q SB Is the energy storage capacity; s is S SB (t) and S SB (t+1) is the end residual capacity of the period t and t+1 respectively; η (eta) dis And eta ch Respectively discharging efficiency and charging efficiency;
respectively allowing a minimum value and a maximum value of the residual electric quantity; delta t is the time period length; the method comprises the steps of carrying out a first treatment on the surface of the />
Respectively the minimum value and the maximum value of the energy storage charge and discharge. />
And->
Respectively minimum and maximum of the power generation power of the micro-fuel engine. />
And->
The minimum value and the maximum value of the power generated by the fuel cell are respectively.
3.2.2 thermal energy Quantum network operation constraints
The operation constraint of the thermal energy quantum network comprises a thermal energy power balance constraint, a cold energy power balance constraint, an energy storage device operation constraint and an outward network purchase thermal power constraint, wherein the thermal energy power balance constraint and the outward network purchase thermal power constraint are shown in a formula (13).
Wherein eta MT (t) is the power generation efficiency of the micro-combustion engine; c (C) he And C co Respectively representing the heating coefficient and the refrigerating coefficient of the double-effect absorption unit; p (P) he (t) and P co (t) t time periods of heat load and cold load power levels, respectively; h x (t) charging and discharging heat power for the energy storage device in the period of t, H x (t) greater than zero represents released energy and less than zero represents absorbed energy; x (t) and X (t-1) are respectively t period and t-1 period energy storage device residual energy, lambda x The energy self-loss coefficient of the energy storage device is used; η (eta) x Is the heat charging and discharging efficiency; when the energy storage device operates in a heating mode and a refrigerating mode, the first constraint or the second constraint in the formula is met respectively;
and->
The minimum power and the maximum power of the heat energy quantum network for outwards online purchase are respectively.
3.2.3 gas energy sub-network operation 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 are shown in a formula (14).
Wherein G is IN (t) the outward online air purchasing amount of the system in the period of t; g s (t) gas discharge amount of the gas tank in a period t; g L (t) is a period t natural gas load; η (eta) FC (t) is the power generation efficiency of the fuel cell, Q LHV Is the heat value of natural gas; q (Q) s (t) and Q s (t-1) the remaining amount of gas in the gas tank at t-time and t-1-time, respectively; g s (t) and the gas release amount of the gas storage tank respectively at t time intervals G s (t) greater than zero represents bleed air;
and->
Respectively the minimum value and the maximum value of the residual quantity of the gas in the gas storage tank; />
And->
Respectively the minimum value and the maximum value of the gas release quantity of the gas storage tank; g l (t) the conveying gas quantity of the first conveying pipeline of the gas network in the period t; />
And->
The minimum value and the maximum value of the quantity of the conveying gas of the first conveying pipeline are respectively.
3.2.4 traffic subnetwork electric vehicle charging policy adjustment
Assuming v (i) is a period of time when the electric vehicle i needs to complete charging, and Δv is a charging duration of the electric vehicle, an adjustment strategy of a charging and discharging plan of the electric vehicle in a 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; if v (i) is not less than T+Deltav, translating the charging load of the electric automobile i to [ T, T+Deltav ]]Within any period of time; if T<v(i)<T+ [ delta ] v, then the period [ v (i) - [ delta ] v, T]The charge load in the battery translates to period [ v (i), T+ [ delta ] v]And (3) inner part. Assume that the charge load after the above adjustment strategy is adopted is
Taking into account the power balance constraints into the electrical energy quantum network.
And 4, the master gaming player knows the strategy of the slave gaming player in the master-slave gaming, and the slave gaming player reacts to the strategy 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；S 1 ,S 2 ；u 1 ,u 2 } (15)
Wherein n= {1,2} represents the participant set of the game, including the master and slave players; s= { S 1 ,S 2 The policy set of the player, u= { u }, is 1 ,u 2 And is the payset of the gambler. Wherein u is 1 ＝u 1 (x, y) and u 2 ＝u 2 (x, y) while x ε S 1 And y.epsilon.S 2 。
When the main game player selects the strategy x epsilon S 1 The response set from the body gambler to the strategy is shown in equation (16).
Where K (x) is the set of responses from the slave gaming machine to the master gaming machine policy x. The slave gaming player will select a strategy from K (x).
The master gambler knows the response set of the slave gambler, so the slave gambler will adjust its policy to x * ∈S 1 So that the expression (17) is established.
Selecting strategy x at subject gambler * ∈S 1 The slave gambler will then select strategy y * ∈K(x * ) Then call (x) * ,y * ) And (5) a Nash equilibrium point for the master-slave game. Beyond the equilibrium point for
All have u 1 (x * ,y * )≤u 1 (x, y) for->
All have u 2 (x * ,y * )≤u 2 (x * ,y)。
According to the method, the solving processes of the main game player and the auxiliary game player are respectively designed based on the chaotic particle swarm algorithm, wherein the main game player module is a fault recovery module, and the auxiliary game player is an optimization operation module. The main body gambler solves the following flow:
(1) And inputting a network topology structure and fault information of the energy interconnection power distribution network.
(2) Parameters of a chaotic particle swarm algorithm are set, wherein the parameters comprise inertia weight, learning factors, chaotic search algebra and the like. The particle population is initialized with the set of switch states as location information.
(3) Detecting whether a fault recovery scheme represented by the initial population meets radial constraints or not, and removing individuals which do not meet the radial constraints.
(4) And calling a solving process of the slave gaming player to obtain the power loss load index corresponding to each particle.
(5) And carrying out load flow calculation through a system operation scheme fed back from the body game player, further obtaining the condition that the constraint condition of the body game player is established, and calculating the constraint condition into an objective function through a penalty function form to obtain the 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 within a set range.
(7) And if the maximum iteration number is reached, ending the algorithm, otherwise judging whether the global optimal solution converges. If the convergence is carried out, the algorithm ends outputting the result, otherwise, the method returns to the step (3).
For the master gambler, the slave gambler solution flow is callable. The solution flow of the slave gaming machine is as follows:
(1) And inputting a network topology structure of the energy interconnection power distribution network and configuration information of energy supply equipment. And inputting the switch state set information provided by the main game player.
(2) Parameters of a chaotic particle swarm algorithm are set, wherein the parameters comprise inertia weight, learning factors, chaotic search algebra and the like. Particle populations are initialized with the system operating scheme during the fault as location information.
(3) And calculating the operation plan corresponding to each particle by taking the comprehensive operation cost as an objective function, and taking constraint conditions into consideration in a penalty function form to obtain an adaptability 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 within a set range.
(5) And if the maximum iteration number is reached, ending the algorithm, otherwise judging whether the global optimal solution converges. If the algorithm is converged, the algorithm ends the output, the power loss load index is fed back to the main game player, and otherwise, the algorithm returns to (3).
Claims (7)
1. The fault recovery method of the energy interconnection power distribution network is characterized in that a switching state and a system optimization operation plan in a fault recovery decision are used as models for dynamic games of different position decision makers, aiming at the problem of fault recovery of the energy interconnection power distribution network under the condition of multi-energy complementation coordination, according to the difference of control variable positions in the models, a switching state variable formulation and a system operation scheme are adjusted to be used as different decision bodies, modeling is carried out by adopting a master-slave game theory, strategies of a main game maker and a slave game maker are mutually influenced and coupled, and the switching state set and the optimization operation plan adjustment of the system are formulated through a game process, so that the fault recovery of the energy interconnection power distribution network is realized;
the method specifically comprises the following steps:
(1) Establishing an energy interconnection power distribution network fault recovery model framework based on a master-slave game theory;
(2) Establishing a main game player model;
(3) Establishing a slave gaming player model;
(4) Establishing master-slave game balance points;
the slave gaming player model comprises a gaming strategy and payment and a gaming constraint condition;
gaming policies and payouts in the slave gaming player model:
the slave gaming machine optimizes the operation module for the energy interconnection power distribution network, and the strategy set is the operation plan of the system in the fault duration period; the policy set is shown in formula (3):
S2＝[PSB,PEX,HIN,HX,PMT,GIN,GS,PFC,PV] (3)
s2 is a strategy set of a slave game player, PSB, PEX, HIN, HX, PMT, GIN, GS, PFC, PV is an electric energy storage charging and discharging power plan, an external network purchase electric power plan, a thermal energy external network purchase electric power plan, an energy storage device charging and discharging plan, a combined cooling, heating and power micro-combustion engine output plan, an external network input natural gas amount plan, an air storage tank charging and discharging plan, a fuel cell output plan and an electric automobile charging and discharging power plan in an energy interconnection power distribution network respectively;
the slave gambler pays for minimizing the system running cost for the duration of the malfunction, as shown in equation (4):
wherein u2 is the payout of the slave gaming player; t is the number of scheduling periods within the duration of the fault; delta t is the running time length; fMT () and fFC () are fuel cost curves of MT and FC, respectively, and PMT (t) and PFC (t) are generated power of MT and FC for t periods, respectively; ploss (t) is the system electric power loss in the period t; fOM, i () is the operation cost function of device i, K is the number of devices, pi (t) is the operating power of device i during period t; PEX (t) is the electricity purchasing and selling power of the system and the external network in the period of t; q (t) is the time-of-use electricity price of the external network in the period t; n is the number of pollutant species;
and->
The emission coefficients of the pollutant of the MT and FC theta type are respectively, and ctheta is the environmental cost conversion coefficient of the pollutant of the theta type; f is the subsidy coefficient of the government for photovoltaic power generation; PPV (t) is the photovoltaic power generation output at period t; beta is a load interruption compensation coefficient, pcut (t) is load interruption power in a t period; HIN (t) is the heat purchasing power from the thermal energy quantum network to the external network in the period of t, and ph is the heat purchasing costCoefficients; GIN (t) is the gas purchase power from the gas energy sub-network to the external network in the period t, and cNG is the price of natural gas.
2. The method for recovering faults of the energy interconnection power distribution network according to claim 1, wherein in the step (1), a main game player in a fault recovery model framework of the energy interconnection power distribution network based on a master-slave game theory is taken as a fault recovery module, a game strategy is a switch state set, game payment is a system power loss load quantity, reliable power supply is taken as a target, and the established switch state set of the system after the faults occur is the basis of a strategy established by a slave game player; on the premise that a slave gaming player provides a switch state set for a main gaming player, a system comprehensive operation cost is used as a game payment to adjust a system optimization operation plan, economic operation is used as a target, and a system power-off load index under the strategy is fed back to the main gaming player; the two strategies are mutually influenced and coupled, and the main body player influences the strategy of the subordinate game player through the strategy of the main body player so as to indirectly determine the game payment of the main body player, and the main body player is dominant in the whole game process.
3. The energy interconnected power distribution network fault recovery method of claim 1, wherein the master gambler model includes gambling policies and payouts and gambling constraints.
4. A method of energy interconnection network failure recovery as claimed in claim 3, wherein the gaming strategy and payment in the master gambler model:
in the fault recovery decision, a main game player is a system fault recovery center, a game strategy S1 is a switching state in an energy interconnection power distribution network, and a strategy set of the game main player is written as a mathematical form as shown in a formula (1);
S1＝[g(1) ,g(2) ,…,g(i) ,…,g(N)] (1)
wherein g (i) is the position state of the switch i, when g (i) =1 indicates that the switch i is in the closed position, and when g (i) =0 indicates that the switch i is in the open position;
the payment of the main game player is that the power of the power-losing load is minimum in the duration of the minimized fault, and the payment is shown in a formula (2);
wherein T is the number of fault duration time periods; u1 is gaming payment; n is the number of load nodes of the energy interconnection power distribution network, rj (t) is whether the load of the j-th load node is interrupted in the t-th period after recovery, and interruption is indicated when rj (t) =1, and no interruption is indicated when rj (t) =0; cj represents importance weight of the j-th load node; pj (t) represents the load interruption power of the jth load node in the t-th period.
5. A method of recovering from a failure of an energy interconnected power distribution network as defined in claim 3, wherein the gaming constraints in the master gambler model include power distribution network topology constraints, node voltage constraints, branch capacity constraints, and switching operation times constraints.
6. The method for recovering faults of an energy interconnection power distribution network according to claim 1, wherein game constraint conditions in the slave game player model comprise electric energy quantum network operation constraint, thermal energy quantum network operation constraint, air energy quantum network operation constraint and traffic sub-network electric vehicle charging strategy adjustment constraint.
7. The energy interconnection power distribution network fault recovery method according to any one of claims 1 to 6, wherein the master-slave gaming integrated model is as shown in formula (5):
G＝{N；S1,S2；u1,u2} (5)
wherein n= {1,2} represents the participant set of the game, including the master and slave players; s= { S1, S2} is the player 'S policy set, u= { u1, u2} is the player' S payment set; wherein, there are u1=u1 (x, y) and u2=u2 (x, y), while x∈s1 and y∈s2;
when the main gambler selects the strategy x epsilon S1, the response set of the main gambler to the strategy is as shown in the formula (6):
wherein K (x) is the response set of the slave gaming machine player to the master gaming machine player policy x; the slave gaming player will select a strategy from K (x);
the master gambler knows the response set of the slave gambler, so the slave gambler will adjust its policy to x e S1, so that equation (7) is established;
under the condition that the main body game player selects the strategy x epsilon S1, the slave body game player selects the strategy y epsilon K (x), and the strategy is called (x, y) as a Nash equilibrium point of the master-slave game; beyond the equilibrium point for
U1 (x, y) is equal to or less than u1 (x, y), for +.>
U2 (x, y) is equal to or less than u2 (x, y).
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