Power clearing evaluation method considering output of aggregated resources and renewable energy sources

Abstract

The invention discloses a power clearing evaluation method considering output of aggregated resources and renewable energy sources. According to the statistical data of the renewable energy output, constructing a renewable energy output constraint of each day-ahead time period; constructing a model constraint condition according to the aggregated resource output constraint, the renewable energy output constraint and the power system and network constraint, constructing an objective function by taking the minimum comprehensive operation cost as an optimization objective, and constructing a day-ahead power clearing model; obtaining system basic parameters and aggregation resource basic parameters, setting load output of each day-ahead time period, and combining with a renewable energy maximum output scene of each day-ahead time period to construct input data; and solving the day-ahead power clearing model by using a solver according to the input data and the day-ahead power clearing model to obtain a day-ahead power clearing result. According to the method, aggregation resources are introduced, risks caused by new energy fluctuation are remarkably reduced, and the stability of the overall level of a power system and the safety of power supply and demand are guaranteed.

Description

Technical Field

[0001] The present invention relates to a power clearing evaluation method, and in particular to a power clearing evaluation method that considers aggregated resources and renewable energy output. Background Art

[0002] As one of the important clean energy sources, renewable energy maintains a rapid development trend, and renewable energy, mainly photovoltaic and wind power, will become the main energy supply in my country. However, the volatility and intermittency of renewable energy output, represented by wind power and photovoltaic, will change its output boundary. Therefore, as the proportion of renewable energy gradually increases, it is urgent to pay attention to the risk of wind and solar power abandonment and drastic fluctuations in electricity cost parameters caused by the uncertainty risk of renewable energy.

[0003] The existing power clearing methods consider the three aspects of medium- and long-term power mechanism, capacity guarantee mechanism and demand-side management mechanism. Although they have alleviated the risks brought by the uncertainty risks of renewable energy to a certain extent, they still have some shortcomings. The medium- and long-term power mechanism relies on the accuracy of predictions and is difficult to cope with real-time supply and demand fluctuations; although the capacity guarantee mechanism ensures reliable power supply, it mainly relies on spare capacity and traditional power units. When the output of new energy fluctuates greatly, the regulation capacity of traditional power sources is limited; the existing demand-side management mechanism is usually constrained by the willingness to participate and the speed of response, especially when there are large-scale fluctuations, the regulation effect of the demand side is difficult to appear immediately. Summary of the invention

[0004] In order to solve the problems existing in the background technology, the present invention provides a power clearing evaluation method considering the output of aggregated resources and renewable energy sources.

[0005] The technical solution adopted by the present invention is: The power clearing evaluation method of the present invention comprises the following steps: S1. Using a normal distribution method in a computer based on historical statistical data of renewable energy output, generate a scenario of renewable energy maximum output in each time period a day ago, and then construct renewable energy output constraints in each time period a day ago; S2. According to the constraints of aggregated resource output, renewable energy output, and power system and network, the model constraints are formed, and the objective function is constructed with the minimization of comprehensive operating costs as the optimization goal, and then the day-ahead power clearing model is constructed; S3, obtain basic system parameters and aggregated resource basic parameters, set the load output for each period of the day before, and then construct input data in combination with the maximum output scenario of renewable energy for each period of the day before in S2; S4. According to the input data and the day-ahead power clearing model in S2, a solver is used to solve the day-ahead power clearing model to obtain a day-ahead power clearing result.

[0006] The maximum output scenario of renewable energy in each period of the day before in S1 is set according to the following formula: P t res,max =P t e,res,max +θ t res ,θ t res ~N(0,σ 2 ) Among them, P t res,max , P t e,res,max and θ t res They represent the actual value, predicted value and prediction error of the maximum output of renewable energy in period t respectively, and σ is the standard deviation of the normal distribution.

[0007] The renewable energy output constraint in S1 is set according to the following formula: 0≤P t res ≤P t res,max Among them, P t res is the renewable energy output during period t, P t res,max is the maximum output of renewable energy in period t.

[0008] The aggregated resource output constraints in S2 include output constraints of heat and power combined participants, output constraints of energy storage participants and output constraints of load participants; The output constraints of the participants in the heat and power combination include unit constraints, heat storage tank constraints, energy storage unit constraints, and electricity and heat balance constraints: (1) The unit constraints are set according to the following formula: P i,t CH ≥max{C i,m h i,t CH +K, P i,min CH -C i,v h i,t CH} P i,t CH ≤P i,max CH -C i,v h i,t CH Pi,t CH -P i,t-1 CH ≤R U,i P i,t-1 CH -P i,t CH ≤R D,i h i,min CH ≤h i,t CH ≤h i,max CH Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of thermal power unit i during period t, C i,m represents the elastic coefficient of electric power and thermal power of the i-th thermal power unit during condensing operation, K is a constant, C i,v P represents the reduction in power generation when the i-th thermal power unit extracts more heating heat, i,max CH , P i,min CH They represent the maximum and minimum output of the i-th thermal power unit, respectively, and h i,t CH represents the real-time thermal output of thermal power unit i during period t, R U,i , R D,i They represent the maximum value of power increase and decrease of thermal power unit i in adjacent time periods, h i,max CH 、h i,min CH They represent the maximum and minimum values ​​of thermal output of thermal power unit i respectively; (2) The heat storage tank constraint is set according to the following formula: 0≤S t ≤S max S t -S t-1 ≤S U S t-1 -S t ≤S D S ini =S fin Among them, t represents the tth period, t-1 represents the t-1th period, S t represents the heat storage capacity of the heat storage tank during period t, S max Indicates the maximum capacity of the heat storage tank, S U, S D They represent the maximum heat storage rate and maximum heat release rate of the heat storage tank in adjacent periods, S ini , S fin They represent the initial heat storage and final heat storage of the heat storage tank respectively; (3) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,a,dis ≤P k ESS,a,dismax 0≤P k,t ESS,a,ch ≤P k ESS,a,chmax E k,t ESS,a =E k,t-1 ESS,a +P k,t ESS,a,ch η k ESS,a,ch -P k,t ESS,a,dis / η k ESS,a,dis E k ESS,a,min ≤E k,t ESS,a ≤E k ESS,a,max E k ini,a= E k fin,a Where a represents the participants of the combined heat and power project, t represents the tth period, t-1 represents the t-1th period, P k ESS ,a,dismax , P k ESS,a,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k in the combined heat and power system, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, E k,t ESS,a It represents the state of charge of energy storage unit k in the heat and power combined power system during period t, E k ESS,a,max 、E k ESS ,a,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k in the heat and power combined power system, respectively, and ηk ESS,a,dis , η k ESS,a,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k in the combined heat and power system, E k ini,a 、E k fin,a They respectively represent the initial state of charge and the final state of charge of the energy storage unit k among the participants of the combined heat and power system; (4) The electrical and thermal balance constraints are set according to the following formula: Σ i P i,t CH +Σ k P k,t ESS,a,dis -Σ k P k,t ESS,a,ch -P t LD,a =P t VPP,a,out -P t VPP,a,in Σ i h i,t CH =h t load +S t -S t-1 Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of cogeneration unit i during period t, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, P t LD,a P represents the actual electric load value of the heat and power joint participants in period t, t VPP,a,in and P t VPP,a,out Respectively represent the power demand and power supply of the heat and power joint participants at time t, i = 1 to N H , k = 1 to N ESS , N H 、N ESS Respectively represent the number of cogeneration units and energy storage units, h i,t CH represents the real-time thermal output of thermal power unit i at time t, h t loadrepresents the actual heat load value of the heat and power joint participants in period t, S t It represents the heat storage capacity of the heat storage tank during period t.

[0009] The output constraints of the energy storage participants include power balance constraints and energy storage unit constraints: (1) The electrical balance constraint is set according to the following formula: Σ k P k,t ESS,b,dis -Σ k P k,t ESS,b,ch -P t LD,b =P t VPP,b,out -P t VPP,b,in Where b represents the energy storage participant, k = 1 to N ESS , N ESS Represents the number of energy storage units, P k,t ESS,b,dis , P k,t ESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, P t LD,b represents the actual load value of the energy storage participant during period t, P t VPP,b,in and P t VPP,b,out They represent the power demand and power supply of the energy storage participant in period t respectively; (2) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,b,dis ≤P k ESS,b,dismax 0≤P k,t ESS,b,ch ≤P k ESS,b,chmax E k,t ESS,b =E k,t-1 ESS,b +P k,t ESS,b,ch η k ESS,b,ch -P k,t ESS,b,dis / η k ESS,b,dis E k ESS,b,min ≤E k,tESS,b ≤E k ESS,b,max E k ini,b= E k fin,b Where b represents the energy storage participant, t represents the tth period, t-1 represents the t-1th period, P k ESS,b,dismax , P k ESS,b,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k of the energy storage participant, P k,t ESS,b,dis , P k,t ESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, E k,t ESS,b represents the charge state of energy storage unit k of energy storage participant in period t, E k ESS,b,max 、E k ESS,b,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k of the energy storage participant, η k ESS,b,dis , η k ESS,b,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k of the energy storage participant, E k ini,b 、E k fin,b They respectively represent the initial charge state and final charge state of the energy storage unit k of the energy storage participant.

[0010] The output constraints of the load-type participants include power balance constraints and interruptible load output constraints: (1) The electrical balance constraint is set according to the following formula: P t DR -P t LD,c =P t VPP,c,out -P t VPP,c,in Among them, c represents the load-type participant, P t DR represents the power reduction of the interruptible load during period t, P t LD,c represents the actual load value of the load-type participant during period t, P t VPP,c,in and P tVPP,c,out They represent the power demand and power supply of the load-type participants in period t respectively; (2) The interruptible load output constraint is set according to the following formula: 0≤P t DR ≤P DR,max Among them, P t DR represents the power reduction of the interruptible load during period t, P DR,max Indicates the maximum curtailment power that can interrupt the load.

[0011] The power system and network constraints in S2 include node power balance constraints, line power constraints and thermal power unit operation constraints: (1) The node power balance constraint is set according to the following formula: Σ G P t,n G,s +Σ z P t,n VPP,z,s,out -Σ z P t,n VPP,z,s,in +Σ res P t,n res,s -P t,n TLD =Σ m B nm (δ t,n s -δ t,m s ):λ n,s,t EN Among them, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant at node n in time period t in scenario s, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, P t,n res,s represents the real-time output of the renewable energy unit at node n in scenario s during period t, P t,n TLD represents the real-time power of the load on node n during period t, δ t,n s ,δ t,m sThey represent the phase angles of node n and node m in scene s during period t, G represents the thermal power unit, G∈Ψ n,g ,Ψ n,g represents the set of thermal power units at node n, z represents the type of participant, z∈{a,b,c}, a, b, c represent the participants of combined heat and power, energy storage participants, and load participants, res represents the photovoltaic unit, res∈Ψ n,res ,Ψ n,res represents the set of photovoltaic units at node n, m∈θ n ,θ n represents the set of downstream nodes of node n, m is the downstream node of node n, λ n,s,t EN The dual variable representing the constraint is the clearing power cost parameter of node n in scenario s during period t; (2) The line power constraint is set according to the following formula: |B nm (δ t,n s -δ t,m s )|≤P nm f,max Among them, B nm represents the line susceptance, δ t,n s ,δ t,m s They represent the phase angles of node n and node m in scene s during period t, P nm f,max It represents the maximum value of the power flow from node m to node n of the line; (3) The operating constraints of the thermal power unit are set according to the following formula: P n G,min ≤P t,n G,s ≤P n G,max P t,n G,s -P t-1,n G,s ≥P R,n G P t-1,n G,s -P t,n G,s ≥P U,n G Among them, P n G,max , P n G,minThey represent the maximum and minimum power generation of the thermal power unit at node n, respectively. t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P R,n G , P U,n G They respectively represent the maximum value of the real-time output increase and the maximum value of the decrease in the thermal power units in adjacent time periods.

[0012] The objective function in S2 is set according to the following formula: F=Σ t Σ n {C n (P t,n G,s )+Σ z ρ t,n VPP,z,out P t,n VPP,z,s,out -Σ z ρ t,n VPP,z,in P t,n VPP,z,s,in +r res (P t,n res,s,max -P t,n res,s )} Among them, F represents the objective function, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, C n It's about P t,n G,s The function represents the cost parameter of the thermal power unit power output at node n; P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant on node n in scenario s during period t, respectively, and ρ t,n VPP,z,in , t,n VPP,z,out They represent the cost parameters of the power demand and power supply of the zth participant at node n in period t, r res represents the wind loss penalty parameter, P t,n res,s represents the real-time output of renewable energy on node n in scenario s during period t, P t,n res,s,maxrepresents the maximum output of renewable energy at node n in scenario s during period t, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, n=1 to N e , N e Represents the number of grid nodes, t=1 to T, T represents the day-ahead scheduling period.

[0013] The basic system parameters in S3 include: network parameters and power cost parameters, and the basic aggregated resource parameters in S3 include: internal equipment parameters of the combined heat and power participants, internal equipment parameters of the energy storage participants, and internal equipment parameters of the load participants.

[0014] The clearing results in S4 include the output configuration of physical parameters including the combined heat and power participants, energy storage participants and load participants in each time period, as well as the node power cost parameters and system average cost parameter results.

[0015] The beneficial effects of the present invention are: This study introduces aggregated resources to make up for the shortcomings of the above studies. Aggregated resources can dispatch resources in real time and improve the flexibility and response speed of the power system by integrating distributed gas units, energy storage units, interruptible loads and other flexible adjustment methods. Compared with traditional mechanisms, aggregated resources can not only cope with fluctuations in the output of new energy, but also reasonably adjust the power load of different user groups. In addition, aggregated resources can make up for the shortcomings of traditional capacity guarantee mechanisms and enhance the regulation capabilities of the power system.

[0016] The method of the present invention introduces aggregated resources to significantly reduce the risks brought by the volatility of new energy, alleviate the risks of wind and solar power abandonment and drastic fluctuations in power cost parameters caused by the uncertainty risks of renewable energy, and ensure the overall stability of the power system and the security of power supply and demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the present invention.

[0018] Figure 2 2 is a topological diagram of the system in this embodiment.

[0019] Figure 3 This is a typical photovoltaic power generation curve.

[0020] Figure 4 Schematic diagram of the amount of abandoned light in two model environments.

[0021] Figure 5 Schematic diagram of the expected cost parameters of the system under two analysis environments.

[0022] Figure 6Schematic diagram of the charging and discharging of the energy storage unit over time.

[0023] Figure 7 Schematic diagram of the load reduction of interruptible load over time.

[0024] Figure 8 This is the convergence diagram of the simulation results. DETAILED DESCRIPTION

[0025] In order to better understand the present invention, the content of the present invention is further described in conjunction with the drawings and embodiments, but the implementation methods of the present invention are not limited thereto.

[0026] A power clearing evaluation method of the present invention is as follows Figure 1 As shown, the embodiment includes the following steps: S1. Based on the historical statistical data of renewable energy output in the current month, the uncertainty of the maximum output of renewable energy is modeled using the normal distribution method in the computer, and the maximum output scenario of renewable energy in each time period before the day is generated, and then the renewable energy output constraints in each time period before the day are constructed.

[0027] In S1, the normal distribution method is used to characterize the uncertainty of the maximum output of renewable energy. The maximum output scenario of renewable energy in each period of the day before is set according to the following formula: P t res,max =P t e,res,max +θ t res ,θ t res ~N(0,σ 2 ) Among them, P t res,max , P t e,res,max and θ t res They represent the actual value, predicted value and prediction error of the maximum output of photovoltaic renewable energy in period t respectively, and σ is the standard deviation of the normal distribution.

[0028] The renewable energy output constraint in S1 is set according to the following formula: 0≤P t res ≤P t res,max Among them, P t res is the renewable energy output during period t, P t res,max is the maximum output of renewable energy in period t.

[0029] S2. Based on the constraints of aggregated resource output, renewable energy output, and power system and network constraints, the model constraints are constructed. The objective function is constructed with the guaranteed consumption of renewable energy as the boundary condition and the minimization of the comprehensive operating cost as the optimization goal, and then the day-ahead power clearing model is constructed.

[0030] The aggregate resource output constraints in S2 include the output constraints of the combined heat and power participants, the output constraints of the energy storage participants, and the output constraints of the load participants; The output constraints of the participants in the heat and power combination include unit constraints, heat storage tank constraints, energy storage unit constraints, and electricity and heat balance constraints: (1) The unit constraints are set according to the following formula: P i,t CH ≥max{C i,m h i,t CH +K, P i,min CH -C i,v h i,t CH} P i,t CH ≤P i,max CH -C i,v h i,t CH P i,t CH -P i,t-1 CH ≤R U,i P i,t-1 CH -P i,t CH ≤R D,i h i,min CH ≤h i,t CH ≤h i,max CH Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of thermal power unit i during period t, C i,m represents the elastic coefficient of electric power and thermal power of the i-th thermal power unit during condensing operation, K is a constant, C i,v P represents the reduction in power generation when the i-th thermal power unit extracts more heating heat, i,max CH , P i,minCH They represent the maximum and minimum output of the i-th thermal power unit, respectively, and h i,t CH represents the real-time thermal output of thermal power unit i during period t, R U,i , R D,i They represent the maximum value of power increase and decrease of thermal power unit i in adjacent time periods, h i,max CH 、h i,min CH They represent the maximum and minimum thermal output of thermal power unit i respectively.

[0031] (2) The heat storage tank constraint is set according to the following formula: 0≤S t ≤S max S t -S t-1 ≤S U S t-1 -S t ≤S D S ini =S fin Among them, t represents the tth period, t-1 represents the t-1th period, S t represents the heat storage capacity of the heat storage tank during period t, S max Indicates the maximum capacity of the heat storage tank, S U , S D They represent the maximum heat storage rate and maximum heat release rate of the heat storage tank in adjacent periods, S ini , S fin They represent the initial heat storage capacity and final heat storage capacity of the heat storage tank respectively.

[0032] (3) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,a,dis ≤P k ESS,a,dismax 0≤P k,t ESS,a,ch ≤P k ESS,a,chmax E k,t ESS,a =E k,t-1 ESS,a +P k,t ESS,a,ch η k ESS,a,ch -P k,t ESS,a,dis / η kESS,a,dis E k ESS,a,min ≤E k,t ESS,a ≤E k ESS,a,max E k ini,a= E k fin,a Where a represents the participants of the combined heat and power project, t represents the tth period, t-1 represents the t-1th period, P k ESS ,a,dismax , P k ESS,a,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k in the combined heat and power system, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, E k,t ESS,a It represents the state of charge of energy storage unit k in the heat and power combined power system during period t, E k ESS,a,max 、E k ESS ,a,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k in the heat and power combined power system, respectively, and η k ESS,a,dis , η k ESS,a,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k in the combined heat and power system, E k ini,a 、E k fin,a They respectively represent the initial state of charge and final state of charge of the energy storage unit k among the participants in the combined heat and power system.

[0033] (4) The electrical and thermal balance constraints are set according to the following formula: Σ i P i,t CH +Σ k P k,t ESS,a,dis -Σ k P k,t ESS,a,ch -P t LD,a =P t VPP,a,out -P tVPP,a,in Σ i h i,t CH =h t load +S t -S t-1 Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of cogeneration unit i during period t, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, P t LD,a P represents the actual electric load value of the heat and power joint participants in period t, t VPP,a,in and P t VPP,a,out Respectively represent the power demand and power supply of the heat and power joint participants at time t, i = 1 to N H , k = 1 to N ESS , N H 、N ESS Respectively represent the number of cogeneration units and energy storage units, h i,t CH represents the real-time thermal output of thermal power unit i at time t, h t load represents the actual heat load value of the heat and power joint participants in period t, S t It represents the heat storage capacity of the heat storage tank during period t.

[0034] The output constraints of energy storage participants include power balance constraints and energy storage unit constraints: (1) The electrical balance constraint is set according to the following formula: Σ k P k,t ESS,b,dis -Σ k P k,t ESS,b,ch -P t LD,b =P t VPP,b,out -P t VPP,b,in Where b represents the energy storage participant, k = 1 to N ESS , N ESS Represents the number of energy storage units, P k,t ESS,b,dis , P k,tESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, P t LD,b represents the actual load value of the energy storage participant during period t, P t VPP,b,in and P t VPP,b,out They represent the power demand and power supply of the energy storage participant in period t respectively.

[0035] (2) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,b,dis ≤P k ESS,b,dismax 0≤P k,t ESS,b,ch ≤P k ESS,b,chmax E k,t ESS,b =E k,t-1 ESS,b +P k,t ESS,b,ch η k ESS,b,ch -P k,t ESS,b,dis / η k ESS,b,dis E k ESS,b,min ≤E k,t ESS,b ≤E k ESS,b,max E k ini,b= E k fin,b Where b represents the energy storage participant, t represents the tth period, t-1 represents the t-1th period, P k ESS,b,dismax , P k ESS,b,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k of the energy storage participant, P k,t ESS,b,dis , P k,t ESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, E k,t ESS,b represents the charge state of energy storage unit k of energy storage participant in period t, E k ESS,b,max 、Ek ESS,b,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k of the energy storage participant, η k ESS,b,dis , η k ESS,b,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k of the energy storage participant, E k ini,b 、E k fin,b They respectively represent the initial charge state and final charge state of the energy storage unit k of the energy storage participant.

[0036] The output constraints of load-type participants include power balance constraints and interruptible load output constraints: (1) The electrical balance constraint is set according to the following formula: P t DR -P t LD,c =P t VPP,c,out -P t VPP,c,in Among them, c represents the load-type participant, P t DR represents the power reduction of the interruptible load during period t, P t LD,c represents the actual load value of the load-type participant during period t, P t VPP,c,in and P t VPP,c,out They represent the power demand and power supply of the load-type participants in period t respectively.

[0037] (2) The interruptible load output constraint is set according to the following formula: 0≤P t DR ≤P DR,max Among them, P t DR represents the power reduction of the interruptible load during period t, P DR,max Indicates the maximum curtailment power that can interrupt the load.

[0038] The power system and network constraints in S2 include node power balance constraints, line power constraints, and thermal power unit operation constraints: (1) The node power balance constraint is set according to the following formula: Σ G P t,n G,s +Σ z P t,nVPP,z,s,out -Σ z P t,n VPP,z,s,in +Σ res P t,n res,s -P t,n TLD =Σ m B nm (δ t,n s -δ t,m s ):λ n,s,t EN Among them, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant at node n in time period t in scenario s, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, P t,n res,s represents the real-time output of the renewable energy unit at node n in scenario s during period t, P t,n TLD represents the real-time power of the load on node n during period t, δ t,n s ,δ t,m s They represent the phase angles of node n and node m in scene s during period t, G represents the thermal power unit, G∈Ψ n,g ,Ψ n,g represents the set of thermal power units at node n, z represents the type of participant, z∈{a,b,c}, a, b, c represent the participants of combined heat and power, energy storage participants, and load participants, res represents the photovoltaic unit, res∈Ψ n,res ,Ψ n,res represents the set of photovoltaic units at node n, m∈θ n ,θ n represents the set of downstream nodes of node n, m is the downstream node of node n, λ n,s,t EN The dual variable representing the constraint is the clearing power cost parameter of node n in scenario s during period t.

[0039] (2) The line power constraint is set according to the following formula: |B nm (δ t,n s -δt,m s )|≤P nm f,max Among them, B nm represents the line susceptance, δ t,n s ,δ t,m s They represent the phase angles of node n and node m in scene s during period t, P nm f,max Indicates the maximum value of the power flow from node m to node n of the line.

[0040] (3) The operating constraints of thermal power units are set according to the following formula: P n G,min ≤P t,n G,s ≤P n G,max P t,n G,s -P t-1,n G,s ≥P R,n G P t-1,n G,s -P t,n G,s ≥P U,n G Among them, P n G,max , P n G,min They represent the maximum and minimum power generation of the thermal power unit at node n, respectively. t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P R,n G , P U,n G They respectively represent the maximum value of the real-time output increase and the maximum value of the decrease in the thermal power units in adjacent time periods.

[0041] The comprehensive operating cost in S2 includes the total power generation cost and the penalty cost for abandoned light. The objective function is set according to the following formula: F=Σ t Σ n {C n (P t,n G,s )+Σ z ρ t,n VPP,z,out P t,nVPP,z,s,out -Σ z ρ t,n VPP,z,in P t,n VPP,z,s,in +r res (P t,n res,s,max -P t,n res,s )} Among them, F represents the objective function, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, C n It's about P t,n G,s The function represents the cost parameter of the thermal power unit power output at node n; P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant on node n in scenario s during period t, respectively, and ρ t,n VPP,z,in , t,n VPP,z,out They represent the cost parameters of the power demand and power supply of the zth participant at node n in period t, r res represents the wind loss penalty parameter, P t,n res,s represents the real-time output of renewable energy on node n in scenario s during period t, P t,n res,s,max represents the maximum output of renewable energy at node n in scenario s during period t, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, n=1 to N e , N e It represents the number of grid nodes, t=1 to T, T represents the day-ahead dispatch period. Generally speaking, the wind loss penalty parameter is set relatively large to ensure that renewable energy can be fully absorbed under the condition of meeting the constraints.

[0042] S3. Obtain basic system parameters and aggregated resource basic parameters, set the load output for each time period before the day, and then construct input data in combination with the maximum output scenario of renewable energy for each time period before the day in S2.

[0043] S4. According to the input data and the day-ahead power clearing model in S2, the solver is used to solve the day-ahead power clearing model to obtain the day-ahead power clearing result, that is, the output configuration of aggregated resources in different time periods, including node power cost parameters and system average power cost parameters. According to the clearing result, relevant resources are configured to control the operation of the power system.

[0044] The node in the present invention is a node of an actual power system in a certain area, wherein the aggregated resources respectively aggregate corresponding internal equipment access nodes, and the renewable energy units and thermal power units are also connected to the nodes in the system.

[0045] The basic system parameters in S3 include: network parameters and power cost parameters. The basic parameters of aggregated resources in S3 include: internal equipment parameters of combined heat and power participants, internal equipment parameters of energy storage participants and internal equipment parameters of load participants.

[0046] The network parameters include: the upper limit of the power flow of the transmission line P nm f,max , the line susceptance B nm ; Maximum power generation capacity of thermal power unit P n G,max , minimum value P n G,min , the maximum value of the real-time output increase of the thermal power unit in adjacent periods P R,n G , the maximum value P of the reduction U,n G .

[0047] The power cost parameters include: the cost parameter C of the thermal power unit power output n , the cost parameter ρ of the aggregated resource for the power demand t,n VPP,z,in , the cost parameter ρ of power supply t,n VPP,z,out .

[0048] The input data include basic system parameters, basic parameters of aggregated resources, load output in each time period the day before, and maximum output scenario of renewable energy in each time period the day before.

[0049] The clearing results in S4 include the output configuration of physical parameters including the combined heat and power participants, energy storage participants and load participants in each time period, as well as the node power cost parameters and system average cost parameter results.

[0050] Participants in the present invention specifically refer to participating factories and equipment. Combined heat and power participants refer to factories and equipment that aggregate cogeneration units, heat storage tanks and energy storage units, and achieve coordinated scheduling of electricity and heat by adjusting internal resource configuration; energy storage participants refer to factories and equipment that aggregate large-capacity energy storage units, which are used to adjust the peak-to-valley difference of the power grid, store energy when electricity demand is low, and release electricity when demand is peak; load-type participants refer to factories and equipment that aggregate a large number of interruptible loads, which can reduce loads in time during peak load periods of the power grid and optimize the load structure of the power system. The three types of participants improve the reliability and flexibility of the power system by rationally scheduling internal resources.

[0051] Based on the clearing model in step 3, the node power balance constraint in each time period of each scenario is solved based on the clearing model in step 3, and the dual variable of the node power balance constraint in each time period in the scenario is calculated. The node cost parameters of different nodes in the corresponding time period in each scenario can be obtained and verified by the following risk assessment indicators; The risk control capability of the present invention can be verified by risk assessment indicators, and the steps of risk assessment indicators are as follows: (1) obtaining the system average power cost parameter by processing the node cost parameter, and then obtaining the expected cost parameter; The node cost parameter is set according to the following formula: π n,s,t EN =λ n,s,t EN Among them, π n,s,t EN represents the power cost parameter of node n in scenario s during period t, λ n,s,t EN represents the dual variable in the node power balance constraint in S2.

[0052] The system average power cost parameter is set according to the following formula: π s,t EN =Σ n π n,s,t EN P n,t TLD / P t TLD Among them, π s,t EN represents the system average power cost parameter in scenario s at time t, π n,s,t EN represents the system power price parameter at node n in scenario s at time t, P n,t TLD Table t time period node n load power, P t TLD Represents the total power of the system load during period t, n=1 to N e , N e Indicates the number of grid nodes.

[0053] Expected cost parameter π' t EN The following formula is used to evaluate the expected level of the system average cost parameter in all possible scenarios: π' t EN =Σ sP s π s,t EN Among them, π' t EN represents the expected cost parameter of the system during time period t, s=1 to N s , N s Indicates the total number of scenes, P s Represents the probability of each scenario occurring, π s,t EN Represents the system average power cost parameter in scenario s at time t.

[0054] (2) Convergence criterion of simulation results: Based on N s The convergence of the results is analyzed by analyzing the changes in the variance coefficient of the simulation results. The convergence standard is defined as follows: the results are considered to be converged only when the variance coefficient of each time period is below the specified threshold; based on N s Simulation results, variance coefficient R t It can be defined as: R t =(σ t ) 1 / 2 / ((N s ) 1 / 2 π' t EN ) Among them, σ t N s The standard deviation of the cost parameter in period t under the simulation results.

[0055] (3) Determine the risk assessment indicators for each time period before the final date.

[0056] In order to facilitate the understanding and implementation of those skilled in the art, a power clearing assessment method designed by the present invention that considers aggregated resources and renewable energy output is verified through a simulation example below.

[0057] The embodiment system adopts an improved actual power system in a certain area. The system topology is shown in the figure below. Figure 2 The unit parameter information is shown in Table 1, and the typical photovoltaic power generation curve is shown in Figure 3 This embodiment adopts per unit value calculation, and the reference capacity is 100.

[0058] Table 1 Unit parameter information Unit No. Node Number Maximum power (PU) Minimum power (PU) Power generation cost Up / down climbing rate (pu / h) Minimum shutdown / startup duration (h) 1 30 0.9 0.15 400 0.35 2 2 31 0.95 0.2 430 0.25 2 3 32 0.85 0.2 450 0.3 2 4 33 0.8 0.2 480 0.35 2 5 34 0.75 0.15 500 0.25 2 6 35 0.7 0.2 530 0.25 2 7 36 0.9 0.25 550 0.35 2 8 37 1.35 0.15 580 0.15 2 9 38 1.45 0.15 600 0.2 2 10 39 1.2 0.2 620 0.35 2 Based on the above parameters, the system of this embodiment sets two model environments.

[0059] Model environment 1: The objects of power clearing include various aggregated resources, conventional units, and new energy sources.

[0060] Model environment 2: The objects of power clearing include conventional units and new energy.

[0061] The amount of wind and solar power curtailment and the expected cost parameters under the two model environments are as follows: Figure 4 , 5 As shown by Figure 4 , 5 It can be seen that when considering uncertainty risks, the amount of wind and solar power abandoned in model environment 1 is significantly smaller than that in model environment 2, and the fluctuation of expected power cost parameters in model environment 1 is also significantly smaller than that in model environment 2. This shows that the proposed model can effectively quantify the uncertainty risks of renewable energy, thereby reducing the risks of wind and solar power abandoned and drastic fluctuations in power cost parameters caused by the uncertainty risks of renewable energy.

[0062] The fluctuation of the expected power cost parameter of model environment 1 is significantly smaller than that of model environment 2. The output of some internal devices of the aggregated resources is Figure 6 , 7 As shown by Figure 6 , 7 It can be seen that after the three types of aggregated resources are added to the model, when the photovoltaic unit starts to output, its output can effectively meet the load demand, thereby reducing the power cost parameter. While the power cost parameter is reduced, the internal energy storage is adjusted to increase the charging amount, delaying the further decline of the power cost parameter. When the output of the photovoltaic unit gradually decreases and the load demand further increases, the power cost parameter of the system increases. This is because the output of the photovoltaic unit decreases and the marginal unit of the system is the high-cost thermal power unit in the market. However, the power cost parameter of model environment 1 also rises slowly. This is because while the power cost parameter rises, the internal resources including thermal power units and interruptible loads adjust their output in time, increase the external power supply on the premise of meeting their own load power consumption, and delay the further rise of the power cost parameter.

[0063] Next, the convergence of the simulation results is explained. Taking model environment 1 as an example, the variance coefficient is calculated for the results of 10,000 simulations until the simulation coefficient reaches the set convergence standard of 0.05, then the simulation is stopped and the simulation coefficients under the two model environments are plotted as a function of the number of simulations. Figure 8 It can be found that with the gradual increase in the number of simulations, the two variance coefficients decrease rapidly. When the number of simulations reaches 1159, it can be considered that the calculation results have converged.

[0064] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for evaluating power clearing considering aggregated resources and renewable energy output, characterized in that: The steps include: S1. Using a normal distribution method in a computer based on historical statistical data of renewable energy output, generate a scenario of renewable energy maximum output in each time period a day ago, and then construct renewable energy output constraints in each time period a day ago; S2. According to the constraints of aggregated resource output, renewable energy output, and power system and network, the model constraints are formed, and the objective function is constructed with the minimization of comprehensive operating costs as the optimization goal, and then the day-ahead power clearing model is constructed; S3, obtain basic system parameters and aggregated resource basic parameters, set the load output for each period of the day before, and then construct input data in combination with the maximum output scenario of renewable energy for each period of the day before in S2; S4. According to the input data and the day-ahead power clearing model in S2, a solver is used to solve the day-ahead power clearing model to obtain a day-ahead power clearing result.

2. A method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The maximum output scenario of renewable energy in each period of the day before in S1 is set according to the following formula: P t res,max =P t e,res,max +θ t res ,i t res ~N(0,σ 2 ) Among them, P t res,max , P t e,res,max and θ t res They represent the actual value, predicted value and prediction error of the maximum output of renewable energy in period t respectively, and σ is the standard deviation of the normal distribution.

3. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The renewable energy output constraint in S1 is set according to the following formula: 0≤P t res ≤P t res,max Among them, P t res is the renewable energy output during period t, P t res,max is the maximum output of renewable energy in period t.

4. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The aggregated resource output constraints in S2 include output constraints of heat and power combined participants, output constraints of energy storage participants and output constraints of load participants; The output constraints of the participants in the heat and power combination include unit constraints, heat storage tank constraints, energy storage unit constraints, and electricity and heat balance constraints: (1) The unit constraints are set according to the following formula: P i,t CH ≥max{C i,m h i,t CH +K, P i,min CH -C i,v h i,t CH } P i,t CH ≤P i,max CH -C i,v h i,t CH P i,t CH -P i,t-1 CH ≤R U,i P i,t-1 CH -P i,t CH ≤R D,i h i,min CH ≤h i,t CH ≤h i,max CH Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of thermal power unit i during period t, C i,m represents the elastic coefficient of electric power and thermal power of the i-th thermal power unit during condensing operation, K is a constant, C i,v P represents the reduction in power generation when the i-th thermal power unit extracts more heating heat, i,max CH , P i,min CH They represent the maximum and minimum output of the i-th thermal power unit, respectively, and h i,t CH represents the real-time thermal output of thermal power unit i during period t, R U,i , R D,i They represent the maximum value of power increase and decrease of thermal power unit i in adjacent time periods, h i,max CH 、h i,min CH They represent the maximum and minimum values ​​of thermal output of thermal power unit i respectively; (2) The heat storage tank constraint is set according to the following formula: 0≤S t ≤S max S t -S t-1 ≤S U S t-1 -S t ≤S D S ini =S fin Among them, t represents the tth period, t-1 represents the t-1th period, S t represents the heat storage capacity of the heat storage tank during period t, S max Indicates the maximum capacity of the heat storage tank, S U , S D They represent the maximum heat storage rate and maximum heat release rate of the heat storage tank in adjacent periods, S ini , S fin They represent the initial heat storage and final heat storage of the heat storage tank respectively; (3) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,a,dis ≤P k ESS,a,dismax 0≤P k,t ESS,a,ch ≤P k ESS,a,chmax E k,t ESS,a =E k,t-1 ESS,a +P k,t ESS,a,ch or k ESS,a,ch -P k,t ESS,a,dis / or k ESS,a,dis AND k ESS,a,min ≤E k,t ESS,a ≤E k ESS,a,max AND k ini,a= AND k fin,a Among them, t represents the tth period, t-1 represents the t-1th period, P k ESS,a,dismax , P k ESS,a,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k in the combined heat and power system, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, E k,t ESS,a It represents the state of charge of energy storage unit k in the heat and power combined power system during period t, E k ESS,a,max 、E k ESS,a,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k in the heat and power combined power system, respectively, and η k ESS,a,dis , η k ESS,a,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k in the combined heat and power system, E k ini,a 、E k fin,a They respectively represent the initial state of charge and the final state of charge of the energy storage unit k among the participants of the combined heat and power system; (4) The electrical and thermal balance constraints are set according to the following formula: Σ i P i,t CH +Σ k P k,t ESS,a,dis -Σ k P k,t ESS,a,ch -P t LD,a =P t VPP,a,out -P t VPP,a,in Σ i h i,t CH =h t load +S t -S t-1 Among them, t represents the tth period, t-1 represents the t-1th period, P i,t CH represents the real-time power output of cogeneration unit i during period t, P k,t ESS,a,dis , P k,t ESS,a,ch They represent the real-time discharge power and charging power of the energy storage unit k in the heat and power combined power system during period t, P t LD,a P represents the actual electric load value of the heat and power joint participant in period t, t VPP,a,in and P t VPP,a,out Respectively represent the power demand and power supply of the heat and power joint participants at time t, i = 1 to N H , k = 1 to N ESS , N H 、N ESS Respectively represent the number of cogeneration units and energy storage units, h i,t CH represents the real-time thermal output of thermal power unit i at time t, h t load represents the actual heat load value of the heat and power combined participants in period t, S t It indicates the heat storage capacity of the heat storage tank during period t.

5. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 4, characterized in that: The output constraints of the energy storage participants include power balance constraints and energy storage unit constraints: (1) The electrical balance constraint is set according to the following formula: Σ k P k,t ESS,b,dis -Σ k P k,t ESS,b,ch -P t LD,b =P t VPP,b,out -P t VPP,b,in Where k = 1 to N ESS , N ESS Represents the number of energy storage units, P k,t ESS,b,dis , P k,t ESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, P t LD,b represents the actual load value of the energy storage participant during period t, P t VPP,b,in and P t VPP,b,out They represent the power demand and power supply of the energy storage participant in period t respectively; (2) The energy storage unit constraint is set according to the following formula: 0≤P k,t ESS,b,dis ≤P k ESS,b,dismax 0≤P k,t ESS,b,ch ≤P k ESS,b,chmax E k,t ESS,b =E k,t-1 ESS,b +P k,t ESS,b,ch or k ESS,b,ch -P k,t ESS,b,dis / or k ESS,b,dis AND k ESS,b,min ≤E k,t ESS,b ≤E k ESS,b,max AND k ini,b= AND k fin,b Among them, t represents the tth period, t-1 represents the t-1th period, P k ESS,b,dismax , P k ESS,b,chmax They represent the maximum discharge power and maximum charging power of the energy storage unit k of the energy storage participant, P k,t ESS,b,dis , P k,t ESS,b,ch They represent the real-time discharge power and charging power of energy storage unit k of energy storage participant in period t, E k,t ESS,b represents the charge state of energy storage unit k of energy storage participant in period t, E k ESS,b,max 、E k ESS,b,min They represent the maximum state of charge and minimum state of charge of the energy storage unit k of the energy storage participant, η k ESS,b,dis , η k ESS,b,ch They represent the discharge efficiency and charging efficiency of the energy storage unit k of the energy storage participant, E k ini,b 、E k fin,b They respectively represent the initial charge state and final charge state of the energy storage unit k of the energy storage participant.

6. A method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 4, characterized in that: The output constraints of the load-type participants include power balance constraints and interruptible load output constraints: (1) The electrical balance constraint is set according to the following formula: P t DR -P t LD,c =P t VPP,c,out -P t VPP,c,in Among them, P t DR represents the power reduction of the interruptible load during period t, P t LD,c represents the actual load value of the load-type participant during period t, P t VPP,c,in and P t VPP,c,out They represent the power demand and power supply of the load-type participants in period t respectively; (2) The interruptible load output constraint is set according to the following formula: 0≤P t DR ≤P DR,max Among them, P t DR represents the power reduction of the interruptible load during period t, P DR,max Indicates the maximum curtailment power that can interrupt the load.

7. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The power system and network constraints in S2 include node power balance constraints, line power constraints and thermal power unit operation constraints: (1) The node power balance constraint is set according to the following formula: S G P t,n G,s +S z P t,n VPP,z,s,out -S z P t,n VPP,z,s,in +S res P t,n res,s -P t,n TLD =S m B nm (d t,n s -d t,m s ):l n,s,t EN Among them, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant at node n in time period t in scenario s, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, P t,n res,s represents the real-time output of the renewable energy unit at node n in scenario s during period t, P t,n TLD represents the real-time power of the load on node n during period t, δ t,n s , δ t,m s They represent the phase angles of node n and node m in scene s during period t, G represents the thermal power unit, G∈Ψ n,g ,Ψ n,g represents the set of thermal power units at node n, z represents the type of participant, z∈{a,b,c}, a, b, c represent the participants of combined heat and power, energy storage participants, and load participants, res represents the photovoltaic unit, res∈Ψ n,res ,Ψ n,res represents the set of photovoltaic units at node n, m∈θ n ,θ n represents the set of downstream nodes of node n, m is the downstream node of node n, λ n,s,t EN The dual variable representing the constraint is the clearing power cost parameter of node n in scenario s during period t; (2) The line power constraint is set according to the following formula: |B nm (d t,n s -d t,m s )|≤P nm f,max Among them, B nm represents the line susceptance, δ t,n s , δ t,m s They represent the phase angles of node n and node m in scene s during period t, P nm f ,max It represents the maximum value of the power flow from node m to node n of the line; (3) The operating constraints of the thermal power unit are set according to the following formula: P n G,min ≤P t,n G,s ≤P n G,max P t,n G,s -P t-1,n G,s ≥P R,n G P t-1,n G,s -P t,n G,s ≥P U,n G Among them, P n G,max , P n G,min They represent the maximum and minimum power generation of the thermal power unit at node n, respectively. t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, P R,n G , P U,n G They respectively represent the maximum value of the real-time output increase and the maximum value of the decrease in the thermal power units in adjacent time periods.

8. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The objective function in S2 is set according to the following formula: F=Σ t S n {C n (P t,n G,s )+S z r t,n VPP,z,out P t,n VPP,z,s,out -S z r t,n VPP,z,in P t,n VPP,z,s,in +r res (P t,n res,s,max -P t,n res,s )} Among them, F represents the objective function, P t,n G,s represents the real-time output of the thermal power unit at node n in scenario s during period t, C n It's about P t,n G,s The function represents the cost parameter of the power generation output of the thermal power unit at node n; P t,n VPP,z,s,in , P t,n VPP,z,s,out They represent the power demand and power supply of the zth participant on node n in scenario s during period t, respectively, and ρ t,n VPP,z,in , t,n VPP,z,out They represent the cost parameters of the power demand and power supply of the zth participant at node n in period t, r res represents the wind loss penalty parameter, P t,n res,s represents the real-time output of renewable energy on node n in scenario s during period t, P t,n res,s,max represents the maximum output of renewable energy at node n in scenario s during period t, z∈{a,b,c}, z represents the type of participant, a, b, c represent the combined heat and power participant, energy storage participant, and load participant, respectively, n=1 to N e , N e Represents the number of grid nodes, t=1 to T, T represents the day-ahead scheduling period.

9. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The basic system parameters in S3 include: network parameters and power cost parameters, and the basic aggregated resource parameters in S3 include: internal equipment parameters of the combined heat and power participants, internal equipment parameters of the energy storage participants, and internal equipment parameters of the load participants.

10. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, characterized in that: The clearing results in S4 include the output configuration of physical parameters including the combined heat and power participants, energy storage participants and load participants in each time period, as well as the node power cost parameters and system average cost parameter results.

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