A power clearing assessment method considering aggregated resources and renewable energy output

Abstract

The present invention discloses a method for evaluating power clearing that considers aggregated resources and renewable energy output. Based on the statistical data of renewable energy output, renewable energy output constraints for each time period before the day are constructed; based on the aggregated resource output constraints, renewable energy output constraints, and power system and network constraints, model constraints are formed, and an objective function is constructed with minimizing the comprehensive operating cost as the optimization goal, and a day-ahead power clearing model is constructed; basic system parameters and aggregated resource basic parameters are obtained, and the load output for each time period before the day is set, combined with the maximum output scenario of renewable energy for each time period before the day, input data is constructed; based on the input data and the day-ahead power clearing model, the day-ahead power clearing model is solved by a solver to obtain the day-ahead power clearing result. The method of the present invention introduces aggregated resources to significantly reduce the risks brought by the volatility of new energy, ensuring the overall stability of the power system and the security of power supply and demand.

Description

Technical Field

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

[0002] As a key clean energy source, renewable energy continues to grow rapidly. Renewable energy, primarily photovoltaic and wind power, will become the primary energy source in my country. However, the volatility and intermittent nature of renewable energy output, particularly from wind and photovoltaic power, can shift their output boundaries. Therefore, as the proportion of renewable energy increases, it is crucial to address the risks of wind and solar power curtailment, as well as the drastic fluctuations in electricity cost parameters, arising from the uncertainty associated with renewable energy.

[0003] Existing power clearing methods consider three aspects: medium- and long-term power generation mechanisms, capacity guarantee mechanisms, and demand-side management mechanisms. While these mechanisms have mitigated the risks associated with renewable energy uncertainty to some extent, they also have several shortcomings. The medium- and long-term power generation mechanisms rely on forecast accuracy and struggle to address real-time supply and demand fluctuations. While capacity guarantee mechanisms ensure reliable power supply, they primarily rely on backup capacity and traditional power generation units. Traditional power generation has limited regulatory capacity when renewable energy output fluctuates significantly. Existing demand-side management mechanisms are often constrained by willingness to participate and response speed, making demand-side regulation difficult to immediately demonstrate, especially during large-scale fluctuations. 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 aggregated resources and renewable energy output.

[0005] The technical solution adopted in the present invention is:

[0006] The power clearing evaluation method of the present invention comprises the following steps:

[0007] S1. Using a normal distribution method in a computer based on historical statistical data on renewable energy output, generate a scenario of maximum renewable energy output for each time period on the previous day, and then construct renewable energy output constraints for each time period on the previous day;

[0008] S2. Based on the model constraints of aggregated resource output constraints, renewable energy output constraints, and power system and network constraints, an objective function is constructed with the optimization goal of minimizing the comprehensive operating cost, and then a day-ahead power clearing model is constructed;

[0009] S3. Obtain basic system parameters and aggregated resource parameters, set the load output for each time period before the previous day, and then construct input data based on the maximum output scenario of renewable energy for each time period before the previous day in S2;

[0010] S4. Based on 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.

[0011] The maximum output scenario of renewable energy in each period of the day before in S1 is set according to the following formula:

[0012] P t res,max =P t e,res,max +θ t res ,θ t res ~N(0,σ 2 )

[0013] 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, and σ is the standard deviation of the normal distribution.

[0014] The renewable energy output constraint in S1 is set according to the following formula:

[0015] 0≤P t res ≤P t res,max

[0016] Among them, P t res is the renewable energy output during period t, P t res,max is the maximum output of renewable energy during period t.

[0017] The aggregated 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;

[0018] The output constraints of the participants in the heat and power combination include unit constraints, heat storage tank constraints, energy storage unit constraints, and power and heat balance constraints:

[0019] (1) The unit constraints are set according to the following formula:

[0020] P i,t CH ≥max{C i,m h i,t CH +K, P i,min CH -Ci,v h i,t CH}

[0021] P i,t CH ≤P i,max CH -C i,v h i,t CH

[0022] P i,t CH -P i,t-1 CH ≤R U,i

[0023] P i,t-1 CH -P i,t CH ≤R D,i

[0024] h i,min CH ≤h i,t CH ≤h i,max CH

[0025] 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 It 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 unit heating heat, i,max CH 、P i,min CH They represent the maximum and minimum output of the i-th thermal power unit, 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;

[0026] (2) The heat storage tank constraint is set according to the following formula:

[0027] 0≤S t ≤S max

[0028] S t -S t-1 ≤S U

[0029] S t-1 -S t ≤S D

[0030] S ini =S fin

[0031] 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 Respectively represent the initial heat storage and final heat storage of the heat storage tank;

[0032] (3) The energy storage unit constraints are set according to the following formula:

[0033] 0≤P k,t ESS,a,dis ≤P k ESS,a,dismax

[0034] 0≤P k,t ESS,a,ch ≤P k ESS,a,chmax

[0035] 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

[0036] E k ESS,a,min ≤E k,t ESS,a ≤E k ESS,a,max

[0037] E k ini,a= E k fin,a

[0038] Where a represents the participants of the combined heat and power system, 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 heat and power combined participant, 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 participant during period t, E k,t ESS,a Indicates the state of charge of the 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 system, 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 represent the initial state of charge and final state of charge of the energy storage unit k in the heat and power combined power system respectively;

[0039] (4) The electrical and thermal balance constraints are set according to the following formula:

[0040] 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

[0041] Σ i h i,t CH =h t load +S t -S t-1

[0042] 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 participant during period t, P t LD,a P represents the actual electric load value of the heat and power joint participant during 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 the number of 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 represents the heat storage capacity of the heat storage tank during period t.

[0043] The output constraints of the energy storage participants include power balance constraints and energy storage unit constraints:

[0044] (1) The electrical balance constraint is set according to the following formula:

[0045] 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

[0046] Where b represents the energy storage participant, k = 1 to N ESS , N ESS Indicates 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,brepresents 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;

[0047] (2) The energy storage unit constraint is set according to the following formula:

[0048] 0≤P k,t ESS,b,dis ≤P k ESS,b,dismax

[0049] 0≤P k,t ESS,b,ch ≤P k ESS,b,chmax

[0050] 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

[0051] E k ESS,b,min ≤E k,t ESS,b ≤E k ESS,b,max

[0052] E k ini,b= E k fin,b

[0053] 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 It represents the state of charge 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 state of charge and final state of charge of the energy storage unit k of the energy storage participant.

[0054] The output constraints of the load-type participants include power balance constraints and interruptible load output constraints:

[0055] (1) The electrical balance constraint is set according to the following formula:

[0056] P t DR -P t LD,c =P t VPP,c,out -P t VPP,c,in

[0057] Among them, c represents the load-type participant, P t DR P represents the power reduction of the interruptible load during period t, 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;

[0058] (2) The interruptible load output constraint is set according to the following formula:

[0059] 0≤P t DR ≤P DR,max

[0060] Among them, P t DR P represents the power reduction of the interruptible load during period t, DR,max Indicates the maximum curtailment power that can interrupt the load.

[0061] The power system and network constraints in S2 include node power balance constraints, line power constraints, and thermal power unit operation constraints:

[0062] (1) The node power balance constraint is set according to the following formula:

[0063] 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

[0064] 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 combined heat and power participant, energy storage participant, and load participant, 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 ENThe dual variable representing the constraint is the clearing power cost parameter of node n in scenario s during period t;

[0065] (2) The line power constraint is set according to the following formula:

[0066] |B nm (δ t,n s -δ t,m s )|≤P nm f,max

[0067] 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;

[0068] (3) The operating constraints of the thermal power units are set according to the following formula:

[0069] P n G,min ≤P t,n G,s ≤P n G,max

[0070] P t,n G,s -P t-1,n G,s ≥P R,n G

[0071] P t-1,n G,s -P t,n G,s ≥P U,n G

[0072] 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, 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 R,n G 、P U,n GThey 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.

[0073] The objective function in S2 is set according to the following formula:

[0074] 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 )}

[0075] 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 function, which represents the cost parameter of the thermal power generation 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, ρ t,n VPP,z,in , ρ 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 time 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}, where z represents the type of participant, a, b, and c represent the combined heat and power participant, energy storage participant, and load participant, respectively, and n=1 to N e , N e represents the number of grid nodes, t=1 to T, and T represents the day-ahead scheduling period.

[0076] The basic system parameters in S3 include: network parameters and power cost parameters; 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.

[0077] 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.

[0078] The beneficial effects of the present invention are:

[0079] This study addresses the shortcomings of the aforementioned studies by introducing aggregated resources. By integrating a variety of flexible regulation mechanisms, such as distributed gas-fired units, energy storage units, and interruptible loads, aggregated resources enable real-time resource dispatch, improving the flexibility and responsiveness of the power system. Compared to traditional mechanisms, aggregated resources can not only cope with fluctuations in renewable energy output but also rationally adjust the power loads of different user groups. Furthermore, aggregated resources can address the shortcomings of traditional capacity assurance mechanisms and enhance the power system's regulatory capabilities.

[0080] 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 electricity 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

[0081] Figure 1 It is a flow chart of the present invention.

[0082] Figure 2 This is a topology diagram of the system in this embodiment.

[0083] Figure 3 This is a typical photovoltaic power generation curve.

[0084] Figure 4 Schematic diagram of the amount of abandoned light in two model environments.

[0085] Figure 5 Schematic diagram of the expected cost parameters of the system under two analysis environments.

[0086] Figure 6 Schematic diagram of the energy storage unit charging and discharging over time.

[0087] Figure 7 Schematic diagram of load reduction of interruptible load over time.

[0088] Figure 8 This is the convergence diagram of the simulation results. DETAILED DESCRIPTION

[0089] In order to better understand the present invention, the content of the present invention is further described with reference to the accompanying drawings and embodiments, but the embodiments of the present invention are not limited thereto.

[0090] A power clearing evaluation method of the present invention is as follows Figure 1 As shown, the embodiment includes the following steps:

[0091] 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 a computer, and the maximum output scenario of renewable energy for each time period before the day is generated, thereby constructing the renewable energy output constraints for each time period before the day.

[0092] 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:

[0093] P t res,max =P t e,res,max +θ t res ,θ t res ~N(0,σ 2 )

[0094] 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, and σ is the standard deviation of the normal distribution.

[0095] The renewable energy output constraint in S1 is set according to the following formula:

[0096] 0≤P t res ≤P t res,max

[0097] Among them, P t res is the renewable energy output during period t, P t res,max is the maximum output of renewable energy during period t.

[0098] S2. Based on the model constraints of aggregated resource output constraints, renewable energy output constraints, and power system and network constraints, an objective function is constructed with guaranteed renewable energy absorption as the boundary condition and minimization of comprehensive operating costs as the optimization goal, and then a day-ahead power clearing model is constructed.

[0099] The aggregated 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;

[0100] The output constraints of the participants in the combined heat and power system include unit constraints, thermal storage tank constraints, energy storage unit constraints, and power and heat balance constraints:

[0101] (1) The unit constraints are set according to the following formula:

[0102] P i,t CH ≥max{C i,m h i,t CH +K, P i,min CH -C i,v h i,t CH}

[0103] P i,t CH ≤P i,max CH -C i,v h i,t CH

[0104] P i,t CH -P i,t-1 CH ≤R U,i

[0105] P i,t-1 CH -P i,t CH ≤R D,i

[0106] h i,min CH ≤h i,t CH ≤h i,max CH

[0107] 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 It 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 unit heating heat, i,max CH 、P i,minCH They represent the maximum and minimum output of the i-th thermal power unit, 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.

[0108] (2) The heat storage tank constraint is set according to the following formula:

[0109] 0≤S t ≤S max

[0110] S t -S t-1 ≤S U

[0111] S t-1 -S t ≤S D

[0112] S ini =S fin

[0113] 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.

[0114] (3) The energy storage unit constraints are set according to the following formula:

[0115] 0≤P k,t ESS,a,dis ≤P k ESS,a,dismax

[0116] 0≤P k,t ESS,a,ch ≤P k ESS,a,chmax

[0117] 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

[0118] E k ESS,a,min ≤E k,t ESS,a ≤E k ESS,a,max

[0119] E k ini,a= E k fin,a

[0120] Where a represents the participants of the combined heat and power system, 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 heat and power combined participant, 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 participant during period t, E k,t ESS,a Indicates the state of charge of the 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 system, 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 represent the initial state of charge and final state of charge of the energy storage unit k in the heat and power combined participant respectively.

[0121] (4) The electrical and thermal balance constraints are set according to the following formula:

[0122] Σ i P i,t CH +Σk 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

[0123] Σ i h i,t CH =h t load +S t -S t-1

[0124] 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 participant during period t, P t LD,a P represents the actual electric load value of the heat and power joint participant during 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 the number of 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 represents the heat storage capacity of the heat storage tank during period t.

[0125] The output constraints of energy storage participants include power balance constraints and energy storage unit constraints:

[0126] (1) The electrical balance constraint is set according to the following formula:

[0127] Σ k P k,t ESS,b,dis -Σ k P k,tESS,b,ch -P t LD,b =P t VPP,b,out -P t VPP,b,in

[0128] Where b represents the energy storage participant, k = 1 to N ESS , N ESS Indicates 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.

[0129] (2) The energy storage unit constraint is set according to the following formula:

[0130] 0≤P k,t ESS,b,dis ≤P k ESS,b,dismax

[0131] 0≤P k,t ESS,b,ch ≤P k ESS,b,chmax

[0132] 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

[0133] E k ESS,b,min ≤E k,t ESS,b ≤E k ESS,b,max

[0134] E k ini,b= E k fin,b

[0135] 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 It represents the state of charge 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 state of charge and final state of charge of the energy storage unit k of the energy storage participant.

[0136] The output constraints of load-type participants include power balance constraints and interruptible load output constraints:

[0137] (1) The electrical balance constraint is set according to the following formula:

[0138] P t DR -P t LD,c =P t VPP,c,out -P t VPP,c,in

[0139] Among them, c represents the load-type participant, P t DR P represents the power reduction of the interruptible load during period t, 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.

[0140] (2) The interruptible load output constraint is set according to the following formula:

[0141] 0≤P t DR ≤P DR,max

[0142] Among them, P t DR P represents the power reduction of the interruptible load during period t, DR,max Indicates the maximum curtailment power that can interrupt the load.

[0143] The power system and network constraints in S2 include node power balance constraints, line power constraints, and thermal power unit operation constraints:

[0144] (1) The node power balance constraint is set according to the following formula:

[0145] 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

[0146] 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,ms 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 combined heat and power participant, energy storage participant, and load participant, 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.

[0147] (2) The line power constraint is set according to the following formula:

[0148] |B nm (δ t,n s -δ t,m s )|≤P nm f,max

[0149] 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 on the line.

[0150] (3) The operating constraints of thermal power units are set according to the following formula:

[0151] P n G,min ≤P t,n G,s ≤P n G,max

[0152] P t,n G,s -P t-1,n G,s ≥P R,n G

[0153] P t-1,n G,s -P t,n G,s≥P U,n G

[0154] 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, 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 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.

[0155] The comprehensive operating cost in S2 includes the total power generation cost and the penalty cost for curtailment of solar power. The objective function is set according to the following formula:

[0156] 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 )}

[0157] 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 function, which represents the cost parameter of the thermal power generation 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, ρ t,n VPP,z,in , ρ 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 time period t, r resrepresents 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}, where z represents the type of participant, a, b, and c represent the combined heat and power participant, energy storage participant, and load participant, respectively, and n=1 to N e , N e represents the number of grid nodes, t = 1 to T, where T represents the day-ahead dispatch period. Generally, the wind loss penalty parameter is set large to ensure that renewable energy is fully absorbed while meeting the constraints.

[0158] 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 based on the maximum output scenario of renewable energy for each time period before the day in S2.

[0159] S4. Based on 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 results, i.e., 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 results, relevant resources are configured to control the operation of the power system.

[0160] The nodes in the present invention are nodes of an actual power system in a certain area, wherein the aggregated resources respectively aggregate corresponding internal equipment access nodes, renewable energy units, and thermal power units are also connected to the nodes in the system.

[0161] The basic system parameters in S3 include: network parameters and power cost parameters; 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.

[0162] Network parameters include: the upper limit of the power flow of the transmission line P nm f,max , the line's 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 of the reduction P U,n G .

[0163] The power cost parameters include: the cost parameter C of the thermal power unit power outputn , the cost parameter ρ of the aggregated resource for power demand t,n VPP,z,in , the cost parameter ρ of power supply t,n VPP,z,out .

[0164] The input data includes basic system parameters, basic parameters of aggregated resources, load output in each time period before the day, and maximum output scenario of renewable energy in each time period before the day.

[0165] The clearing results in S4 include the output configuration of physical parameters of 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.

[0166] In the present invention, participants 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 the 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 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.

[0167] Based on the clearing model in step 3, the node power balance constraint for each time period in each scenario is solved based on the clearing model in step 3, and the dual variable of the node power balance constraint for 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 using the following risk assessment indicators;

[0168] The risk control capability of the present invention can be verified by risk assessment indicators. 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;

[0169] The node cost parameter is set according to the following formula:

[0170] π n,s,t EN =λ n,s,t EN

[0171] 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.

[0172] The system average power cost parameter is set according to the following formula:

[0173] π s,t EN =Σ n π n,s,t EN P n,t TLD / P t TLD

[0174] 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 load power of node n, P t TLD Indicates the total power of the system load during period t, n=1 to N e , N e Indicates the number of grid nodes.

[0175] Expected cost parameter π' t EN The following formula is used to evaluate the expected level of the system's average cost parameter in all possible scenarios:

[0176] π' t EN =Σ s P s π s,t EN

[0177] Among them, π' t EN Represents the system expected cost parameter for 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.

[0178] (2) Convergence criterion of simulation results: Based on N s The convergence of the results is analyzed by looking at the variance coefficient of the simulation results. The convergence standard is defined as follows: the results are considered converged only when the variance coefficient of each time period is below the specified threshold; based on N s The simulation results, the variance coefficient R t It can be defined as:

[0179] R t =(σ t ) 1 / 2 / ((N s ) 1 / 2 π' t EN )

[0180] Among them, σ t Indicates N s The standard deviation of the cost parameter in period t under the simulation results.

[0181] (3) Determine the risk assessment indicators for each period before the final date.

[0182] To facilitate understanding and implementation by 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.

[0183] The embodiment system adopts the improved actual power system of a certain area, and the system topology is as follows: 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 calculation, and the base capacity is 100.

[0184] Table 1 Unit parameter information

[0185] Unit number 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

[0186] Based on the above parameters, the system in this embodiment sets two model environments.

[0187] Model environment 1: The objects of power clearing include various aggregated resources, conventional units, and new energy sources.

[0188] Model environment 2: The objects of power clearing include conventional units and new energy.

[0189] The amount of wind and solar 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 uncertainty risks are considered, the amount of wind and solar power curtailment in model environment 1 is significantly less than that in model environment 2, and the fluctuation of the expected power cost parameters in model environment 1 is also significantly less 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 curtailment and drastic fluctuations in power cost parameters caused by the uncertainty risks of renewable energy.

[0190] 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 determined by Figure 6 、 7 As shown by Figure 6 、 7 As can be seen, after the model incorporates the three types of aggregated resources, once the PV units begin generating power, their output effectively meets the load demand, thereby reducing the power cost parameter. While the power cost parameter decreases, internal energy storage is adjusted to increase charging capacity, slowing the further decline in the power cost parameter. As the PV unit output gradually decreases and the load demand further increases, the system's power cost parameter increases. This is because the PV unit output decreases, and the system's marginal unit becomes the high-cost thermal power unit in the market. However, the power cost parameter in model scenario 1 also increases more slowly. This is because, as the power cost parameter increases, internal resources, including thermal power units and interruptible loads, adjust their output in a timely manner, increasing external power supply while still meeting their own load demand, thus slowing the further increase in the power cost parameter.

[0191] Next, we will explain the convergence of the simulation results. Taking model environment 1 as an example, we calculate the variance coefficient of the simulation results for 10,000 times until the simulation coefficient reaches the set convergence standard of 0.05, stop the simulation, and draw the changes of the simulation coefficient under the two model environments with the number of simulations, as shown in the figure below. Figure 8 As shown in Figure 2, 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.

[0192] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection 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 on renewable energy output, generate a scenario of maximum renewable energy output for each time period on the previous day, and then construct renewable energy output constraints for each time period on the previous day; S2. Based on the model constraints of aggregated resource output constraints, renewable energy output constraints, and power system and network constraints, an objective function is constructed with the optimization goal of minimizing the comprehensive operating cost, and then a day-ahead power clearing model is constructed; The aggregated 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 power 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 It 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 unit heating heat, i,max CH 、P i,min CH They represent the maximum and minimum output of the i-th thermal power unit, 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; (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 Respectively represent the initial heat storage and final heat storage of the heat storage tank; (3) The energy storage unit constraints are 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 heat and power combined participant, 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 participant during period t, E k,t ESS,a Indicates the state of charge of the 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 system, 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 represent the initial state of charge and final state of charge of the energy storage unit k in the heat and power combined power system respectively; (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 participant during period t, P t LD,a P represents the actual electric load value of the heat and power joint participant during 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 the number of 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 represents the heat storage capacity of the heat storage tank during period t; S3. Obtain basic system parameters and aggregated resource parameters, set the load output for each time period before the previous day, and then construct input data based on the maximum output scenario of renewable energy for each time period before the previous day in S2; S4. Based on 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. The 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, 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 during period t.

4. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, 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 Indicates 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 It represents the state of charge 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 state of charge and final state of charge of the energy storage unit k of the energy storage participant.

5. The method for evaluating power clearing considering aggregated resources and renewable energy output according to claim 1, 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 P represents the power reduction of the interruptible load during period t, 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 P represents the power reduction of the interruptible load during period t, DR,max Indicates the maximum curtailment power that can interrupt the load.

6. 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 combined heat and power participant, energy storage participant, and load participant, 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 Indicates the maximum value of the power flow from node m to node n of the line; (3) The operating constraints of the 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, 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 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.

7. 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 function, which represents the cost parameter of the thermal power generation 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, ρ t,n VPP,z,in , ρ 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 time 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}, where z represents the type of participant, a, b, and c represent the combined heat and power participant, energy storage participant, and load participant, respectively, and n=1 to N e , N e represents the number of grid nodes, t=1 to T, and T represents the day-ahead scheduling period.

8. 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; 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.

9. 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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