Random optimization scheduling method considering heterogeneous flexible resources and power grid toughness improvement

Abstract

The invention discloses a random optimization scheduling method considering heterogeneous flexible resources and power grid toughness improvement. The method comprises the steps of constructing a resource operation model according to operation characteristics of various heterogeneous flexible resources in a power system, considering a power grid operation state change process under an extreme weather condition, constructing a two-stage stochastic optimization scheduling model by taking the lowest operation cost of the power system as a target, determining constraint conditions of the two-stage stochastic optimization scheduling model, and establishing a two-stage stochastic optimization scheduling model according to the constraint conditions of the two-stage stochastic optimization scheduling model. And based on constraint conditions of the resource operation model and the two-stage stochastic optimization scheduling model, obtaining an optimal scheduling decision result, and configuring an actual operation state of the power system according to the scheduling decision result. According to the method, the randomness of a fault scene under an extreme condition is simulated by utilizing the probability model, and the toughness of the power system is effectively improved through the flexible power supply and load resource collaborative response and toughness index constraint.

Description

Technical Field

[0001] The present invention belongs to the field of power grid optimization and dispatching, and in particular relates to a random optimization and dispatching method that takes into account heterogeneous flexible resources and power grid resilience improvement. Background Art

[0002] In recent years, frequent extreme weather events around the world have seriously threatened the safe operation of power systems. The global climate and environment have deteriorated sharply in recent years. Extreme weather events such as droughts, floods, hurricanes, extreme heat and extreme cold have occurred frequently, and disaster losses have continued to increase. As the most important infrastructure, the safe and stable operation of energy and power systems is seriously affected by extreme weather. Extreme weather will not only cause a surge in load in a short period of time, but the sudden deterioration of operating conditions will also increase the failure rate of equipment such as power generation and transmission lines. Natural disasters accompanied by extreme weather may also cause damage to key facilities such as power plants, transmission lines, power equipment, and dispatching communications. Therefore, the study of power system resilience has been extended in the field of power system safety and stability. Different from the types and characteristics of faults dealt with by the "Guidelines for Power System Safety and Stability" and the "Three Lines of Defense", the theory of power system resilience deals with faults such as extreme weather with extremely low probability but extremely high harm.

[0003] On the other hand, the flexibility of my country's power system is insufficient, and the coordinated response capabilities of flexible power sources and load resources have not been fully utilized. From the perspective of power system flexibility, the flexible power sources on the power supply side and the flexible load resources on the load side are uniformly summarized as heterogeneous flexible resources, such as flexible power sources such as natural gas power generation, pumped storage, and new energy storage, and flexible load resources such as temperature control loads and electric vehicles. Various flexible resources can play an important role in the recovery of power systems under extreme conditions, but current research has not yet involved the dispatching strategy of coordinated response of various heterogeneous flexible resources to enhance the resilience of power systems. Therefore, it is urgent to develop an optimized dispatching model that takes into account the improvement of power grid resilience, so as to further improve the cross-temporal and spatial configuration efficiency of flexible resources and effectively release the multi-time scale flexibility of power systems. Summary of the invention

[0004] In order to solve the problems existing in the background technology, the purpose of the present invention is to provide a random optimization scheduling method that takes into account heterogeneous flexible resources and improved grid resilience. The present invention can give full play to the regulation capabilities of various flexible resources (including flexible power sources and load resources) under extreme weather conditions.

[0005] The technical solution adopted by the present invention comprises the following steps:

[0006] Step S1: First, a resource operation model is constructed according to the operation characteristics of various heterogeneous flexible resources in the power system; the heterogeneous flexible resources include gas generators, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and temperature control load systems;

[0007] Step S2, then considering the change process of the power grid operation state under extreme weather conditions, with the goal of minimizing the power system operation cost, a two-stage stochastic optimization scheduling model is constructed; the first stage of the two-stage stochastic optimization scheduling model is the preventive scheduling stage before the power system fails, and the second stage is the emergency recovery stage after the power system fails;

[0008] Step S3, determining the constraint conditions of the two-stage stochastic optimization scheduling model described in step S2;

[0009] Step S4: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimized scheduling result of the preventive scheduling stage is obtained. Then, the optimized scheduling result of the preventive scheduling stage is used as the boundary condition of the emergency recovery stage. Combined with the resource operation model, the best scheduling decision result of the emergency recovery stage is obtained as the final scheduling decision result of the power system, and the operating state of the actual power system is configured according to the final scheduling decision result.

[0010] The climbing speed of the gas generator set k in step S1 satisfies the following constraints:

[0011] -Rp k,max ≤ i,k,t -P i,k,t+1 ≤p k,max

[0012] Where P i,k,t and P i,k,t+1 They represent the power output level of gas generator set k at node i at time t and time t+1, Rp k,max Indicates the maximum ramp rate of gas generator set k;

[0013] The power generation of the pumped storage power station pu during the pumping and power generation process is obtained according to the following formula:

[0014]

[0015] Among them, S pu,t is the power generation capacity of the pumped storage power station pu in time period t, μ represents the efficiency coefficient of the pumping process, x pu,t It is a 0-1 variable that represents the state of the pumped storage power station, where 0 represents the pumping state and 1 represents the power generation state; They represent the generating power and pumping power of the pumped storage power station pu at time t, They represent the power generation flow and pumping flow of the pumped storage power station pu at time t, They represent the calculated values ​​of the generating head and pumping head of the pumped storage power station pu, ρ wrepresents the density of water, η M , η G , η P , η T They represent the motor efficiency, generator efficiency, hydraulic efficiency of the pump condition, and hydraulic efficiency of the generator condition, respectively. pu,max represents the maximum water head of the pumped storage power station pu, r pu,min It represents the minimum water head of pumped storage power station pu;

[0016] The expression of the charging and discharging process of the battery energy storage station es is as follows:

[0017]

[0018] In the formula, represents the state of charge of the battery energy storage station es in period t, η loss represents the loss coefficient of the battery energy storage station es, x es,t It is a 0-1 variable that represents the state of the battery energy storage station, 0 represents the charging state, 1 represents the discharging state, and They represent the charging power and discharging power of the battery energy storage station es in time period t, η ch and η dis is the charging efficiency and discharging efficiency of the battery energy storage power station, C Es is the rated capacity of energy storage, and They are the upper and lower limits of the state of charge of the battery energy storage station es respectively.

[0019] The charging and discharging capacity model of the electric vehicle charging station in step S1 is specifically as follows:

[0020]

[0021] in, is the charging battery capacity of the electric vehicle charging station evs during period t, is the discharge battery capacity of the electric vehicle charging station at time t, m represents the number of electric vehicles that the electric vehicle charging station evs can provide for charging and discharging during time period t, and They represent the charging capacity and discharging capacity of the electric vehicle ev in period t, C ev,bat is the battery capacity of the electric vehicle EV, is the maximum battery charge value, It represents the state of charge of the electric vehicle ev during the period t, The initial state of charge of the battery when the electric vehicle ev starts to interact with the power grid;

[0022] The response model of the temperature control load system is as follows:

[0023] RV A1 =P init -P min

[0024] RC A2 =P max -P init

[0025] RR A1 =RC A1 (1-α%) / RT A1

[0026] RR A2 =RC A2 (1-α%) / RT A2

[0027] Among them, RC A1 Represents the downward adjustable capacity of the temperature control load system ac, RC A2 Indicates the upward adjustable capacity of the temperature control load system, P init Represents the initial power of the temperature control load system, P max Indicates the maximum operating power of the temperature control load system, P min Indicates the minimum operating power of the temperature control load system, RR A1 Indicates the ramp rate of the downward adjustment process, RR A2 It represents the climbing rate of the upward adjustment process, % is the capacity deviation rate generated by the rebound effect, RT A1 RT is the response time of power down adjustment. A2 The response time for power adjustment upward.

[0028] In step S2, the two-stage random optimization scheduling model is specifically as follows in the preventive scheduling stage:

[0029]

[0030] in, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources in each failure scenario with probability p under the influence of extreme weather;

[0031] In the above formula, the operating cost of the power system before the failure The details are as follows:

[0032]

[0033] Among them, t0 represents the time when the fault occurs, N g 、N k 、Np 、N es 、N evs and N d They represent the number of coal-fired generating units, gas-fired generating units, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and loads in the power grid. and They represent the unit power generation costs of coal-fired generator g and gas-fired generator k respectively, and They represent the power output levels of coal-fired generator g and gas-fired generator k in period t under normal grid operation. and They represent the standby costs of coal-fired generator g and gas-fired generator k, respectively. They represent the upper and lower spinning reserve capacities of coal-fired generating unit g, They represent the upper and lower spinning reserve capacities of gas generator set k, and They represent the unit costs of pumped storage and hydropower generation in the pumped storage power station pu, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the normal operation of the power grid, and They represent the unit charging cost and unit discharging cost of the battery energy storage station es respectively, and They represent the unit charging cost and unit discharging cost of electric vehicle charging stations (EVS), and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, represents the unit load reduction cost, It represents the load reduction at node i at time t under normal grid operation;

[0034] In the above formula, the expected value of the sum of the operating cost and the adjustment cost of various heterogeneous flexible resources in each failure scenario with probability p is The details are as follows:

[0035]

[0036] Among them, N s represents the number of fault scenarios, T represents the total number of periods in the power system operation simulation process, and N acrepresents the number of temperature control load systems, p s represents the probability of failure scenario s, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k in period t under fault scenario s, and They represent the estimated power of pumped storage and discharge power generation of the pumped storage power station pu in time period t under the grid fault scenario s, and They represent the estimated charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, respectively, and c ac represents the unit cost of air conditioning load system adjustment, represents the power estimate of the air conditioning load system under fault scenario s, represents the estimated value of the load reduction at node i at time t under fault scenario s.

[0037] In step S2, the two-stage random optimization scheduling model in the emergency recovery stage is specifically as follows:

[0038]

[0039] Among them, C em represents the cost of emergency restoration of the power system, and They represent the power output levels of coal-fired generator g and gas-fired generator k in period y under fault scenario s, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the grid fault scenario s, and They represent the charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, represents the power value adjusted by the temperature control load system ac in the period t under the fault scenario s, represents the load reduction at node i at time t under fault scenario s.

[0040] In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the preventive scheduling stage is specifically as follows:

[0041] i) Power balance constraints at each node in the power grid:

[0042]

[0043] Among them, EG, GG, PU, ​​ES, EVS, and AC represent the coal-fired generator set, gas-fired generator set, pumped storage power station set, battery energy storage power station set, electric vehicle charging station set, and temperature control load system set connected to node i, respectively. EL represents the branch set connected to node i. and They represent the power output levels of coal-fired generator g and gas-fired generator k at node i at time t under normal grid operation. and represents the power of pumped storage and discharge power generation at the pumped storage power station pu at node i during period t under normal grid operation, and They represent the charging power and discharging power of the battery energy storage station es at node i during time period t under normal grid operation. and They represent the charging power and discharging power of the electric vehicle charging station evs at node i during period t under normal grid operation. represents the power of the temperature control load system ac at node i during period t under normal grid operation, represents the load power of node i at time t under normal grid operation, It represents the power flow of line l at time t under normal grid operation;

[0044] In the above formula, the power flow of line l is The relationship with the node phase angle is as follows:

[0045]

[0046] in, and They represent the phase angles of node i and node j at time t when the power grid is operating normally, and x l represents the impedance of line l;

[0047] Transmission line power constraints:

[0048]

[0049] Among them, f l,max Indicates the maximum value of the transmission power of line l;

[0050] Node phase angle constraint:

[0051]

[0052] Among them, θ i,max Indicates the maximum value allowed for the power angle deviation of node i;

[0053] ii) Reserve constraints for coal-fired and gas-fired generating units:

[0054]

[0055] in, and They represent the upper and lower spinning reserve capacities of the coal-fired generator g at node i under normal grid operation, and They represent the upper and lower spinning reserve capacities of gas generator set k at node i under normal grid operation, P ig,max and P ig,max They represent the minimum and maximum power generation of coal-fired generator sets, P ik,min and P ik,max Respectively represent the minimum and maximum power generation of the gas generator set;

[0056] iii) Pumped storage power station operation constraints:

[0057] Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are:

[0058]

[0059] Pumped storage power station pumping power constraints and power generation constraints:

[0060]

[0061]

[0062] in, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pi in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the pumped storage power station pu is charging. and They represent the upper and lower limits of the power when the pumped storage power station pu is discharging;

[0063] Pumped storage power stations cannot be charged and discharged at the same time:

[0064]

[0065] Wherein, M is a preset constant, and M takes a very large number;

[0066] Constraints on the power generation capacity of pumped storage power plants:

[0067]

[0068] Among them, S pu, is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, S pu, is the equivalent power generation of the minimum capacity of the reservoir;

[0069] iv) Battery energy storage power station operation constraints:

[0070] Among them, the constraints of the state of charge and charging and discharging power of the battery energy storage station are:

[0071]

[0072] The upper and lower limits of charging and discharging power of battery energy storage power stations:

[0073]

[0074] in, and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging;

[0075] Battery energy storage power stations cannot charge and discharge at the same time:

[0076]

[0077] The upper and lower limits of the state of charge of the battery energy storage station are:

[0078]

[0079] in, and They represent the minimum state of charge and the maximum state of charge of the battery energy storage station es respectively;

[0080] v) Electric vehicle charging station operation constraints:

[0081] Among them, the constraints of the state of charge of the electric vehicle charging station and the power of the charging and discharging process are:

[0082]

[0083] In the formula, represents the state of charge of the electric vehicle charging station evs during period t, η loss′ represents the loss coefficient of the electric vehicle charging station, evs,t is a 0-1 variable representing the state of an electric vehicle charging station (EVS), where 0 represents the charging state and 1 represents the discharging state. and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t, η ch′ and η dis′ Charging efficiency and discharging efficiency of electric vehicle charging stations;

[0084] The upper and lower limits of charging and discharging power of electric vehicle charging stations:

[0085]

[0086] in, and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the electric vehicle charging station is charging. and They represent the upper and lower limits of the power when the electric vehicle charging station evs is discharging;

[0087] Electric vehicle charging stations cannot charge and discharge at the same time:

[0088]

[0089] The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station:

[0090]

[0091] in, and They represent the minimum state of charge and the maximum state of charge of the electric vehicle charging station evs respectively;

[0092] vi) Climbing constraints of various types of heterogeneous flexible resources:

[0093]

[0094]

[0095] Among them, Rp g,max and Rp k,max They represent the maximum climbing speeds of coal-fired generator set g and gas-fired generator set k, respectively. and They represent the maximum climbing speed of the pumped storage power station pu during the charging process and the discharging process, and They represent the maximum climbing speed of the battery energy storage station es during the charging process and the discharging process, respectively. and Indicates the maximum climbing speed of the electric vehicle charging station evs during the charging and discharging process, Rp ac, It means that the response climbing speed of the air conditioning load system ac is the maximum;

[0096] vii) Load shedding constraints:

[0097]

[0098] in, It represents the load reduction at node i at time t under normal grid operation. It represents the load power of node i at time t when the power grid is in normal operation.

[0099] In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the emergency recovery phase is specifically as follows:

[0100] i) Power balance constraints at each node in the power grid:

[0101]

[0102] in, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k at node i at time t under fault scenario s, and represents the estimated power of pumped storage and discharge power generation at the pumped storage power station pu at node i in the fault scenario s during the period t, and They represent the estimated charging power and discharging power of the battery energy storage station es at node i in the fault scenario s during the period t, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs at node i in the fault scenario s during the period t, respectively. represents the power estimation value of the temperature control load system ac at node i in the fault scenario s during the period t, represents the estimated load power of node i at time t under power grid fault scenario s, represents the estimated load reduction value of node i at time t under the grid fault scenario s, represents the estimated value of the power flow of line l at time t under the grid fault scenario s;

[0103] In the above formula, the estimated value of line power flow is The relationship with the node phase angle is as follows:

[0104]

[0105] in, and They represent the estimated phase angles of node i and node j at time t under fault scenario s respectively;

[0106] Transmission line power constraints:

[0107]

[0108] Node phase angle constraints:

[0109]

[0110] ii) Reserve constraints for coal-fired and gas-fired units:

[0111]

[0112] iii) Pumped storage power station operation constraints:

[0113] Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are:

[0114]

[0115] in, and They represent the estimated values ​​of charging power and discharging power of the pumped storage power station pu during period t respectively;

[0116] Pumped storage power station pumping power constraints and power generation constraints:

[0117]

[0118] Pumped storage power stations cannot be charged and discharged at the same time:

[0119]

[0120] in, is a 0-1 variable of the pumped storage power station state under fault scenario s, 0 represents the pumping state and 1 represents the power generation state;

[0121] Constraints on the power generation capacity of pumped storage power plants:

[0122]

[0123] in, is the power generation capacity of the pumped storage power station pu in the fault scenario s during the period t, S pu,max is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, S pu,min is the equivalent power generation of the minimum capacity of the reservoir;

[0124] iv) Battery energy storage power station operation constraints:

[0125] Among them, the state of charge of the battery energy storage station and the power constraints of its charging and discharging process are:

[0126]

[0127] in, and They represent the estimated values ​​of charging power and discharging power of the battery energy storage station es in period t respectively;

[0128] The upper and lower limits of charging and discharging power of battery energy storage power stations:

[0129]

[0130] in, and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging;

[0131] Battery energy storage power stations cannot charge and discharge at the same time:

[0132]

[0133] in, is a 0-1 variable indicating the state of the battery energy storage power station under fault scenario s, where 0 indicates the pumping state and 1 indicates the power generation state;

[0134] The upper and lower limits of the state of charge of the battery energy storage station are:

[0135]

[0136] v) Electric vehicle charging station operation constraints:

[0137] Among them, the state of charge of the electric vehicle charging station and the power constraints of its charging and discharging process are:

[0138]

[0139] In the formula, and They represent the estimated values ​​of charging power and discharging power of the electric vehicle charging station evs during period t respectively;

[0140] The upper and lower limits of charging and discharging power of electric vehicle charging stations:

[0141]

[0142] Electric vehicle charging stations cannot charge and discharge at the same time:

[0143]

[0144]

[0145] in, is a 0-1 variable of the electric vehicle charging station evs state under fault scenario s, 0 represents the charging state and 1 represents the power generation state;

[0146] The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station:

[0147]

[0148] in, is the charge state of the electric vehicle charging station evs at time t under fault scenario s;

[0149] vi) Climbing constraints of various types of regulation resources:

[0150]

[0151] vii) Load shedding constraints:

[0152]

[0153] viii) Risk constraints:

[0154]

[0155] EENS T ≤EENS set

[0156] Among them, p s represents the probability of failure scenario s, EENS T Indicates the expected value of electric energy shortage, EENS set Indicates the preset expected threshold.

[0157] The step S4 is specifically as follows:

[0158] Step S4.1: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is obtained. The optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is Ω pre The details are as follows:

[0159]

[0160] Among them, Ω pre Indicates the optimized scheduling result in the preventive scheduling stage;

[0161] Step S4.2, then, the power output level and spare capacity of the coal-fired generator set g and the gas-fired generator set k at time t0 before the fault occurs in the circuit system are used as the boundary conditions for optimizing the scheduling decision of the two-stage stochastic optimization scheduling model in the emergency recovery stage;

[0162] Step S4.3: Combine the resource operation model and use the total power system operation cost C all The goal is to obtain the best dispatch decision result in the emergency recovery phase as the final dispatch decision result of the power system;

[0163] Total cost of power system operation C all According to the following formula:

[0164]

[0165] Among them, C em represents the cost of emergency restoration of the power system, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources in each failure scenario with probability p under the influence of extreme weather;

[0166] Step S4.4: Finally, the operating state of the actual power system is set according to the final dispatch decision result.

[0167] This method first analyzes and models the operating characteristics of various heterogeneous flexible resources, then considers the change process of power grid operation status under extreme weather conditions, and finally establishes a two-stage stochastic optimization scheduling model considering resilience improvement. The first stage of the two-stage stochastic optimization scheduling model is the preventive scheduling stage before the fault. According to the extreme weather warning information, the line disconnection under different fault scenarios is considered through the probability model, and the conventional power output plan and backup demand before the fault occurs are decided, as well as the preparation of various heterogeneous flexible resources, such as flexible power reserves. Reserve capacity, various energy storage devices are charged in the preparation stage to ensure sufficient power generation capacity, and the decision results of the first stage are used as the boundary conditions of the optimization decision in the second stage. The second stage is the emergency recovery stage after the fault occurs. Considering a variety of heterogeneous flexible resources, corrective scheduling is performed under the fault scenario that has occurred. This method uses the scheduling of various types of flexible resources to formulate a grid resilience improvement strategy, and uses the load shedding results of the corresponding scenarios to calculate the grid resilience index. By introducing the resilience index constraint in the model, the interaction between the two-stage scheduling before and after the extreme event is realized, thereby effectively improving the resilience of the power system.

[0168] The beneficial effects of the present invention are:

[0169] This paper proposes a random optimization scheduling method that considers heterogeneous flexible resources and grid resilience improvement. This method first analyzes and models the operating characteristics of various flexible resources, then considers the grid operation scheduling strategy under extreme weather conditions, and divides the optimization process into two stages before and after the fault occurs, namely the preventive scheduling stage before the fault and the emergency recovery stage after the fault occurs. Finally, a probability model is used to simulate the randomness of fault scenarios under extreme conditions, and through the coordinated response of flexible power and load resources and the constraints of resilience indicators, the resilience of the power system is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0170] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0171] The present invention is described in detail below in conjunction with specific implementation cases. The following implementation cases will help those skilled in the art to further understand the present invention, but will not limit the present invention in any form.

[0172] The specific steps of the embodiment of the present invention are as follows

[0173] Step S1: First, a resource operation model is constructed according to the operation characteristics of various heterogeneous flexible resources in the power system; the heterogeneous flexible resources include gas generators, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and temperature control load systems;

[0174] Step S2, then considering the change process of the power grid operation state under extreme weather conditions, with the goal of minimizing the power system operation cost, a two-stage stochastic optimization scheduling model is constructed; the first stage of the two-stage stochastic optimization scheduling model is the preventive scheduling stage before the power system fails, and the second stage is the emergency recovery stage after the power system fails;

[0175] Step S3, determining the constraint conditions of the two-stage random optimization scheduling model in step S2;

[0176] Step S4: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimized scheduling result of the preventive scheduling stage is obtained. Then, the optimized scheduling result of the preventive scheduling stage is used as the boundary condition of the emergency recovery stage. Combined with the resource operation model, the best scheduling decision result of the emergency recovery stage is obtained as the final scheduling decision result of the power system, and the operating state of the actual power system is configured according to the final scheduling decision result.

[0177] Compared with coal-fired generators, gas-fired generators are more energy-efficient, clean and low-carbon. They also have the advantages of rapid ramping, flexible operation and strong peak-shaving capability. Therefore, they play an increasingly important role in power supply and can also quickly respond to load fluctuations and rapid scheduling adjustments after failures. The ramping speed of gas-fired generator set k in step S1 satisfies the following constraints:

[0178] -Rp k,max ≤ i,k,t -P i,k,t+1 ≤p k,max

[0179] Where P i,k,t and P i,k,t+1 They represent the power output level of gas generator set k at grid node i at time t and time t+1, Rp k,max Indicates the maximum ramp rate of gas generator set k;

[0180] Pumped storage power stations are flexible and reliable in operation. They can not only switch between the two working conditions of pumping water to consume electricity and releasing water to generate electricity at will to achieve peak load shifting, but also assist the power grid in frequency and voltage regulation when the load of the power grid changes. The power generation capacity of a pumped storage power station is related to the capacity of the reservoir. The power generation capacity of a pumped storage power station is converted by the capacity of the reservoir, which will affect the power supply capacity during the accident recovery process.

[0181] The power generation of the pumped storage power station pu during the pumping and power generation process is obtained according to the following formula:

[0182]

[0183] Among them, S pu,tis the power generation capacity of the pumped storage power station pu in time period t, μ represents the efficiency coefficient of the given pumping process, x pu,t It is a 0-1 variable that represents the state of the pumped storage power station, where 0 represents the pumping state and 1 represents the power generation state; They represent the generating power and pumping power of the pumped storage power station pu at time t, They represent the power generation flow and pumping flow of the pumped storage power station pu at time t, They represent the calculated values ​​of the generating head and pumping head of the pumped storage power station pu, ρ w represents the density of water, η M , η G , η P , η T They represent the motor efficiency, generator efficiency, hydraulic efficiency of the pump condition, and hydraulic efficiency of the generator condition, respectively. pu,max The maximum water head of the pumped storage power station pu is the difference between the highest water level of the upper reservoir and the dead water level of the lower reservoir. pu,min It indicates the minimum head of the pumped storage power station pu, which is the difference between the dead water level of the upper reservoir and the highest water level of the lower reservoir. Generally, the head and head of the pumped storage power station pu are equal. The calculation value of the generating head and the pumping head of the water pump adopts the average value of the maximum head (head) and the minimum head (head);

[0184] Battery energy storage power stations have similar characteristics to pumped storage power stations. They can both achieve peak load shaving and valley filling of the power grid and assist in frequency modulation of the power grid. The operation status mainly depends on the state of charge (SoC) of the battery energy storage system. The expression of the charging and discharging process of the battery energy storage power station es is as follows:

[0185]

[0186] In the formula, represents the state of charge of the battery energy storage station es in period t, η loss represents the loss coefficient of the battery energy storage station es, es, It is a 0-1 variable that represents the state of the battery energy storage station, 0 represents the charging state, 1 represents the discharging state, and They represent the charging power and discharging power of the battery energy storage station es in time period t, η ch and η dis is the charging efficiency and discharging efficiency of the battery energy storage power station, C Es To ensure the rated capacity of energy storage and the stable operation of the energy storage system, the state of charge of the battery energy storage station needs to be limited to a certain range. and They are the upper and lower limits of the state of charge of the battery energy storage station es respectively.

[0187] With the rapid development and popularization of electric vehicles, large-scale charging of electric vehicles has become an important load in the operation of the power grid. Through intelligent regulation, a huge adjustment space can be provided for the power grid, and the response and recovery capabilities of the power grid under extreme weather conditions can be improved. Modeling the charging and discharging capacity of electric vehicle charging stations is divided into two steps. First, the adjustable capacity of the power grid through the charging and discharging process of a single electric vehicle is modeled, and then the charging station capacity is modeled.

[0188] The charging and discharging capacity model of the electric vehicle charging station in step S1 is as follows:

[0189] Among them, the formula for the charging and discharging power of an electric vehicle charging station that can interact with the power grid at a certain moment is as follows:

[0190]

[0191] When a single electric vehicle has excess power to participate in grid interaction, the battery capacity formula is as follows:

[0192]

[0193] in, is the charging battery capacity of the electric vehicle charging station evs during period t, is the discharge battery capacity of the electric vehicle charging station at time t, m represents the number of electric vehicles that the electric vehicle charging station evs can provide for charging and discharging during time period t, and They represent the charging capacity and discharging capacity of the electric vehicle ev in period t, C ev,bat is the battery capacity of the electric vehicle EV, is the maximum battery charge value, It represents the state of charge of the electric vehicle ev during the period t, The initial state of charge of the battery at which the electric vehicle ev can start to interact with the power grid;

[0194] There are a large number of fixed-frequency and variable-frequency air-conditioning loads in the power system. In some economically developed areas, the peak load accounts for more than 50%, with high regulation capacity and fast response speed. If the air-conditioning load is controlled and the operation mode of the air-conditioning is adjusted, the power supply regulation capacity of the power grid under extreme conditions will be improved. The temperature control load system response model can refer to the operating characteristics of the generator, and consider the unique rebound effect in the power recovery process after the air-conditioning load regulation is completed, and establish a flexible resource regulation characteristic evaluation index system including adjustable capacity, response speed, climbing rate, regulation duration and other indicators.

[0195] The response model of the temperature control load (air conditioning) system is as follows:

[0196] RC A1 =P init -P min

[0197] RC A2 =P max -P init

[0198] RR A1 =RC A1 (1-α%) / RT A1

[0199] RR A2 =RC A2 (1-α%) / RT A2

[0200] Among them, RC A1 Represents the downward adjustable capacity of the temperature control load system ac, RC A2 Indicates the upward adjustable capacity of the temperature control load system, P init Represents the initial power of the temperature control load system, P max Indicates the maximum operating power of the temperature control load system, P min Indicates the minimum operating power of the temperature control load system, RR A1 Indicates the ramp rate of the downward adjustment process, RR A2 represents the climbing rate of the upward regulation process, α% is the capacity deviation rate generated by the rebound effect, and RT A1 RT is the response time of power down adjustment. A2 The response time for power adjustment upward.

[0201] The objective function of the two-stage stochastic optimization scheduling model is to minimize the total cost of power system operation, which includes the preventive scheduling cost in the first stage and the emergency recovery related costs under extreme conditions in the second stage. Under extreme weather conditions with early warning, the goal is to minimize the power system operation cost, including the cost of the preventive scheduling stage and the cost of the emergency recovery stage. However, since the power grid failures caused by extreme conditions are random and the costs of the two stages are coupled, it is necessary to consider various scenarios of failures that will occur during the optimization process of the first stage. In step S2, the two-stage stochastic optimization scheduling model is specifically as follows in the preventive scheduling stage:

[0202]

[0203] in, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources (i.e., flexible power sources and load resources) in each failure scenario with probability p under the influence of extreme weather;

[0204] In the above formula, the operating cost of the power system before the failure The details are as follows:

[0205]

[0206] Among them, t0 represents the time when the fault occurs, N g 、N k 、N p 、N es 、N evs and N d They represent the number of coal-fired generating units, gas-fired generating units, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and loads in the power grid. and They represent the unit power generation costs of coal-fired generator g and gas-fired generator k respectively, and They represent the power output levels of coal-fired generator g and gas-fired generator k in period t under normal grid operation. and They represent the standby costs of coal-fired generator g and gas-fired generator k, respectively. They represent the upper and lower spinning reserve capacities of coal-fired generating unit g, They represent the upper and lower spinning reserve capacities of gas generator set k, and They represent the unit costs of pumped storage and hydropower generation in the pumped storage power station pu, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the normal operation of the power grid, and They represent the unit charging cost and unit discharging cost of the battery energy storage station es respectively, and They represent the unit charging cost and unit discharging cost of electric vehicle charging stations (EVS), and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, represents the unit load reduction cost, It represents the load reduction at node i at time t under normal operation of the power grid; g, k, pu, es, evs, and ac represent the index values ​​of coal-fired generator sets, gas-fired generator sets, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations, and temperature control load systems, respectively.

[0207] In the above formula, the expected value of the sum of the operating cost and the adjustment cost of various heterogeneous flexible resources in each failure scenario with probability p is The details are as follows:

[0208]

[0209] Among them, N s represents the number of fault scenarios, T represents the total number of periods in the power system operation simulation process, and N ac represents the number of temperature control load systems, p s represents the probability of failure scenario s, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k in period t under fault scenario s, and They represent the estimated power of pumped storage and discharge power generation of the pumped storage power station pu in time period t under the grid fault scenario s, and They represent the estimated charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, respectively, and c ac represents the unit cost of air conditioning load system adjustment, represents the power estimate of the air conditioning load system under fault scenario s, represents the estimated value of the load reduction at node i at time t under fault scenario s; s represents the index value of the fault scenario.

[0210] In step S2, the two-stage random optimization scheduling model in the emergency recovery stage is as follows:

[0211]

[0212] Among them, C em represents the cost of emergency restoration of the power system, and They represent the power output levels of coal-fired generator set g and gas-fired generator set k in period t under fault scenario s, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the grid fault scenario s, and They represent the charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, represents the power adjusted by the air conditioning load system ac in the period t under the fault scenario s, represents the load reduction at node i at time t under fault scenario s;

[0213] The two-stage stochastic optimization dispatch model in the preventive dispatch stage mainly considers the operation constraints of the power system based on the DC power flow model and the operation constraints of various heterogeneous flexible resources.

[0214] In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the preventive scheduling stage is as follows:

[0215] i) Power balance constraints at each node in the power grid:

[0216]

[0217] Among them, EG, GG, PU, ​​ES, EVS, and AC represent the coal-fired generator set, gas-fired generator set, pumped storage power station set, battery energy storage power station set, electric vehicle charging station set, and temperature control load system set connected to node i, respectively. EL represents the branch set connected to node i. and They represent the power output levels of coal-fired generator g and gas-fired generator k at node i at time t under normal grid operation. and represents the power of pumped storage and discharge power generation at the pumped storage power station pu at node i during period t under normal grid operation, and They represent the charging power and discharging power of the battery energy storage station es at node i during time period t under normal grid operation. and They represent the charging power and discharging power of the electric vehicle charging station evs at node i during period t under normal grid operation. represents the power of the temperature control load system ac at node i during period t under normal grid operation, represents the load power of node i at time t under normal grid operation, It represents the power flow of line l at time t under normal operation of the power grid; l represents the serial number of the line;

[0218] In the above formula, the power flow of line l is The relationship with the node phase angle is as follows:

[0219]

[0220] in, and They represent the phase angles of node i and node j at time t when the power grid is operating normally, and x l represents the impedance of line l;

[0221] Transmission line power constraints:

[0222]

[0223] Among them, f l,max Indicates the maximum value of the transmission power of line l;

[0224] Node phase angle constraint:

[0225]

[0226] Among them, θ i,max Indicates the maximum value allowed for the power angle deviation of node i;

[0227] ii) Reserve constraints for coal-fired and gas-fired generating units:

[0228]

[0229] in, and They represent the upper and lower spinning reserve capacities of the coal-fired generator g at node i under normal grid operation, and They represent the upper and lower spinning reserve capacities of gas generator set k at node i under normal grid operation, P ig,max and P ig,max They represent the minimum and maximum power generation of coal-fired generator sets, P ik,min and P ik,max Respectively represent the minimum and maximum power generation of the gas generator set;

[0230] iii) Pumped storage power station operation constraints. The power generation capacity of a pumped storage power station is related to the reservoir capacity:

[0231] Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are:

[0232]

[0233] Pumped storage power station pumping power constraints and power generation constraints:

[0234]

[0235] in, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the pumped storage power station pu is charging. and They represent the upper and lower limits of the power when the pumped storage power station pu is discharging;

[0236] Pumped storage power stations cannot be charged and discharged at the same time:

[0237]

[0238] Wherein, M is a preset constant, and M takes a preset extremely large number;

[0239] Constraints on the power generation capacity of pumped storage power plants:

[0240]

[0241] Among them, S pu,max is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, that is, the equivalent power generation of the reservoir under the highest water level allowed, S pu,min is the equivalent power generation of the minimum capacity of the reservoir;

[0242] iv) Battery energy storage power station operation constraints:

[0243] Among them, the constraints of the state of charge and charging and discharging power of the battery energy storage station are:

[0244]

[0245] The upper and lower limits of charging and discharging power of battery energy storage power stations:

[0246]

[0247] in, and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging;

[0248] Battery energy storage stations cannot charge and discharge at the same time:

[0249]

[0250] The upper and lower limits of the state of charge of the battery energy storage station are:

[0251]

[0252] in, and They represent the minimum state of charge and the maximum state of charge of the battery energy storage station es respectively;

[0253] v) Electric vehicle charging station operation constraints:

[0254] Among them, the constraints of the state of charge of the electric vehicle charging station and the power of the charging and discharging process are:

[0255]

[0256] In the formula, represents the state of charge of the electric vehicle charging station evs during period t, η loss′ represents the loss coefficient of the electric vehicle charging station, evs,t is a 0-1 variable that represents the state of an electric vehicle charging station (EVS), where 0 represents the charging state and 1 represents the discharging state. and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t, η ch′ and η dis′ Charging efficiency and discharging efficiency of electric vehicle charging stations;

[0257] The upper and lower limits of charging and discharging power of electric vehicle charging stations:

[0258]

[0259] in, and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the electric vehicle charging station is charging. and They represent the upper and lower limits of the power when the electric vehicle charging station evs is discharging;

[0260] Electric vehicle charging stations cannot charge and discharge at the same time:

[0261]

[0262] The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station:

[0263]

[0264] in, and They represent the minimum state of charge and the maximum state of charge of the electric vehicle charging station evs respectively;

[0265] vi) Climbing constraints of various types of heterogeneous flexible resources:

[0266]

[0267] Among them, Rp g,max and Rp k,max They represent the maximum climbing speeds of coal-fired generator set g and gas-fired generator set k, respectively. and They represent the maximum climbing speed of the pumped storage power station pu during the charging process and the discharging process, and They represent the maximum climbing speed of the battery energy storage station es during the charging process and the discharging process, respectively. and Indicates the maximum climbing speed of the electric vehicle charging station evs during the charging and discharging process, Rp ac, It indicates that the response climbing speed of the air-conditioning load system ac is the largest; the pumped storage power station, battery energy storage power station and electric vehicle charging station consider the climbing constraints of the bidirectional charging and discharging process respectively.

[0268] vii) Load shedding constraints:

[0269]

[0270] in, It represents the load reduction at node i at time t under normal grid operation. It represents the load power of node i at time t when the power grid is in normal operation.

[0271] In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the emergency recovery phase is as follows:

[0272] i) Power balance constraints at each node in the power grid:

[0273]

[0274] in, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k at node i at time t under fault scenario s, and represents the estimated power of pumped storage and discharge power generation at the pumped storage power station pu at node i in the fault scenario s during the period t, and They represent the estimated charging power and discharging power of the battery energy storage station es at node i in the fault scenario s during the period t, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs at node i in the fault scenario s during the period t, respectively. represents the power estimation value of the temperature control load system ac at node i in the fault scenario s during the period t, represents the estimated load power of node i at time t under power grid fault scenario s, represents the estimated load reduction value of node i at time t under the grid fault scenario s, represents the estimated value of the power flow of line l at time t under the grid fault scenario s;

[0275] In the above formula, the estimated value of line power flow is The relationship with the node phase angle is as follows:

[0276]

[0277] in, and They represent the estimated phase angles of node i and node j at time t under fault scenario s respectively;

[0278] Transmission line power constraints:

[0279]

[0280] Node phase angle constraints:

[0281]

[0282] ii) Reserve constraints for coal-fired and gas-fired units:

[0283]

[0284] iii) Pumped storage power station operation constraints. The power generation capacity of a pumped storage power station is related to the reservoir capacity:

[0285] Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are:

[0286]

[0287] in, and They represent the estimated values ​​of charging power and discharging power of the pumped storage power station pu during period t respectively;

[0288] Pumped storage power station pumping power constraints and power generation constraints:

[0289]

[0290] Pumped storage power stations cannot be charged and discharged at the same time:

[0291]

[0292] in, is a 0-1 variable of the pumped storage power station state under fault scenario s, 0 represents the pumping state and 1 represents the power generation state;

[0293] Constraints on the power generation capacity of pumped storage power plants:

[0294]

[0295] in, is the power generation capacity of the pumped storage power station pu in the fault scenario s during the period t, S pu, is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, that is, the equivalent power generation of the reservoir under the highest water level allowed, S pu, is the equivalent power generation of the minimum capacity of the reservoir;

[0296] iv) Battery energy storage power station operation constraints:

[0297] Among them, the state of charge of the battery energy storage station and the power constraints of its charging and discharging process are:

[0298]

[0299] in, and They represent the estimated values ​​of charging power and discharging power of the battery energy storage station es in period t respectively;

[0300] The upper and lower limits of charging and discharging power of battery energy storage power stations:

[0301]

[0302] in, and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging;

[0303] Battery energy storage stations cannot charge and discharge at the same time:

[0304]

[0305] in, is a 0-1 variable indicating the state of the battery energy storage power station under fault scenario s, where 0 indicates the pumping state and 1 indicates the power generation state;

[0306] The upper and lower limits of the state of charge of the battery energy storage station are:

[0307]

[0308] v) Electric vehicle charging station operation constraints:

[0309] Among them, the state of charge of the electric vehicle charging station and the power constraints of its charging and discharging process are:

[0310]

[0311] In the formula, and They represent the estimated values ​​of charging power and discharging power of the electric vehicle charging station evs during period t respectively;

[0312] The upper and lower limits of charging and discharging power of electric vehicle charging stations:

[0313]

[0314] Electric vehicle charging stations cannot charge and discharge at the same time:

[0315]

[0316] in, is a 0-1 variable representing the state of the electric vehicle charging station under fault scenario s, where 0 represents the charging state and 1 represents the power generation state.

[0317] The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station:

[0318]

[0319] in, is the charge state of the electric vehicle charging station evs at time t under fault scenario s;

[0320] vi) Climbing constraints of various types of regulation resources:

[0321]

[0322]

[0323] vii) Load shedding constraints:

[0324]

[0325] viii) Risk constraint: Risk constraint is an important indicator for considering grid resilience and is expressed as the expected energy shortage value (EENS). Based on the estimated value of load reduction, the EENS indicator can be calculated using the following formula:

[0326]

[0327] EENS T ≤EENS set

[0328] Among them, p s represents the probability of failure scenario s, EENS T Indicates the expected value of electric energy shortage, EENS set Indicates the preset expected threshold.

[0329] In the specific implementation, step S4 is specifically as follows:

[0330] Step S4.1: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is obtained. The optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is Ω pre The details are as follows:

[0331]

[0332] Among them, Ω pre Represents the optimized scheduling result in the preventive scheduling stage.

[0333] Step S4.2, then, the power output level and spare capacity of the coal-fired generator set g and the gas-fired generator set k at time t0 before the fault occurs in the circuit system are used as the boundary conditions for optimizing the scheduling decision of the two-stage stochastic optimization scheduling model in the emergency recovery stage;

[0334] Step S4.3: Combine the resource operation model and use the total power system operation cost C all The goal is to obtain the best dispatch decision result in the emergency recovery phase as the final dispatch decision result of the power system;

[0335] Total cost of power system operation C all According to the following formula:

[0336]

[0337] Among them, C em represents the cost of emergency restoration of the power system, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources in each failure scenario with probability p under the influence of extreme weather;

[0338] The optimal dispatch decision results in the emergency restoration phase include the power curves of coal-fired and gas-fired generators from the time t0 when the fault occurs to the time when the power system regains balance, the power curves of pumped storage power stations, battery energy storage power stations, and electric vehicle charging stations, as well as the power curves that need to be adjusted for the temperature control load system;

[0339] Step S4.4: Finally, the operating state of the actual power system is set according to the final dispatch decision result.

[0340] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement, characterized in that: The following steps are involved: Step S1: First, a resource operation model is constructed according to the operation characteristics of various heterogeneous flexible resources in the power system; the heterogeneous flexible resources include gas generators, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and temperature control load systems; Step S2, then considering the change process of the power grid operation state under extreme weather conditions, with the goal of minimizing the power system operation cost, a two-stage stochastic optimization scheduling model is constructed; the first stage of the two-stage stochastic optimization scheduling model is the preventive scheduling stage before the power system fails, and the second stage is the emergency recovery stage after the power system fails; Step S3, determining the constraint conditions of the two-stage stochastic optimization scheduling model described in step S2; Step S4: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimized scheduling result of the preventive scheduling stage is obtained. Then, the optimized scheduling result of the preventive scheduling stage is used as the boundary condition of the emergency recovery stage. Combined with the resource operation model, the best scheduling decision result of the emergency recovery stage is obtained as the final scheduling decision result of the power system, and the operating state of the actual power system is configured according to the final scheduling decision result.

2. A random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 1, characterized in that: The climbing speed of the gas generator set k in step S1 satisfies the following constraints: -Rp k,max ≤P i,k,t -P i,k,t+1 ≤Rp k,max Where P i,k,t and P i,k,t+1 They represent the power output level of gas generator set k at node i at time t and time t+1, Rp k,max Indicates the maximum ramp rate of gas generator set k; The power generation of the pumped storage power station pu during the pumping and power generation process is obtained according to the following formula: Among them, S pu,t is the power generation capacity of the pumped storage power station pu in time period t, μ represents the efficiency coefficient of the pumping process, x pu,t It is a 0-1 variable that represents the state of the pumped storage power station, where 0 represents the pumping state and 1 represents the power generation state; They represent the generating power and pumping power of the pumped storage power station pu at time t, They represent the power generation flow and pumping flow of the pumped storage power station pu at time t, They represent the calculated values ​​of the generating head and pumping head of the pumped storage power station pu, ρ w represents the density of water, η M , η G , η P , η T They represent the motor efficiency, generator efficiency, hydraulic efficiency of the pump condition, and hydraulic efficiency of the generator condition, respectively. pu,max represents the maximum water head of the pumped storage power station pu, r pu,min It represents the minimum water head of pumped storage power station pu; The expression of the charging and discharging process of the battery energy storage station es is as follows: In the formula, represents the state of charge of the battery energy storage station es in period t, η loss represents the loss coefficient of the battery energy storage station es, x es,t It is a 0-1 variable that represents the state of the battery energy storage station, 0 represents the charging state, 1 represents the discharging state, and They represent the charging power and discharging power of the battery energy storage station es in time period t, η ch and η dis is the charging efficiency and discharging efficiency of the battery energy storage power station, C ES is the rated capacity of energy storage, and They are the upper and lower limits of the state of charge of the battery energy storage station es respectively.

3. A random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 2, characterized in that: The charging and discharging capacity model of the electric vehicle charging station in step S1 is specifically as follows: in, is the charging battery capacity of the electric vehicle charging station evs during period t, is the discharge battery capacity of the electric vehicle charging station at time t, m represents the number of electric vehicles that the electric vehicle charging station evs can provide for charging and discharging during time period t, and They represent the charging capacity and discharging capacity of the electric vehicle ev in period t, C ev,bat is the battery capacity of the electric vehicle EV, is the maximum battery charge value, It represents the state of charge of the electric vehicle ev during the period t, The initial state of charge of the battery when the electric vehicle ev starts to interact with the power grid; The response model of the temperature control load system is as follows: r A1 =P init -P min r A2 =P max -P init RR A1 =RC A1 ·(1-α%) / RT A1 RR A2 =RC A2 ·(1-α%) / RT A2 Among them, RC A1 Represents the downward adjustable capacity of the temperature control load system ac, RC A2 Indicates the upward adjustable capacity of the temperature control load system, P init Represents the initial power of the temperature control load system, P max Indicates the maximum operating power of the temperature control load system, P min Indicates the minimum operating power of the temperature control load system, RR A1 Indicates the ramp rate of the downward adjustment process, RR A2 represents the climbing rate of the upward regulation process, α% is the capacity deviation rate generated by the rebound effect, and RT A1 RT is the response time of power down adjustment. A2 The response time for power adjustment upward.

4. According to claim 1, a random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement is characterized by: In step S2, the two-stage random optimization scheduling model is specifically as follows in the preventive scheduling stage: in, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources in each failure scenario with probability p under the influence of extreme weather; In the above formula, the operating cost of the power system before the failure The details are as follows: Among them, t0 represents the time when the fault occurs, N g 、N k 、N p 、N es 、N evs and N d They represent the number of coal-fired generating units, gas-fired generating units, pumped storage power stations, battery energy storage power stations, electric vehicle charging stations and loads in the power grid. and They represent the unit power generation costs of coal-fired generator g and gas-fired generator k respectively, and They represent the power output levels of coal-fired generator g and gas-fired generator k in period t under normal grid operation. and They represent the standby costs of coal-fired generator g and gas-fired generator k, respectively. They represent the upper and lower spinning reserve capacities of coal-fired generating unit g, They represent the upper and lower spinning reserve capacities of gas generator set k, and They represent the unit costs of pumped storage and hydropower generation in the pumped storage power station pu, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the normal operation of the power grid, and They represent the unit charging cost and unit discharging cost of the battery energy storage station es respectively, and They represent the unit charging cost and unit discharging cost of electric vehicle charging stations (EVS), and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, represents the unit load reduction cost, It represents the load reduction at node i at time t under normal grid operation; In the above formula, the expected value of the sum of the operating cost and the adjustment cost of various heterogeneous flexible resources in each failure scenario with probability p is The details are as follows: Among them, N s represents the number of fault scenarios, T represents the total number of periods in the power system operation simulation process, and N ac represents the number of temperature control load systems, p s represents the probability of failure scenario s, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k in period t under fault scenario s, and They represent the estimated power of pumped storage and discharge power generation of the pumped storage power station pu in time period t under the grid fault scenario s, and They represent the estimated charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, respectively, and c ac represents the unit cost of air conditioning load system adjustment, represents the power estimate of the air conditioning load system under fault scenario s, represents the estimated value of the load reduction at node i at time t under fault scenario s.

5. The random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 1 is characterized by: In step S2, the two-stage random optimization scheduling model in the emergency recovery stage is specifically as follows: Among them, C em represents the cost of emergency restoration of the power system, and They represent the power output levels of coal-fired generator set g and gas-fired generator set k in period t under fault scenario s, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the grid fault scenario s, and They represent the charging power and discharging power of the battery energy storage station es in time period t under the grid fault scenario s, and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t under the grid fault scenario s, represents the power value adjusted by the temperature control load system ac in the period t under the fault scenario s, represents the load reduction at node i at time t under fault scenario s.

6. A random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 3, characterized in that: In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the preventive scheduling stage is specifically as follows: i) Power balance constraints at each node in the power grid: Among them, EG, GG, PU, ​​ES, EVS, and AC represent the coal-fired generator set, gas-fired generator set, pumped storage power station set, battery energy storage power station set, electric vehicle charging station set, and temperature control load system set connected to node i, respectively. EL represents the branch set connected to node i. and They represent the power output levels of coal-fired generator g and gas-fired generator k at node i at time t under normal grid operation. and represents the power of pumped storage and discharge power generation at the pumped storage power station pu at node i during period t under normal grid operation, and They represent the charging power and discharging power of the battery energy storage station es at node i during time period t under normal grid operation. and They represent the charging power and discharging power of the electric vehicle charging station evs at node i during period t under normal grid operation. represents the power of the temperature control load system ac at node i during period t under normal grid operation, represents the load power of node i at time t under normal grid operation, It represents the power flow of line l at time t under normal grid operation; In the above formula, the power flow of line l is The relationship with the node phase angle is as follows: in, and They represent the phase angles of node i and node j at time t when the power grid is operating normally, and x l represents the impedance of line l; Transmission line power constraints: Among them, f l,max Indicates the maximum value of the transmission power of line l; Node phase angle constraint: Among them, θ i,max Indicates the maximum value allowed for the power angle deviation of node i; ii) Reserve constraints for coal-fired and gas-fired generating units: in, and They represent the upper and lower spinning reserve capacities of the coal-fired generator g at node i under normal grid operation, and They represent the upper and lower spinning reserve capacities of gas generator set k at node i under normal grid operation, P ig,max and P ig,max They represent the minimum and maximum power generation of coal-fired generator sets, P ik,min and P ik,max Respectively represent the minimum and maximum power generation of the gas generator set; iii) Pumped storage power station operation constraints: Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are: Pumped storage power station pumping power constraints and power generation constraints: in, and They represent the power of pumped storage and discharge power generation of the pumped storage power station pu in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the pumped storage power station pu is charging. and They represent the upper and lower limits of the power when the pumped storage power station pu is discharging; Pumped storage power stations cannot be charged and discharged at the same time: Wherein, M is a preset constant; Constraints on the power generation capacity of pumped storage power plants: Among them, S pu,max is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, S pu,min is the equivalent power generation of the minimum capacity of the reservoir; iv) Battery energy storage power station operation constraints: Among them, the constraints of the state of charge and charging and discharging power of the battery energy storage station are: The upper and lower limits of charging and discharging power of battery energy storage power stations: in, and They represent the charging power and discharging power of the battery energy storage station es in the period t under the normal operation of the power grid. and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging; Battery energy storage stations cannot charge and discharge at the same time: The upper and lower limits of the state of charge of the battery energy storage station are: in, and They represent the minimum state of charge and the maximum state of charge of the battery energy storage station es respectively; v) Electric vehicle charging station operation constraints: Among them, the constraints of the state of charge of the electric vehicle charging station and the power of the charging and discharging process are: In the formula, represents the state of charge of the electric vehicle charging station evs during period t, η loss′ represents the loss coefficient of the electric vehicle charging station, x evs,t is a 0-1 variable representing the state of an electric vehicle charging station (EVS), where 0 represents the charging state and 1 represents the discharging state. and They represent the charging power and discharging power of the electric vehicle charging station evs in time period t, η ch′ and η dis′ Charging efficiency and discharging efficiency of electric vehicle charging stations; The upper and lower limits of charging and discharging power of electric vehicle charging stations: in, and They represent the charging power and discharging power of the electric vehicle charging station evs in the period t under the normal operation of the power grid, and They represent the upper and lower limits of the power when the electric vehicle charging station is charging. and They represent the upper and lower limits of the power when the electric vehicle charging station evs is discharging; Electric vehicle charging stations cannot charge and discharge at the same time: The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station: in, and They represent the minimum state of charge and the maximum state of charge of the electric vehicle charging station evs respectively; vi) Climbing constraints of various types of heterogeneous flexible resources: Among them, Rp g,max and Rp k,max They represent the maximum climbing speeds of coal-fired generator set g and gas-fired generator set k, respectively. and They represent the maximum climbing speed of the pumped storage power station pu during the charging process and the discharging process, and They represent the maximum climbing speed of the battery energy storage station es during the charging process and the discharging process, respectively. and Indicates the maximum climbing speed of the electric vehicle charging station evs during the charging and discharging process, Rp ac,max It means that the response climbing speed of the air conditioning load system ac is the maximum; vii) Load shedding constraints: in, It represents the load reduction at node i at time t under normal grid operation. It represents the load power of node i at time t when the power grid is in normal operation.

7. A random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 3, characterized in that: In step S3, the operation constraint adjustment of the two-stage stochastic optimization scheduling model in the emergency recovery phase is specifically as follows: i) Power balance constraints at each node in the power grid: in, and They represent the estimated power output levels of coal-fired generator g and gas-fired generator k at node i at time t under fault scenario s, and represents the estimated power of pumped storage and discharge power generation at the pumped storage power station pu at node i in the fault scenario s during the period t, and They represent the estimated charging power and discharging power of the battery energy storage station es at node i in the fault scenario s during the period t, respectively. and They represent the estimated charging power and discharging power of the electric vehicle charging station evs at node i in the fault scenario s during the period t, respectively. represents the power estimation value of the temperature control load system ac at node i in the fault scenario s during the period t, represents the estimated load power of node i at time t under power grid fault scenario s, represents the estimated load reduction value of node i at time t under the grid fault scenario s, represents the estimated value of the power flow of line l at time t under the grid fault scenario s; In the above formula, the estimated value of line power flow is The relationship with the node phase angle is as follows: in, and They represent the estimated phase angles of node i and node j at time t under fault scenario s respectively; Transmission line power constraints: Node phase angle constraints: ii) Reserve constraints for coal-fired and gas-fired units: iii) Pumped storage power station operation constraints: Among them, the constraints on the power generation of pumped storage power stations, pumping power and power generation power are: in, and They represent the estimated values ​​of charging power and discharging power of the pumped storage power station pu during period t respectively; Pumped storage power station pumping power constraints and power generation constraints: Pumped storage power stations cannot be charged and discharged at the same time: in, is a 0-1 variable of the pumped storage power station state under fault scenario s, 0 represents the pumping state and 1 represents the power generation state; Constraints on the power generation capacity of pumped storage power plants: in, is the power generation capacity of the pumped storage power station pu in the fault scenario s during the period t, S pu,max is the equivalent power generation of the maximum capacity of the reservoir of the pumped storage power station pu, S pu,min is the equivalent power generation of the minimum capacity of the reservoir; iv) Battery energy storage power station operation constraints: Among them, the state of charge of the battery energy storage station and the power constraints of its charging and discharging process are: in, and They represent the estimated values ​​of charging power and discharging power of the battery energy storage station es in period t respectively; The upper and lower limits of charging and discharging power of battery energy storage power stations: in, and They represent the upper and lower limits of the power when the battery energy storage station es is charging. and They represent the upper and lower power limits of the battery energy storage station es when discharging; Battery energy storage stations cannot charge and discharge at the same time: in, is a 0-1 variable indicating the state of the battery energy storage power station under fault scenario s, where 0 indicates the pumping state and 1 indicates the power generation state; The upper and lower limits of the state of charge of the battery energy storage station are: v) Electric vehicle charging station operation constraints: Among them, the state of charge of the electric vehicle charging station and the power constraints of its charging and discharging process are: In the formula, and They represent the estimated values ​​of charging power and discharging power of the electric vehicle charging station evs during period t respectively; The upper and lower limits of charging and discharging power of electric vehicle charging stations: Electric vehicle charging stations cannot charge and discharge at the same time: in, is a 0-1 variable of the electric vehicle charging station evs state under fault scenario s, 0 represents the charging state and 1 represents the power generation state; The upper and lower limit constraints of the state of charge of the charging battery of the electric vehicle charging station: in, is the charge state of the electric vehicle charging station evs at time t under fault scenario s; vi) Climbing constraints of various types of regulation resources: vii) Load shedding constraints: viii) Risk constraints: AT SOMETIME T ≤ONCE set Among them, p s represents the probability of failure scenario s, EENS T Indicates the expected value of electric energy shortage, EENS set Indicates the preset expected threshold.

8. The random optimization scheduling method considering heterogeneous flexible resources and grid resilience improvement according to claim 1 is characterized by: The step S4 is specifically as follows: Step S4.1: Based on the resource operation model and the constraints of the two-stage random optimization scheduling model, the optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is obtained. The optimization scheduling result of the two-stage random optimization scheduling model in the preventive scheduling stage is Ω pre The details are as follows: Among them, Ω pre Indicates the optimized scheduling result in the preventive scheduling stage; Step S4.2, then, the power output level and spare capacity of the coal-fired generator set g and the gas-fired generator set k at time t0 before the fault occurs in the circuit system are used as the boundary conditions for optimizing the scheduling decision of the two-stage stochastic optimization scheduling model in the emergency recovery stage; Step S4.3: Combine the resource operation model and use the total power system operation cost C all The goal is to obtain the best dispatch decision result in the emergency recovery phase as the final dispatch decision result of the power system; Total cost of power system operation C all According to the following formula: Among them, C em represents the cost of emergency restoration of the power system, represents the operating cost of the power system before the failure, It represents the expected value of the sum of the operating costs and the adjustment costs of various heterogeneous flexible resources in each failure scenario with probability p under the influence of extreme weather; Step S4.4: Finally, the operating characteristics of the heterogeneous flexible resources in the actual power system are set according to the final dispatch decision result.

9. An electronic device, characterized in that: The method comprises a memory and a processor coupled to each other, wherein the memory stores program data, and the processor calls the program data to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having program data stored thereon, characterized in that: When the program data is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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