Novel power system multi-element flexibility resource planning method in extreme weather

Abstract

The invention discloses a novel power system multi-element flexibility resource planning method in extreme weather, and the method comprises the steps: building a flexibility resource model of a novel power system in conventional weather, and the flexibility resource model comprises a power side flexibility resource model, a load side flexibility resource model and an energy storage side flexibility resource model; on the basis, establishing a flexibility resource mathematical model of the novel power system in extreme weather; extreme weather is divided into environment type and disaster type, the standby thermal power generating unit is added to the environment type extreme weather, and the mobile energy storage vehicle is added to the disaster type extreme weather; the method comprises the following steps: establishing a flexibility resource planning model in extreme weather by taking total cost minimization as a target function, and setting investment constraint conditions and operation constraint conditions, and performing linearization processing and solving on the flexibility resource planning model in the extreme weather to obtain a multi-element flexibility resource planning result of the novel power system in the extreme weather. According to the invention, the flexibility and economy of the novel power system in extreme weather can be effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of power systems, and more specifically, relates to a novel method for planning multiple flexibility resources in power systems under extreme weather conditions. Background Technology

[0002] Under the "dual carbon" target, the "dual high" characteristics of high-proportion renewable energy integration and high-proportion power electronic equipment application exacerbate the uncertainty of the new power system. As the support capacity of traditional power sources declines, leading to a weakening of system flexibility, this contradiction becomes increasingly prominent under the dual effects of load characteristic changes and fluctuations in new energy output. Traditional power system flexibility resource planning typically only considers regular weather conditions; however, global climate change has made extreme weather a major factor affecting power system reliability. How to achieve systematic optimization of flexibility resources across the power generation, grid, load, and storage sides, and improve the system's supply-demand balance flexibility under extreme weather conditions, has become a key technical challenge for the new power system.

[0003] However, existing research has not fully considered the diversity of extreme weather and its impact on the differentiation of power systems, making it difficult to meet the flexibility requirements of power systems under complex extreme weather conditions. Regarding resource planning models, few studies have been able to comprehensively integrate multiple types of flexibility resources and fully explore their synergistic potential to achieve flexible and efficient system operation under different operating conditions. Therefore, it is necessary to propose a novel multi-dimensional flexibility resource planning method for power systems under extreme weather conditions to effectively improve the flexibility and economy of new power systems under extreme weather conditions. Summary of the Invention

[0004] To address the shortcomings of existing research and the need for optimization, this invention proposes a multi-dimensional flexibility resource planning method for novel power systems under extreme weather conditions, in order to improve the supply and demand balance flexibility of novel power systems under extreme weather conditions.

[0005] To achieve the above objectives, the technical solution adopted by this invention is as follows: In a first aspect, the present invention provides a novel multi-dimensional flexibility resource planning method for power systems under extreme weather conditions, the method comprising: S1. Establish a flexibility resource model for a new type of power system under normal weather conditions, including flexibility resource models for the power source side, load side, and energy storage side. S2. Based on the flexibility resource model of the new power system under normal weather conditions, establish a mathematical model of the flexibility resource of the new power system under extreme weather conditions; the extreme weather is divided into environmental type and disaster type. In environmental type extreme weather, a backup thermal power unit is added, and in disaster type extreme weather, a mobile energy storage vehicle is added. S3. With the goal of minimizing total cost, establish a flexible resource planning model for extreme weather conditions. The total cost includes investment cost and operating cost, and set investment constraints and operating constraints. S4. Linearize and solve the flexibility resource planning model under extreme weather conditions to obtain the multivariate flexibility resource planning results of the new power system under extreme weather conditions.

[0006] In the above scheme, step S1 includes: S11. Establish a power supply side flexibility resource model, including: determining the output characteristics and upward and downward flexibility adjustment capabilities of conventional thermal power units and flexible retrofitted thermal power units, and combining conventional thermal power units and flexible retrofitted thermal power units to obtain the power supply side flexibility adjustment capability. S12. Establish a load-side flexibility resource model, including: determining the maximum power of demand response, simplifying demand response into peak-shaving loads and valley-filling loads, with peak-shaving loads providing upward flexibility adjustment capability for the system and valley-filling loads providing downward flexibility adjustment capability for the system. S13. Establish flexible resources on the energy storage side, including: setting up an energy storage system. During periods of low electricity demand, the energy storage system acts as an electrical device, storing excess electricity from renewable energy sources. During periods of high electricity demand, the energy storage system acts as a power generation device, releasing the stored electricity to supply power to the system. S14. Based on the combined resources of the power supply side, load side, and energy storage side, determine the system's flexibility and adjustment capabilities under normal weather conditions; details are as follows:

[0007]

[0008] In the formula: , For each system Flexible adjustment capability; , for The up and down adjustment capability of the power supply side; , They are respectively The ability to adjust upward and downward loads; , They are respectively Upward and downward adjustment capabilities of the energy storage side.

[0009] In the above scheme, step S2 includes: S21. Based on the comprehensive impact characteristics of extreme weather on new power systems, extreme weather is classified into environmental and disaster types. S22. For extreme weather events, add backup thermal power units and establish a mathematical model for flexibility resources under extreme weather conditions; the specific steps of S22 are as follows: Adding standby thermal power units to the environmental extreme weather conditions and determining the vertical flexibility adjustment capability of the standby thermal power units. and ; The system's flexibility and adjustability under extreme weather conditions meet the following requirements:

[0010]

[0011] S23. For severe extreme weather events, add backup thermal power units and mobile energy storage vehicles to establish a mathematical model of flexibility resources under severe extreme weather conditions; the specific steps of S23 are as follows: In the event of severe weather, backup thermal power units and mobile energy storage vehicles are added, with the mobile energy storage vehicles providing upsizing capability; assuming the total capacity of the mobile energy storage vehicles is... The maximum discharge power of the mobile energy storage vehicle is The system adjustment flexibility provided by mobile energy storage vehicles under severe weather conditions meets the following requirements:

[0012] In the formula: Provides mobile energy storage vehicles with system flexibility and adjustability; for Discharge power of mobile energy storage vehicle; Improve the efficiency of mobile emergency power supply; Ultimately, the system's flexibility and adjustability under extreme weather conditions must meet the following requirements:

[0013]

[0014] In the formula: and To enhance the system's flexibility and adjustability under environmental and disaster-related extreme weather conditions; , for The up and down adjustment capability of the power supply side; , They are respectively The ability to adjust upward and downward loads; , They are respectively Upward and downward adjustment capabilities of the energy storage side.

[0015] In the above scheme, step S2 also includes: S24. Set evaluation indicators to measure system flexibility requirements, including annual imbalance risk coefficient, upward adjustment of insufficient flexibility power expectation value, downward adjustment of insufficient flexibility power expectation value, upward adjustment of insufficient flexibility power expectation value, and downward adjustment of insufficient flexibility power expectation value.

[0016] In the above scheme, step S3 includes: S31. The objective function of the flexibility resource planning model under extreme weather conditions is to minimize the sum of investment costs and operating costs.

[0017] In the formula: For investment costs; Operating costs; S32. Investment costs include the cost of adapting thermal power units for flexibility. Demand response investment costs Energy storage system investment costs Cost of extending the life of standby thermal power units and mobile energy storage investment costs The details are as follows:

[0018] S33, System operating costs under normal weather conditions Including the cost of power curtailment penalties Load shedding penalty cost Operating costs of thermal power units Demand response compensation costs and variable operation and maintenance costs of energy storage systems The details are as follows:

[0019] System operating costs under extreme weather conditions This also includes the operating costs of standby thermal power units. The details are as follows:

[0020] System operating costs under severe extreme weather conditions This also includes the cost of mobile power supply from mobile energy storage vehicles. The details are as follows:

[0021] Investment constraints and operational constraints are set.

[0022] The specific investment costs for the above plan are as follows: Let the capital recovery coefficient be ,have:

[0023] In the formula: The discount rate; For the planning cycle; (1) The annual value of the cost of flexible retrofitting of thermal power units meets the following requirements:

[0024] In the formula: Unit cost for flexibility retrofitting of thermal power units; Capacity for flexible modification of thermal power units; This refers to the output coefficient of conventional thermal power units; This refers to the output coefficient during the oil injection phase. (2) The annual value of demand response investment costs, etc., is satisfied:

[0025] In the formula: Compensation for costs per unit of demand response; The proportion of demand response to maximum load; Maximum load; (3) The annual value of the energy storage system investment cost meets the following requirements:

[0026] In the formula: , These represent the unit investment cost for the energy storage system's power and capacity, respectively. Fixed operation and maintenance costs per unit of energy storage system; This represents the maximum charging and discharging power of the energy storage system. This represents the maximum amount of electricity that the energy storage system can store. (4) The life extension cost of standby thermal power units meets the following requirements:

[0027] In the formula: The cost per unit capacity of refurbished retired thermal power units to extend their service life; For the capacity of decommissioned thermal power units; (5) Investment cost of mobile energy storage vehicle, the annual value of investment cost of mobile energy storage vehicle, etc., meets the following requirements:

[0028] In the formula: Unit investment cost for mobile energy storage vehicles; This represents the maximum discharge power of the mobile energy storage vehicle. The specific operating costs are as follows: (1) The cost of power curtailment penalty is satisfied:

[0029] In the formula: Cost per unit of abandoned electricity; for Power abandoned per hour; (2) The load shedding penalty cost is satisfied:

[0030] In the formula: Penalty cost per load shedding unit; This refers to the load shedding power; (3) Operating costs of thermal power units, including operating costs of conventional thermal power units that have not undergone modification. Flexibility modification of thermal power unit operating costs Carbon emission costs of thermal power units ,satisfy:

[0031] (4) Demand response compensation costs are met:

[0032] In the formula: A unified subsidy unit price is set for the system's demand-side response; Variables are 0-1, where 1 represents When the load is a valley filling type, 0 indicates The load was peak-shaving. for Peak-valley demand response load power; for Peak-shaving demand response load power; (5) The variable operation and maintenance cost of an energy storage system includes discharge cost and charging cost. Only one state can exist at any given time. Therefore, the variable operation and maintenance cost of an energy storage system satisfies:

[0033] In the formula: The unit variable operation and maintenance cost of energy storage systems; The variables are 0-1, where 1 indicates that the energy storage system is in... Discharge at any time, 0 indicates that the energy storage system is in a state of constant discharge. Always charging; for Discharge power of the energy storage system; for Time-based energy storage system charging power; (6) The operating cost of the standby unit is calculated using the same formula as that of the conventional thermal power unit; (7) The operating cost of the mobile energy storage vehicle meets the following requirements:

[0034] In the formula: Unit operating cost of mobile energy storage vehicles; The variables are 0-1, where 1 indicates that the mobile energy storage vehicle is in Discharging at any time, 0 indicates that the mobile energy storage vehicle is in operation. Not running at any time; for Power supply of mobile energy storage vehicle; Labor costs for providing mobile power; This refers to diesel fuel consumption.

[0035] In the above scheme, the operating cost of conventional thermal power units includes coal consumption costs. and start-up / shutdown costs ,satisfy:

[0036]

[0037]

[0038] In the formula: , , For the consumption of secondary, primary, and constant coefficients; , These are the costs of starting up and stopping the generator unit, respectively. For the first Output of conventional thermal power units; For the first Timing group start / stop state variables For the first Timing group start / stop state variables; The operating costs of flexible retrofit units include basic operating costs. Unit life loss cost Combustion fuel cost The operating costs are segmented according to different operating states as follows:

[0039]

[0040]

[0041] In the formula: This is the unit operating loss coefficient; For the cost of purchasing the equipment; This represents the number of rotor-induced cracking cycles. Price per unit of oil; for Timing fuel consumption; , These are the minimum and maximum technical outputs of conventional thermal power units, respectively. To provide the minimum technical output during the non-oil injection phase after the flexibility upgrade; To achieve the minimum technical output during the oil injection phase after the flexibility upgrade; The carbon emission cost of thermal power units meets the following requirements:

[0042] In the formula: Carbon emissions per unit of electricity generated by a thermal power unit; The cost of carbon trading per unit of carbon emissions.

[0043] In the above scheme, the investment constraints include power constraints, electricity consumption constraints, equipment utilization hours constraints, investment cost constraints, and thermal power unit ratio constraints, as detailed below: (1) Power constraints: Planned installed capacity of wind turbine generators Photovoltaic generator unit capacity Conventional thermal power unit capacity Flexible modification of unit capacity The sum must be greater than the maximum load power. :

[0044] (2) Power Constraint: Utilization hours of wind power generation after planning Photovoltaic power generation utilization hours Thermal power unit utilization hours Flexibility modification of unit utilization hours The product of each capacity must be greater than the total electricity demand. :

[0045] (3) The hour constraint is satisfied:

[0046]

[0047]

[0048]

[0049] In the formula: , These are the maximum and minimum utilization hours of wind power generation, respectively. , These are the maximum and minimum utilization hours of the photovoltaic power generation source, respectively. , These are the maximum and minimum utilization hours for conventional thermal power units, respectively. , These refer to the maximum and minimum utilization numbers of thermal power units undergoing flexible retrofitting. (4) The specific investment cost constraints are as follows: The investment amount shall not exceed the limit. :

[0050] Demand response range as a percentage of maximum load meets:

[0051] In the formula: The proportion of demand response to maximum load; This represents the maximum achievable proportion of demand response; (5) The proportional constraints of thermal power units are satisfied:

[0052]

[0053]

[0054] In the formula: , , These are the proportions of conventional thermal power units, flexible retrofitted thermal power units, and standby thermal power units in the total installed thermal power capacity. , These are the proportions of the largest conventional thermal power units, flexible-modified thermal power units, and standby thermal power units, respectively. Operational constraints include constraints on power curtailment and load shedding, real-time power supply and demand balance, thermal power unit operation, demand response, energy storage system, and mobile energy storage vehicle, as detailed below: (1) The specific constraints on power curtailment and load shedding are as follows: Constraints on power curtailment and load shedding are met under both normal and extreme weather conditions:

[0055]

[0056]

[0057]

[0058] In the formula: for Actual grid-connected power output of wind power generation at that time; for Actual grid-connected power of photovoltaic power generation; for Wind power curtailment; for Solar power curtailment; for Wind power generation capacity; for Photovoltaic power generation capacity; for Actual electricity demand at the time; for Real-time network load; for Power abandoned per hour; Under severe weather events, the specific phenomena of additional power curtailment and load shedding are as follows:

[0059]

[0060] In the formula: Power wasted and load shedding due to line damage; This refers to the load shedding power; and This refers to power curtailment and load shedding during severe weather events. (2) The real-time balance constraint of power supply and demand is satisfied:

[0061] In the formula: for Actual output of conventional thermal power units; for The actual output of thermal power units can be flexibly modified in a timely manner. for Standby unit output; The variables are 0-1, where 1 indicates that the energy storage system is in... Discharge at any time, 0 indicates that the energy storage system is in a state of constant discharge. Always charging; for Discharge power of the energy storage system; for Time-based energy storage system charging power; , To improve the discharge and charging efficiency of energy storage systems; for Discharge power of mobile energy storage vehicle Improve the efficiency of mobile emergency power supply; Variables are 0-1, where 1 represents When the load is a valley filling type, 0 indicates The load was peak-shaving. for Peak-valley demand response load power; for Peak-shaving demand response load power; (3) The constraints of thermal power units include output constraints, reserve capacity constraints, ramp-up constraints, minimum start-up and shutdown time constraints, and standby unit constraints, as detailed below: Output constraints are satisfied:

[0062]

[0063] In the formula: , These refer to the upward and downward reserve capacities that conventional thermal power units can provide, respectively. , These are the maximum and minimum output limits for conventional thermal power units; It is a 0-1 variable, representing the unit's start-up or shutdown status; The reserve capacity constraint is satisfied:

[0064]

[0065] In the formula: , These refer to the maximum upward and downward reserve capacity that conventional thermal power units can provide, respectively. The climbing constraint is satisfied:

[0066] In the formula: , These represent the maximum hourly upward and downward climbing values ​​for conventional thermal power units; Minimum start-stop time constraints are satisfied:

[0067]

[0068] In the formula: , The continuous start-up and shutdown time of thermal power units; , Minimum start-up and shutdown time for thermal power units; Standby unit constraints are met under normal weather conditions:

[0069] (4) Demand response constraints are satisfied:

[0070] (5) The energy storage system constraints are satisfied:

[0071]

[0072]

[0073]

[0074] In the formula: , These are the minimum and maximum capacities of the energy storage system, respectively. for Stored power at that time; This represents the maximum charging and discharging power of the energy storage system. (6) The constraints of the mobile energy storage vehicle are satisfied: Under both normal weather and extreme weather conditions, the following conditions must be met:

[0075]

[0076] Under severe extreme weather conditions, the following conditions must be met:

[0077]

[0078]

[0079] In the formula: , These are the minimum and maximum capacities of the mobile energy storage vehicle, respectively. for Stored power at that time; Maximum power supply for mobile energy storage vehicles.

[0080] According to a second aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the novel power system multi-flexibility resource planning method under extreme weather conditions as described in any one of the first aspects.

[0081] According to a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the novel power system multi-variable flexibility resource planning method under extreme weather conditions as described in any one of the first aspects.

[0082] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: This invention provides a novel multi-faceted flexibility resource planning method for power systems under extreme weather conditions. It innovatively classifies extreme weather into environmental and disaster-related categories, and proposes differentiated technical solutions based on their different characteristics, such as converting decommissioned thermal power units into standby units and using mobile energy storage vehicles to provide emergency power. Furthermore, it constructs a model encompassing the adjustment capabilities of various flexibility resources, including source, load, and storage, comprehensively considering the synergistic effects of different resources under various weather conditions, and uses five indicators, including the annual imbalance risk coefficient, to evaluate system flexibility. Finally, an optimization model incorporating investment and operating costs is established with the goal of minimizing total cost. Considering both investment and operational constraints, the solution process is simplified through linearization, yielding the multi-faceted flexibility resource planning results for novel power systems under extreme weather conditions. The method proposed in this invention can more effectively improve the flexibility and economy of novel power systems under extreme weather conditions. Attached Figure Description

[0083] Figure 1 This is a framework diagram of a novel multi-dimensional flexibility resource planning method for power systems under extreme weather conditions, provided by an embodiment of the present invention. Figure 2 This invention provides a diagram showing the annual power balance operation results according to an embodiment of the present invention. Figure 3 This is a diagram illustrating the operational results of a scheme under normal weather conditions, as provided in an embodiment of the present invention. Figure 4 This is a diagram illustrating the operational results of Scheme 2 under normal weather conditions, as provided in an embodiment of the present invention. Figure 5 This is a diagram illustrating the operational results of Scheme 3 under normal weather conditions, as provided in an embodiment of the present invention. Figure 6 This is a diagram illustrating the operational results of an environmental extreme weather scheme according to an embodiment of the present invention. Figure 7 This is a diagram illustrating the operational results of a second environmental extreme weather scenario according to an embodiment of the present invention. Figure 8 This is a diagram illustrating the operational results of a third environmental extreme weather scenario according to an embodiment of the present invention. Figure 9 This is a diagram illustrating the operational results of a second disaster-type extreme weather scenario according to an embodiment of the present invention. Figure 10 This is a diagram illustrating the operational results of a third disaster-type extreme weather scenario according to an embodiment of the present invention. Figure 11 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0084] The following detailed description is merely exemplary in nature and is not intended to limit the disclosed technology or its application and use. Furthermore, it is not intended to be bound by any express or implied theory presented in the foregoing technical fields, background art, or the following detailed description.

[0085] In the following detailed description of the embodiments, numerous specific details are set forth in order to provide a more thorough understanding of the disclosed technology. However, it will be apparent to those skilled in the art that the disclosed technology can be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.

[0086] This invention proposes a multi-faceted flexibility resource planning method for novel power systems under extreme weather conditions. It innovatively classifies extreme weather into environmental and disaster-related categories, and proposes differentiated technical solutions based on their different characteristics, such as converting decommissioned thermal power units into standby units and using mobile energy storage vehicles to provide emergency power. Furthermore, it constructs a model encompassing the regulation capacity of various flexibility resources, including source, load, and storage, comprehensively considering the synergistic effects of different resources under various weather conditions, and uses five indicators, including the annual imbalance risk coefficient, to evaluate system flexibility. Finally, an optimization model incorporating investment and operating costs is established with the goal of minimizing total cost. Considering the constraints of investment and operation, the solution process is simplified through linearization, yielding the multi-faceted flexibility resource planning results for novel power systems under extreme weather conditions. The method is validated using an example of annual power and meteorological data from Hubei Province, demonstrating that it can more effectively improve the flexibility and economy of novel power systems under extreme weather conditions.

[0087] Figure 1 This is a framework diagram of a novel multi-variable flexibility resource planning method for power systems under extreme weather conditions, according to one or more embodiments of the present invention. Figure 1 As shown in the figure, the novel power system multi-dimensional flexibility resource planning method under extreme weather conditions according to an embodiment of the present invention specifically includes the following steps: Step S1: Establish a flexible resource model for the new power system under normal weather conditions as a basis.

[0088] Step S2: Based on the model obtained in Step 1, establish a mathematical model of flexibility resources under extreme weather conditions, and propose flexibility assessment indicators to measure the system's flexibility requirements.

[0089] Step S3: Establish a flexible resource planning model for extreme weather conditions with the objective function of minimizing total cost.

[0090] Step S4: Based on the planning model obtained in Step S3, taking Hubei Province's power and meteorological data as an example, construct a set of normal weather and extreme weather scenarios, and conduct a comparative study on the system operation results under whether or not flexible planning is carried out.

[0091] In some embodiments, the establishment of a flexibility resource model for a new power system under normal weather conditions in step S1 is based on the following: Step S11: Establish a power supply-side flexibility resource model, as follows: Conventional thermal power units are one of the main flexible resources, and their output characteristics meet the following requirements:

[0092] In the formula: , These are the minimum and maximum technical outputs of thermal power units, respectively. This represents the output coefficient of the thermal power unit.

[0093] Conventional thermal power units can provide the following upward / downward flexibility adjustment capabilities:

[0094]

[0095] In the formula: , for The up / down adjustment capability that conventional thermal power units can provide; , This refers to the uphill / downhill climbing capability of thermal power units; for Actual output of conventional thermal power units.

[0096] After the flexibility modification, the thermal power unit has a higher flexibility margin, and its output characteristics meet the following requirements:

[0097]

[0098] In the formula: To provide the minimum technical output during the non-oil injection phase after the flexibility upgrade; To achieve the minimum technical output during the oil injection phase after the flexibility upgrade; , These are the output coefficients for the non-oil injection stage and the oil injection stage, respectively.

[0099] The upward / downward flexibility adjustment capability provided by the flexible retrofit thermal power unit meets the following requirements:

[0100]

[0101] In the formula: , for The flexibility to modify thermal power units allows for upward / downward adjustment capabilities; , To improve the flexibility of thermal power units, their ability to climb slopes was modified. for The actual output of thermal power units can be flexibly modified in a timely manner.

[0102] Combining conventional thermal power units with those retrofitted for flexibility, the power supply side flexibility adjustment capability meets the following requirements:

[0103]

[0104] In the formula: , for The power supply side's up and down adjustment capability.

[0105] Step S12: Establish a load-side flexibility resource model, as follows: Load-side flexibility resources primarily refer to demand response. Assuming demand response is maximally correlated with total annual load demand, then the following conditions are met:

[0106] In the formula: To maximize power for demand response; The ratio of demand response capability to maximum electricity load; This is the maximum load.

[0107] Simplify demand response as peak-shaving load Valley-filling load Peak-shaving loads provide upward flexibility for the system, while valley-filling loads provide downward flexibility. Therefore, the load-side flexibility must satisfy the following:

[0108]

[0109] In the formula: , They are respectively The ability to adjust upwards or downwards in response to demand.

[0110] Step S13: Establish energy storage-side flexibility resources, as detailed below: During periods of low electricity demand, the energy storage system acts as a power-consuming device, storing excess electricity from renewable energy sources. During peak demand periods, the energy storage system acts as a power-generating device, releasing the stored electricity to supply power to the system. Therefore, the flexibility and regulation capability of the energy storage side meets the following requirements:

[0111]

[0112] In the formula: , They are respectively The up / down adjustment capability that the energy storage system can provide. This represents the maximum charging and discharging power of the energy storage system. , To improve the discharge and charging efficiency of energy storage systems; for The amount of stored energy at any given time; , These represent the minimum and maximum stored electrical quantities of the energy storage system.

[0113] Step S14: Considering the resources on the power supply side, load side, and energy storage side, the system's flexibility and adjustment capability under normal weather conditions meets the following requirements:

[0114]

[0115] In the formula: , For each system Flexible adjustment capability.

[0116] In some embodiments, step S2 establishes a mathematical model of flexibility resources under extreme weather conditions based on the model obtained in step 1, and proposes flexibility assessment indicators to measure the system's flexibility requirements, as detailed below: Step S21: Based on the comprehensive characteristics of the impact of extreme weather on the power system, it is divided into two categories: environmental and catastrophic. Environmental extreme weather changes environmental factors such as temperature, wind speed, and irradiance, indirectly affecting the operation of the power system; catastrophic extreme weather not only has a significant impact on environmental conditions, but may also cause direct damage to power equipment.

[0117] Step S22: Establish a mathematical model for flexibility resources under extreme weather conditions, as detailed below: The system regulation flexibility provided by converting decommissioned thermal power units into emergency standby units , The calculations are the same as for conventional thermal power units. At this point, the system's flexibility and adjustability under extreme weather conditions meet the following requirements:

[0118]

[0119] Compared to the system's flexibility and adjustability under normal weather conditions, the system's flexibility and adjustability under extreme environmental weather conditions includes the adjustment capability of backup thermal power units.

[0120] Step S23: Establish a mathematical model for flexibility resources under catastrophic extreme weather conditions, as detailed below: For such scenarios, deploying mobile energy storage vehicles enhances the flexibility and resilience of the power system. In this case, the mobile energy storage vehicles provide power and offer upscaling capabilities. Assume the total capacity of the mobile energy storage vehicles is... The maximum discharge power of the mobile energy storage vehicle is In the event of severe extreme weather, it can provide system regulation flexibility to meet the following requirements:

[0121] In the formula: Provides mobile energy storage vehicles with system flexibility and adjustability; for Discharge power of mobile energy storage vehicle; Improve the efficiency of mobile emergency power supply.

[0122] At this point, the system's flexibility and adjustability under severe weather conditions meet the following requirements:

[0123]

[0124] Compared to the system's flexibility and adjustability under normal weather conditions, the system's flexibility and adjustability under extreme weather conditions includes the adjustment capabilities of backup thermal power units and mobile energy storage vehicles.

[0125] Step S24: Based on the characteristics of system flexibility, five indicators are proposed to measure the system flexibility requirements: annual imbalance risk coefficient, upward adjustment of expected power, downward adjustment of expected power, upward adjustment of expected flexible power consumption, and downward adjustment of expected insufficient flexible power consumption.

[0126] The annual imbalance risk coefficient measures the proportion of periods with overall flexibility demand throughout the year, ranging from 0 to 1. A value closer to 0 indicates a lower imbalance risk, while a value closer to 1 indicates a higher imbalance risk. The expected upward power adjustment measures the maximum load shedding value during the year when the increased capacity fails to meet the increased demand. The expected downward power adjustment measures the maximum amount of power curtailed during the year when the decreased capacity fails to meet the decreased demand. The expected upward electricity adjustment measures the cumulative amount of load shedding during the year when the increased capacity fails to meet the increased demand. The expected downward electricity adjustment measures the cumulative amount of power curtailed during the year when the decreased capacity fails to meet the decreased demand. Details are as follows:

[0127]

[0128]

[0129]

[0130]

[0131] In the formula: The annual imbalance risk coefficient; , These are the cumulative hours of power curtailment and load shedding, respectively. The total number of hours throughout the year; , These represent the expected power values ​​for insufficient flexibility when adjusting upwards or downwards, respectively. , for Adjust the required power up / down as needed; , The flexibility to adjust the power consumption expectation value upwards / downwards is insufficient.

[0132] In some embodiments, step S3, with the objective function of minimizing total cost, establishes a flexible resource planning model under extreme weather conditions as follows: Step S31: The objective function of the flexibility resource planning model is to minimize the sum of investment cost and operating cost, specifically satisfying:

[0133] In the formula: For investment costs; Operating costs.

[0134] Step S32: Investment Costs: Including the costs of adapting thermal power units to flexibility requirements. Demand response investment costs Energy storage system investment costs Cost of extending the life of standby thermal power units Mobile energy storage investment costs The details are as follows:

[0135] Let the capital recovery coefficient be ,have:

[0136] In the formula: The discount rate; For the planning cycle.

[0137] The costs of each investment are as follows: (1) Cost of flexible retrofitting of thermal power units. Assuming that the thermal power units under study had not undergone flexible retrofitting before the planning, the annual value of the cost of flexible retrofitting of thermal power units is satisfied.

[0138] In the formula: Unit cost for flexibility retrofitting of thermal power units; Capacity for flexible modification of thermal power units.

[0139] (2) Demand response investment cost, the annual value of demand response investment cost, etc., meets:

[0140] In the formula: Compensation for costs per unit of demand response; This refers to the proportion of demand response to the maximum load.

[0141] (3) Energy storage system investment cost, the annual value of energy storage system investment cost, etc., meets the following requirements:

[0142] In the formula: , These represent the unit investment cost for the energy storage system's power and capacity, respectively. Fixed operation and maintenance costs per unit of energy storage system.

[0143] (4) The life extension cost of standby thermal power units meets the following requirements:

[0144] In the formula: The cost per unit capacity of refurbished retired thermal power units to extend their service life; This is for the capacity of decommissioned thermal power units.

[0145] (5) Investment cost of mobile energy storage vehicle, the annual value of investment cost of mobile energy storage vehicle, etc., meets the following requirements:

[0146] In the formula: Unit investment cost for mobile energy storage vehicles.

[0147] Step S33: Operating Costs: System operating costs under normal weather conditions Including the cost of power curtailment penalties Load shedding penalty cost Operating costs of thermal power units Demand response subsidy costs Variable operation and maintenance costs of energy storage systems The details are as follows:

[0148] System operating costs under extreme weather conditions It will also include the operating costs of standby thermal power units. The details are as follows:

[0149] System operating costs under severe extreme weather events It will also include the cost of mobile power supply from mobile energy storage vehicles. The details are as follows:

[0150] The specific operating costs are as follows: (1) The cost of power curtailment penalty is satisfied:

[0151] In the formula: Cost per unit of abandoned electricity; for Power abandoned at any time.

[0152] (2) The load shedding penalty cost is satisfied:

[0153] In the formula: Penalty cost per load shedding unit; This refers to the load shedding power.

[0154] (3) Operating costs of thermal power units, including the operating costs of conventional thermal power units that have not undergone modification. Flexibility modification of thermal power unit operating costs Carbon emission costs of thermal power units ,satisfy:

[0155] Among them, the operating cost of traditional thermal power units mainly consists of coal consumption costs. and start-up / shutdown costs The basic operating costs consist of the following components, satisfying:

[0156]

[0157]

[0158] In the formula: , , For the consumption of secondary, primary, and constant coefficients; , These are the costs of starting up and stopping the generator unit, respectively. For the first Output of conventional thermal power units; For the first Timing group start / stop state variables For the first Timing group start / stop state variables.

[0159] The operating costs of flexible retrofit units mainly consist of basic operating costs. Unit life loss cost Combustion fuel cost Composition. The operating cost is segmented according to different operating states as follows:

[0160]

[0161]

[0162] In the formula: This is the unit operating loss coefficient; For the cost of purchasing the equipment; This represents the number of rotor-induced cracking cycles. Price per unit of oil; for Timing fuel consumption.

[0163] The carbon emission cost of thermal power units meets the following requirements:

[0164] In the formula: Carbon emissions per unit of electricity generated by a thermal power unit; The cost of carbon trading per unit of carbon emissions.

[0165] (4) Demand response compensation cost, the demand response compensation cost satisfies:

[0166] In the formula: A unified subsidy unit price is set for the system's demand-side response; Variables are 0-1, where 1 represents When the load is a valley filling type, 0 indicates The load was peak-shaving. for Peak-valley demand response load power; for Peak-shaving demand response load power.

[0167] (5) Variable operation and maintenance cost of energy storage system. The variable operation and maintenance cost of energy storage system includes discharge cost and charging cost. Only one state can exist at any given time. Therefore, the variable operation and maintenance cost of energy storage system satisfies:

[0168] In the formula: The unit variable operation and maintenance cost of energy storage systems; The variables are 0-1, where 1 indicates that the energy storage system is in... Discharge at any time, 0 indicates that the energy storage system is in a state of constant discharge. Always charging; for Discharge power of the energy storage system; for Charging power of the energy storage system.

[0169] (6) Operating cost of standby units. The formula for calculating the operating cost of standby thermal power units is the same as that for conventional thermal power units.

[0170] (7) The operating cost of the mobile energy storage vehicle meets the following requirements:

[0171] In the formula: Unit operating cost of mobile energy storage vehicles; The variables are 0-1, where 1 indicates that the mobile energy storage vehicle is in Discharging at any time, 0 indicates that the mobile energy storage vehicle is in operation. Not running at any time; for Power supply of mobile energy storage vehicle; Labor costs for providing mobile power; This refers to diesel fuel consumption.

[0172] Step S34: The specific constraints are as follows.

[0173] (1) The constraints of the investment decision model include power constraints, electricity constraints, equipment utilization hours constraints, investment cost constraints, etc.

[0174] 1) Power constraints, planned wind turbine installed capacity Photovoltaic generator unit capacity Conventional thermal power unit capacity (Excluding standby capacity), capacity for flexible retrofitting of generating units The sum must be greater than the maximum load power. :

[0175] 2) Power constraints, planned wind power generation utilization hours Photovoltaic power generation utilization hours Thermal power unit utilization hours Flexibility modification of unit utilization hours The product of each capacity must be greater than the total electricity demand. :

[0176] 3) The hour constraint is satisfied as follows:

[0177]

[0178]

[0179]

[0180] In the formula: , These are the maximum and minimum utilization hours of wind power generation, respectively. , These are the maximum and minimum utilization hours of the photovoltaic power generation source, respectively. , These are the maximum and minimum utilization hours for conventional thermal power units, respectively. , These represent the maximum and minimum utilization numbers of thermal power units undergoing flexible retrofitting, respectively.

[0181] 4) The specific investment limit constraints are as follows: The investment amount shall not exceed the limit. satisfy:

[0182] Demand response range as a percentage of maximum load meets:

[0183] In the formula: This represents the maximum achievable proportion of the demand response.

[0184] 5) The proportional constraints of thermal power units are satisfied:

[0185]

[0186]

[0187] In the formula: , , These are the proportions of conventional thermal power units, flexible retrofitted thermal power units, and standby thermal power units in the total installed thermal power capacity. , These represent the proportions of the largest conventional thermal power units, the flexible retrofitted thermal power units, and the standby thermal power units.

[0188] (2) Operational constraints The constraints of the lower-level dispatching and operation model include constraints on power curtailment and load shedding, real-time power supply and demand balance, thermal power unit constraints, demand response constraints, energy storage system constraints, and mobile energy storage vehicle constraints.

[0189] 1) The specific constraints on power curtailment and load shedding are as follows: Constraints on power curtailment and load shedding are met under both normal and extreme weather conditions:

[0190]

[0191]

[0192]

[0193] In the formula: for Actual grid-connected power output of wind power generation at that time; for Actual grid-connected power of photovoltaic power generation; for Wind power curtailment; for Solar power curtailment; for Wind power generation capacity; for Photovoltaic power generation capacity; for Actual electricity demand at the time; for The actual network load at that time.

[0194] Under severe weather events, additional power curtailment and load shedding may occur due to factors such as line damage, as detailed below:

[0195]

[0196] In the formula: This refers to power wastage and load shedding caused by line damage.

[0197] 2) The real-time balance constraint of power supply and demand is satisfied:

[0198] In the formula: for Standby unit output; for Actual discharge power of energy storage at any time; Actual charging power of energy storage.

[0199] 3) Constraints on thermal power units include output constraints, reserve capacity constraints, ramp-up constraints, minimum start-up and shutdown time constraints, and standby unit constraints, as detailed below: Output constraints are satisfied:

[0200]

[0201] In the formula: , These refer to the upward and downward reserve capacities that conventional thermal power units can provide, respectively. , These are the maximum and minimum output limits for conventional thermal power units; It is a 0-1 variable, representing the unit's start-up or shutdown status.

[0202] The reserve capacity constraint is satisfied:

[0203]

[0204] In the formula: , These refer to the maximum upward and downward reserve capacity that conventional thermal power units can provide, respectively.

[0205] The climbing constraint is satisfied:

[0206] In the formula: , These represent the maximum upward and downward ramp speeds per hour for conventional thermal power units.

[0207] Minimum start-stop time constraints are satisfied:

[0208]

[0209] In the formula: , The continuous start-up and shutdown time of thermal power units; , This refers to the minimum start-up and shutdown time for thermal power units.

[0210] Under normal weather conditions, the standby unit constraints are met:

[0211] 4) Demand response constraints are satisfied:

[0212] 5) Energy storage system constraints are satisfied:

[0213]

[0214]

[0215]

[0216] In the formula: , These are the minimum and maximum capacities of the energy storage system, respectively. for Stored power at that time; This represents the maximum charging and discharging power of the energy storage system.

[0217] 6) The constraints of the mobile energy storage vehicle are satisfied: Under both normal weather and extreme weather conditions, the following conditions must be met:

[0218]

[0219] Under severe extreme weather conditions, the following conditions must be met:

[0220]

[0221]

[0222] In the formula: , These are the minimum and maximum capacities of the mobile energy storage vehicle, respectively. for Stored power at that time; Maximum power supply for mobile energy storage vehicles.

[0223] Step S35: The flexibility resource requirement model is a mixed integer nonlinear model, involving nonlinear parts such as 0-1 variables, quadratic functions, and piecewise functions.

[0224] (1) 0-1 variables: The problem is transformed into a nonlinear problem using the Big M method.

[0225] (2) Quadratic function: Piecewise linearization is used to divide the nonlinear function into multiple segments for linear approximation.

[0226] (3) Piecewise function: Introduce index variables to solve.

[0227] Using the above method, the nonlinear terms in the model can be transformed into linear terms, and the model can be built and solved by calling the Gurobi commercial solver.

[0228] In some embodiments, the planning model obtained in step S3, as described in step S4, uses Hubei Province's power and meteorological data as an example to construct sets of routine and extreme weather scenarios, and compares the system operation results with and without flexible planning, as follows: Step S41: Select the 2022 power and meteorological data of Hubei Province to verify the planning model. By replacing the centralized scenario of the dataset, construct a dataset with different extreme weather proportions for the flexible resource allocation case study, as shown in Table 1. The unit output parameter settings required for the case study are shown in Table 2.

[0229] Table 1 Scene Setting Table

[0230] Table 2 Parameter Setting Table

[0231] The following planning scheme is set: Option 1: Includes only conventional thermal power units, without considering flexibility resources (i.e., thermal power units do not participate in flexibility retrofits, all thermal power units that have reached the end of their service life are decommissioned, and demand response, energy storage systems and mobile energy storage vehicles are not considered), and conducts basic planning scheme. Option 2: Based on Option 1, consider flexible resource planning under normal weather conditions, and add planning for flexible retrofitting of thermal power units, demand response, and energy storage systems; Option 3: Based on Option 2, consider flexible resource planning under extreme weather conditions, and add planning for the transformation of thermal power units that have reached the end of their service life into standby units and mobile energy storage vehicles.

[0232] Step S42: Analyze the planning results of the example.

[0233] Depend on Figure 2It is evident that power curtailment occurs throughout the year, but is particularly pronounced in spring and autumn. Furthermore, conventional thermal power units do not maintain high-load operation for extended periods. This indicates that the system does not suffer from insufficient installed capacity, but rather lacks sufficient flexibility to cope with uncertainties. In contrast, load shedding is concentrated in summer and winter, with summer power shortages being more severe. This phenomenon suggests that during the peak electricity demand period in summer, existing power output is insufficient to meet the demand, necessitating the introduction of additional power supply solutions.

[0234] Depend on Figure 3 It can be seen that during the daytime (6:00-16:00), thermal power units operate at relatively low output levels, the system has ample flexibility resources, and the output of thermal power units fluctuates significantly, indicating that the system's flexibility adjustment capability is mainly provided by thermal power units during this period. However, during peak electricity consumption periods (18:00-23:00), photovoltaic power generation capacity decreases significantly, and wind power generation exhibits strong randomness, leading to insufficient system flexibility adjustment capability. Operational data from three consecutive days shows that load shedding occurred during this period, indicating a significant gap in the system's flexibility adjustment capability under high load demand scenarios. In contrast, Figure 4 The demonstration showcases the system's operational performance after implementing Scheme 2. By introducing demand response and energy storage systems for regulation, the system's flexibility has been significantly improved, and load shedding has been markedly reduced compared to before the plan was implemented. Although some load shedding still occurs, its magnitude and duration have been mitigated. Figure 5 The results of Scheme 3's system operation under normal weather conditions are presented. In this case, all scenario identification results are for normal scenarios, and the backup unit and mobile energy storage vehicle are not activated. Therefore, the operational results of Scheme 3 are consistent with... Figure 4 Basically the same.

[0235] Figure 6 Load shedding increased at 0:00, 2:00, and 4:00 on the first day; 2:00 and 17:00 on the second day; and 15:00 on the third day. Simultaneously, the peak load shedding also increased significantly, rising from approximately 10,000 MW under normal weather conditions to approximately 17,000 MW under extreme weather conditions. This change indicates that the system's operating pressure significantly increases under extreme weather conditions. Due to intensified load fluctuations, the newly added load shedding not only expanded in time and frequency but also significantly increased in intensity, making it difficult for the system to maintain supply-demand balance during specific periods. This reflects the system's insufficient flexibility in adjusting under extreme weather conditions. It is noteworthy that although high summer temperatures significantly increase load demand, power curtailment is relatively rare under these types of extreme weather conditions. This suggests that under extreme weather conditions, the primary challenge for the power system is not overcapacity, but rather a severe power shortage, necessitating improved system flexibility to cope with increased demand during peak hours. Figure 7The results of Scheme 2 were presented. By introducing flexible resources, the load shedding phenomenon was significantly alleviated. For example, during the periods of 0:00, 2:00, and 4:00 on the first day, the previously existing low-amplitude load shedding completely disappeared, and the overall load shedding amplitude was significantly reduced to approximately 15MW. This result demonstrates that the effective introduction of flexible resources in Scheme 2 played a crucial role in improving system operational stability. By optimizing resource allocation and enhancing system responsiveness, the load shedding phenomenon was effectively suppressed, and the system's reliability and resilience were significantly improved. Although a small amount of load shedding still exists, its scale has been greatly reduced, reflecting a significant improvement in the system's adaptability to extreme weather conditions. Figure 8 As shown, the system's operation was significantly improved by further increasing the number of standby generating units when dealing with extreme weather conditions. Load shedding phenomena at 23:00 on the first day, 4:00, 6:00, and 16:00 on the second day, and 0:00, 16:00, and 20:00 on the third day all disappeared, and the maximum amplitude of remaining load shedding phenomena was reduced to within approximately 10,000 MW. This result demonstrates that increasing standby generating units can effectively enhance the system's operational flexibility under extreme weather conditions. By supplementing additional capacity resources, the system has a stronger ability to cope with load fluctuations and power supply uncertainties. The disappearance or significant reduction of load shedding phenomena reflects that the effective deployment of standby generating units reduces the risk of supply-demand imbalance and improves the overall reliability of power supply.

[0236] In addition, such as Figure 9 As shown, during severe weather events, the system not only faces challenges in supplying load but also experiences additional load shedding and power curtailment due to equipment failures. This indicates that under severe weather conditions, the system's operational pressure increases significantly, leading to some power being unable to be effectively transmitted or meet demand. Figure 10 The results demonstrate the system's operation after the introduction of the mobile energy storage vehicle. The vehicle only activates during severe weather events. While the problem of power curtailment was not alleviated, the load shedding phenomenon was effectively mitigated. This result indicates that the system can effectively supplement power supply and reduce load gaps caused by equipment failures or line damage during severe weather events.

[0237] Figure 11 This is a schematic block diagram of an electronic device according to one or more embodiments of the present invention. The electronic device 200 includes a memory 210, a processor 220, and a computer program 230 stored in the memory 210 and executable on the processor 220. The execution of the computer program 230 causes a novel power system multi-flexibility resource planning method under extreme weather conditions, as described in the method embodiments above, to be implemented. Exemplarily, the electronic device 200 may be a controller or a computer.

[0238] Alternatively, the present invention can also be implemented as a computer-readable storage medium storing a program for causing a computer to execute the novel power system multi-functional flexibility resource planning method under extreme weather conditions described in the above-described method embodiments. Here, various types of computer-readable storage media can be used, such as disks (e.g., magnetic disks, optical disks, etc.), cards (e.g., memory cards, optical cards, etc.), semiconductor memories (e.g., ROM, non-volatile memory, etc.), and tapes (e.g., magnetic tape, cassette tape, etc.).

[0239] The embodiments and examples presented herein are provided to best illustrate embodiments of the invention and its particular applications, thereby enabling those skilled in the art to practice and use the invention. However, those skilled in the art will understand that the above description and examples are provided merely for ease of illustration and example. The descriptions presented are not intended to cover all aspects of the invention or to limit the invention to the precise forms disclosed.

Claims

1. A method for planning multi-element flexible resources of a new power system under extreme weather, characterized in that, The method comprises: S1, establishing a flexibility resource model of a new power system under normal weather, including a power supply side, a load side and an energy storage side flexibility resource model; S2, based on the flexibility resource model of the new power system under normal weather, establishing a flexibility resource mathematical model of the new power system under extreme weather; the extreme weather is divided into environmental type and disaster type, the environmental type extreme weather adds standby thermal power units, and the disaster type extreme weather further adds mobile energy storage vehicles; S3, taking total cost minimization as an objective function, establishing a flexibility resource planning model under extreme weather, the total cost including investment cost and operation cost, and setting investment constraint conditions and operation constraint conditions; S4, linearly processing and solving the flexibility resource planning model under extreme weather, to obtain a multi-element flexibility resource planning result of the new power system under extreme weather.

2. The method of claim 1, wherein, Step S1 comprises: S11, establishing a power supply side flexibility resource model, including: determining output characteristics and upward and downward flexibility adjustment capabilities of conventional thermal power units and flexibility transformation thermal power units, and comprehensively obtaining power supply side flexibility adjustment capabilities from the conventional thermal power units and the flexibility transformation thermal power units; Step S11 specifically comprises: The output characteristics of the conventional thermal power units satisfy: In the formula: , are the minimum and maximum technical output of the conventional thermal power unit, respectively; is the output coefficient of the conventional thermal power unit. The upward and downward flexibility adjustment capabilities of the conventional thermal power units satisfy: In the formula: , is the up and down regulation ability of a conventional thermal power unit; , is the up and down ramping ability of a conventional thermal power unit; is the actual output of a conventional thermal power unit; The output characteristics of the conventional thermal power units after flexibility transformation satisfy: In the formula: is the minimum technical output after the flexibility reconstruction in the non-oil injection stage; is the minimum technical output after the flexibility reconstruction in the oil injection stage; , are the output coefficients in the non-oil injection stage and the oil injection stage, respectively. The upward and downward flexibility adjustment capabilities of the flexibility transformation thermal power units satisfy: In the formula: , is the up and down regulation ability of the flexible reform thermal power generating unit when , is the up and down ramping ability of the flexible reform thermal power generating unit; is the actual output of the flexible reform thermal power generating unit when Comprehensively, the power supply side flexibility adjustment capabilities satisfy: In the formula: , is the up and down regulation capability of the power supply side; S12, establishing a load side flexibility resource model, including: determining a demand response maximum limit power, simplifying the demand response into peak-cut type load and valley-fill type load, the peak-cut type load providing upward flexibility adjustment capabilities for the system, and the valley-fill type load providing downward flexibility adjustment capabilities for the system; Step S12 specifically comprises: The load side flexibility resource refers to demand response; assuming that the demand response maximum limit is related to total annual load demand, then: In the formula: is the maximum power for demand response; is the proportion of demand response capability in the maximum power load; is the maximum load; Simplifying demand response to peak shaving type load and valley filling type load ; wherein the peak shaving type load provides the system with an upward flexibility adjustment capability and the valley filling type load provides the system with a downward flexibility adjustment capability; The load side flexibility adjustment capabilities satisfy: In the formula: , are respectively upper and lower regulation ability of the load side; S13, establishing an energy storage side flexibility resource, including: setting an energy storage system, in a low electricity consumption valley, the energy storage system acts as an electricity consumption equipment, stores excess power of renewable energy, and in a high electricity consumption peak, the energy storage system acts as a power generation equipment to release the stored power to supply power for the system; Step S13 specifically comprises: Setting an energy storage system, in a low electricity consumption valley, the energy storage system acts as an electricity consumption equipment, stores excess power of renewable energy, and in a high electricity consumption peak, the energy storage system acts as a power generation equipment to release the stored power to supply power for the system, then the energy storage side flexibility adjustment capabilities satisfy: In the formula: , are the upper and lower regulation capabilities of the energy storage side when , is the maximum charge and discharge power of the energy storage system; , are the discharge and charge efficiencies of the energy storage system; is the storage power at the moment is the storage power at the moment , are the minimum and maximum storage powers of the energy storage system; S14, comprehensively determining system flexibility adjustment capabilities under normal weather from the power supply side, the load side and the energy storage side resources; Step S14 specifically comprises: Comprehensively, the system flexibility adjustment capabilities under normal weather satisfy: In the formulae: , are systems flexibility adjustment capabilities.

3. The method of claim 1, wherein, Step S2 comprises: S21, comprehensively considering influence characteristics of extreme weather on the new power system, and dividing the extreme weather into environmental type and disaster type; S22, for environmental extreme weather, add standby thermal power units, establish environmental extreme weather under the flexibility of resource mathematical model; step S22 is as follows: Environmental extreme weather joins standby thermal power unit, and determine standby thermal power unit's up and down flexibility adjustment ability and ; Then the system flexibility under environmental extreme weather can be adjusted to meet: S23, for disaster type extreme weather, add standby thermal power units and mobile energy storage vehicles, establish disaster type extreme weather under the flexibility of resource mathematical model; step S23 is as follows: Disaster type extreme weather joins standby thermal power unit and mobile energy storage vehicle, mobile energy storage vehicle provides upward adjustment capacity; assuming that the total capacity of mobile energy storage vehicle is , the maximum discharge power of mobile energy storage vehicle is , then the system adjustment flexibility provided by mobile energy storage vehicle under disaster type extreme weather meets: In the formula: The system flexibility provided for the mobile energy storage vehicle can adjust the capacity; For When the mobile energy storage vehicle discharges power; The mobile emergency power supply efficiency; The final disaster type extreme weather system flexibility can be adjusted to meet: In the formula: and is the adjustable flexibility of the system under environmental and disaster type extreme weather; , is the up and down adjustment capability of the power supply side; , respectively the up and down adjustment capability of the load side; , respectively the up and down adjustment capability of the energy storage side.

4. The method of claim 3, wherein, Step S2 also includes: S24, set up evaluation index for measuring system flexibility demand, including annual imbalance risk coefficient, up-regulation flexibility insufficient power expectation value, down-regulation flexibility insufficient power expectation value, up-regulation flexibility insufficient power expectation value, down-regulation flexibility insufficient power expectation value; Among them, the annual imbalance risk coefficient measures the proportion of overall flexibility demand period in the whole year operation, the value range is 0-1, the closer to 0 represents the smaller imbalance risk, the closer to 1 represents the greater imbalance risk; The up-regulation flexibility insufficient power expectation value measures the maximum power value of cut load due to the insufficient up-regulation capacity to meet the up-regulation demand in the whole year operation; The down-regulation flexibility insufficient power expectation value measures the maximum power value of cut load due to the insufficient down-regulation capacity to meet the down-regulation demand in the whole year operation; The up-regulation flexibility insufficient power expectation value measures the cumulative value of cut load due to the insufficient up-regulation capacity to meet the up-regulation demand in the whole year operation; The down-regulation flexibility insufficient power expectation value measures the cumulative value of cut load due to the insufficient down-regulation capacity to meet the down-regulation demand in the whole year operation; As follows: In the formula: is the annual unbalanced risk coefficient; , are the cumulative hours of abandoned electricity and load shedding, respectively; is the annual hour; , are the expected values of insufficient up-regulation and down-regulation flexibility, respectively; , is is the required power for up-regulation and down-regulation; , are the expected values of insufficient up-regulation and down-regulation power.

5. The method of claim 1, wherein, Step S3 includes: S31, the sum of investment cost and operation cost is minimum as the extreme weather under the flexibility of resource planning model objective function: In the formulae: is the investment cost; is the operating cost; S32, investment cost includes the cost of flexibility improvement of thermal power units , investment cost of demand response , investment cost of energy storage system , cost of life extension of standby thermal power units and investment cost of mobile energy storage , as follows: S33, system operation cost under normal weather including abandoned electricity penalty cost , load shedding penalty cost , thermal power unit operation cost , demand response compensation cost and variable operation and maintenance cost of energy storage system , as follows: System operating cost under environmental extreme weather Also included is the operating cost of backup thermal power units Specifically as follows: System operating cost under disaster type extreme weather Also included is mobile energy storage vehicle mobile power supply cost Specifically as follows: And set investment constraint condition and operation constraint condition.

6. The method of claim 5, wherein, The investment cost is as follows: Let the capital recovery factor be , where: In the formula: is the discount rate; is the planning period; (1) the equivalent annual value of thermal power unit flexibility transformation cost meets: In the formula: is the unit cost of flexibility retrofit for thermal power units; is the capacity of flexibility retrofit for thermal power units; is the output coefficient of conventional thermal power units; is the output coefficient in the oil injection stage; (2) the equivalent annual value of demand response investment cost meets: In the formula: Cost of demand response unit compensation; Maximum load proportion of demand response; Maximum load; (3) the equivalent annual value of energy storage system investment cost meets: In the formula: , are the power and capacity unit investment cost of the energy storage system, respectively; is the unit fixed operation and maintenance cost of the energy storage system; is the maximum charge and discharge power of the energy storage system; is the maximum storage capacity of the energy storage system; (4) the cost of standby thermal power unit life extension meets: In the formula: is the life extension cost per unit capacity of the overhauled retired thermal power unit; is the capacity of the retired thermal power unit. (5) the equivalent annual value of mobile energy storage vehicle investment cost meets: In the formula: is the unit investment cost of the mobile energy storage vehicle; is the maximum discharge power of the mobile energy storage vehicle; The operation cost is as follows: (1) the penalty cost of cut load meets: In the formulae: is the unit cost of curtailed power; is is the curtailed power. (2) the penalty cost of cut load meets: In the formula: is the unit penalty cost for cutting load; is the cutting load power; (3) the operation cost of the thermal power generating unit, including the operation cost of the conventional thermal power generating unit without modification , the operation cost of the flexible modification thermal power generating unit , the carbon emission cost of the thermal power generating unit , meet: (4) the compensation cost of demand response meets: In the formula: is the system demand side response uniform subsidy unit price; is a 0-1 variable, 1 represents is a valley filling load, 0 represents is a peak clipping load; is is a valley filling demand response load power when is is a peak clipping demand response load power when (5) the variable operation and maintenance cost of energy storage system includes discharge cost and charge cost, and only one state exists at the same time, so the variable operation and maintenance cost of energy storage system meets: In the formula: is the unit variable operation and maintenance cost of the energy storage system; is a 0-1 variable, 1 indicating that the energy storage system discharges at , and 0 indicating that the energy storage system charges at ; is the discharging power of the energy storage system at ; is the charging power of the energy storage system at ; (6) the operation cost of standby unit meets the calculation formula of conventional thermal power unit operation cost; (7) the operation cost of mobile energy storage vehicle meets: In the formula: is the unit operating cost of the mobile energy storage vehicle; is a 0-1 variable, 1 indicating that the mobile energy storage vehicle discharges at , and 0 indicating that the mobile energy storage vehicle does not operate at ; is the power supplied by the mobile energy storage vehicle at ; is the labor cost when the mobile energy storage vehicle supplies power; is the diesel fuel consumption.

7. The method of claim 6, wherein, In the operation cost of the thermal power unit, the operation cost of the conventional thermal power unit includes coal consumption cost and start-stop cost , satisfying: In the formula: , , is the quadratic, linear and constant coefficients of the consumption; , are the start-up and stop costs of the unit, respectively; is the output of the conventional thermal power unit at the time; is the unit start-stop state variable at the time, is the unit start-stop state variable at the time; Flexibility retrofit unit operating cost includes base operating cost , unit life consumption cost , combustion oil cost , the operating cost is segmented according to different operating states as follows: In the formula: is the unit operation loss coefficient; is the purchase cost of the unit; is the number of rotor cracking cycles; is the unit oil price; is is the oil consumption of the unit; , are the minimum and maximum technical output of the conventional thermal power unit, respectively; is the minimum technical output after the flexibility reconstruction and in the non-oil injection stage; is the minimum technical output after the flexibility reconstruction and in the oil injection stage; The carbon emission cost of thermal power unit meets: In the formula: is the carbon emission per unit of power generation of the thermal power generating unit; is the carbon trading cost per unit of carbon emission.

8. The method of claim 5, wherein, The investment constraint condition includes power constraint, power constraint, equipment utilization hour constraint, investment cost constraint, thermal power unit proportion constraint, as follows: (1) Power constraint: sum of planned wind turbine generator installed capacity , photovoltaic generator installed capacity , conventional thermal power generator installed capacity , flexible retrofit generator installed capacity must be greater than maximum load power : (2) Power constraint: the utilization hours of wind power after planning , the utilization hours of photovoltaic power , the utilization hours of thermal power units , the utilization hours of flexible units and the product of each capacity is greater than the total power demand : (3) the utilization hour constraint meets: In the formula: , are the maximum and minimum utilization hours of the wind power generation source, respectively; , are the maximum and minimum utilization hours of the photovoltaic power generation source, respectively; , are the maximum and minimum utilization hours of the conventional thermal power unit, respectively; , are the maximum and minimum utilization hours of the flexible thermal power unit, respectively; (4) the investment cost constraint is as follows: The investment amount shall not exceed the limit : The demand response range accounts for the maximum load percentage, which meets: In the formula: is the maximum load proportion for demand response; is the maximum proportion achievable for demand response; (5) the thermal power unit proportion constraint meets: In the formula: , , respectively are the proportion of conventional thermal power generating units, flexible retrofit thermal power generating units and standby thermal power generating units in the installed capacity of thermal power; , respectively are the maximum proportion of conventional thermal power, flexible retrofit thermal power and standby thermal power generating units. The operation constraint condition includes cut load and cut load constraint, real-time balance constraint of power supply and demand, thermal power unit operation constraint, demand response constraint, energy storage system constraint, mobile energy storage vehicle constraint, as follows: (1) The specific constraints of power curtailment and load shedding are as follows: The constraints of power curtailment and load shedding under normal weather and environmental extreme weather are satisfied: In the formula: is the actual on-grid power of wind power generation when is the actual on-grid power of wind power generation when is the actual on-grid power of photovoltaic power generation when is the actual on-grid power of photovoltaic power generation when is the wind power curtailment power when is the wind power curtailment power when is the photovoltaic power curtailment power when is the photovoltaic power curtailment power when is the wind power generation power when is the wind power generation power when is the photovoltaic power generation power when is the photovoltaic power generation power when is the actual power demand when is the actual power demand when is the actual on-grid load when is the actual on-grid load when is the curtailment power when is the curtailment power when Under disaster type extreme weather, additional power curtailment and load shedding occurs, and the specific constraints are as follows: In the formula: is the power of the line damage resulting in power curtailment and load shedding; is the power of the load shedding; and is the power of the power curtailment and load shedding under disaster-type extreme weather. (2) The real-time balance constraint of power supply and demand is satisfied: In the formula: for Actual output of conventional thermal power units; for The actual output of thermal power units can be flexibly modified in a timely manner. for Standby unit output; The variables are 0-1, where 1 indicates that the energy storage system is in... Discharge at any time, 0 indicates that the energy storage system is in a state of constant discharge. Always charging; for Discharge power of the energy storage system; for Time-based energy storage system charging power; , To improve the discharge and charging efficiency of energy storage systems; for Discharge power of mobile energy storage vehicle Improve the efficiency of mobile emergency power supply; Variables are 0-1, where 1 represents When the load is a valley filling type, 0 indicates The load was peak-shaving. for Peak-valley demand response load power; for Peak-shaving demand response load power; (3) The constraints of thermal power units include output constraint, reserve capacity constraint, ramping constraint, minimum start-stop time constraint, and standby unit constraint, and the specific constraints are as follows: The output constraint is satisfied: In the formula: , are the up and down reserve capacity that can be provided by the conventional thermal power unit, respectively; , are the maximum and minimum output limits of the conventional thermal power unit, respectively; is a 0-1 variable representing the on or off state of the unit. The reserve capacity constraint is satisfied: In the formula: , are the maximum upward and downward reserve capacities that can be provided by a conventional thermal power unit, respectively; The ramping constraint is satisfied: In the formula: , are the maximum hourly upward and downward ramping values, respectively, for a conventional thermal power unit. The minimum start-stop time constraint is satisfied: In the formula: , is the continuous operation and shutdown time of the thermal power unit; , is the minimum operation and shutdown time of the thermal power unit; The standby unit constraint under normal weather is satisfied: (4) The demand response constraint is satisfied: (5) The constraint of energy storage system is satisfied: In the formula: , are the minimum and maximum capacity of the energy storage system, respectively; is the storage power at the time of; is the maximum charge and discharge power of the energy storage system.​ (6) The constraint of mobile energy storage vehicle is satisfied: Under normal weather and environmental extreme weather, the constraints are satisfied: Under disaster type extreme weather, the constraints are satisfied: In the formula: , are the minimum and maximum capacity of the mobile energy storage vehicle, respectively; is the storage power when ; is the maximum power supply of the mobile energy storage vehicle.

9. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the extreme weather new type power system multi-element flexible resource planning method in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the extreme weather new type power system multi-element flexible resource planning method in any one of claims 1 to 8.

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