A method and system for configuring the flexibility of pumped storage capacity under extreme conditions

Abstract

The application relates to a method and system for configuring the capacity of pumped storage under extreme working conditions, and belongs to the technical field of power system resilience evaluation and extreme weather risk defense planning. The method comprises the following steps: based on annual load demand data of a power grid system, wind power / photovoltaic predicted output data and set constraint conditions, determining a pumped storage basic capacity, an annualized comprehensive cost and a scheduling scheme with the lowest annualized comprehensive cost as the target; determining annual high-risk low-probability extreme working condition scenarios; determining pumped storage capacity increments corresponding to each extreme working condition scenario with the minimum capacity increment required for realizing zero load loss under each extreme working condition scenario as the target; and determining the final pumped storage resilience survival boundary capacity of the power grid system based on each capacity increment and the basic capacity. The method of the application scientifically quantifies the pumped storage resilience survival boundary capacity for high-impact low-probability extreme working condition scenarios by stripping the high-risk low-probability extreme working condition scenarios.

Description

Technical Field

[0001] This invention relates to the field of power system resilience assessment and extreme weather risk defense planning, and in particular to a method and system for configuring pumped storage capacity resilience under extreme operating conditions. Background Technology

[0002] Against the backdrop of the "dual carbon" goals and the strategic context of building a new power system, the installed capacity of new energy sources such as wind power and photovoltaics is growing rapidly. Offshore wind power bases, centralized photovoltaics, distributed photovoltaics, and nuclear power baseload clusters are jointly reshaping the operation of traditional power systems. Unlike traditional power systems dominated by thermal power, the supply side of high-proportion new energy power systems exhibits significant randomness, intermittency, and weather-related characteristics. At the same time, baseload power sources such as nuclear power are constrained by safe operation and have limited downward adjustment capabilities. When large-scale wind and solar power output is superimposed with rigid nuclear power baseload, the system net load curve no longer exhibits simple peak-valley fluctuations, but gradually evolves from the traditional "duck curve" into a "canyon curve" characterized by extremely deep valleys, strong uphill climbs, and long-term energy mismatch.

[0003] Pumped storage, as a mature, large-scale, and long-term energy storage technology, can absorb electricity during periods of high renewable energy generation and release it during peak hours or when renewable energy is insufficient. It serves as a crucial flexible resource for smoothing fluctuations, peak shaving, and ensuring safety in power systems with a high proportion of renewable energy. However, larger pumped storage capacity is not always better. Insufficient capacity can lead to inadequate system regulation under extreme weather conditions, resulting in wind and solar power curtailment, insufficient reserves, and even the risk of load shedding. Excessive capacity, on the other hand, leads to wasted investment and resource redundancy. Therefore, scientifically identifying the capacity boundaries of pumped storage under different planning horizons, renewable energy penetration rates, and meteorological shock conditions is a key issue in the planning of new power systems.

[0004] Existing pumped storage capacity allocation methods mostly employ typical daily clustering, load continuity curves, or normal full-energy time-series production simulation methods to determine the economically optimal capacity allocation with the goal of minimizing system operating costs, curtailment rates, or overall investment costs. While these methods have some applicability in normal operation planning, they still have the following shortcomings in the context of high proportions of renewable energy and frequent extreme weather events: First, traditional typical daily clustering methods are prone to falling into the "averaging trap." Typical daily clustering typically extracts high-frequency mean features to represent the annual operating status, but high-impact, low-probability events often exhibit long-tail extreme value characteristics. For example, significant fluctuations in offshore wind power during typhoons, continuous low wind and low light causing energy drought, the superposition of midday photovoltaic peaks and nuclear power baseload creating extreme valleys, and the combination of a sudden drop in photovoltaic power and a surge in load in the evening creating steep upswings. These extreme weather scenarios do not occur frequently, but once they do, they directly determine the system's resilience capacity requirements under extreme operating conditions caused by extreme weather. If the planning model relies solely on normal averages or typical daily data, it may underestimate the capacity defense required for extreme weather events. Second, existing methods are insufficient in characterizing the distortion of net load patterns. As wind and solar installed capacity surpasses critical scale, the system's regulation needs are no longer merely a matter of traditional power balance, but encompass multi-dimensional demands including short-term ramp-up, long-term energy migration, valley absorption, evening peak support, and reserve maintenance. Simply using power balance or curtailment rate indicators cannot reveal the physical mechanism of the evolution of net load from "normal fluctuations" to "valley-like distortions," nor can it explain the shift of pumped storage capacity from economic allocation to safety necessity. Third, even when considering extreme operating scenarios, traditional economic optimization models often treat extreme weather as external input, lacking a unified modeling mechanism to transform the impact of extreme weather into source-side output deviation, net load ramp-up impact, valley downsampling degree, and initial energy storage constraints under extreme operating scenarios. Therefore, existing solutions struggle to quantify how different uncertainties affect the load deficit of the power grid system under extreme weather scenarios, making it impossible to scientifically formulate safety defense measures. Summary of the Invention

[0005] Based on the above analysis, this invention aims to disclose a method and system for configuring pumped storage capacity resilience under extreme operating conditions. It determines the basic pumped storage capacity to ensure stable operation of the power grid system through year-round time-series generation simulation, and then identifies the pumped storage resilience survival boundary capacity of the power grid system through net load distortion analysis and high-risk, low-probability extreme operating condition scenario review. This allows for resilience optimization configuration of the pumped storage capacity, thereby providing technical support for the flexibility resource planning and pumped storage construction decisions of high-proportion renewable energy power systems.

[0006] On the one hand, the present invention provides a method for configuring the resilience of pumped storage capacity under extreme operating conditions, specifically including the following steps: Based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme are determined with the goal of minimizing the annualized comprehensive cost. Based on the load demand data, wind power / solar power forecast output data and the scheduling scheme, high-risk, low-probability extreme operating conditions throughout the year are identified. Based on the aforementioned basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss under each of the aforementioned extreme operating conditions, the pumped storage capacity increment corresponding to each of the aforementioned extreme operating conditions is determined based on the load demand data of each of the aforementioned extreme operating conditions, the predicted output data of wind power / solar power, and the aforementioned constraints. Based on the maximum value among the aforementioned capacity increments and the aforementioned base capacity, the pumped storage capacity is configured with resilience optimization to determine the pumped storage resilience survival boundary capacity of the power grid system.

[0007] Furthermore, based on the load demand data, wind / solar power forecast output data, and the dispatch scheme, the high-risk, low-probability extreme operating condition scenarios identified throughout the year include: A sliding scan window is set to scan the scheduling scheme; the duration of the sliding scan window is not less than the shortest duration of the extreme working condition scenario; Based on the scheduling scheme, the new energy drop amplitude, maximum net load ramp rate, and net load depressurization depth of each window are calculated; Based on the new energy drop amplitude of each window, determine whether the corresponding window meets the new energy drop trigger condition; based on the maximum net load ramp rate of each window, determine whether the corresponding window meets the ramp over-limit trigger condition; based on the net load down-pressure depth of each window, determine whether the corresponding window meets the net load down-pressure depth over-limit condition. Windows that simultaneously meet the trigger conditions for new energy drop and ramp-up trigger conditions, or windows that meet the limit conditions for net load downpressure depth, are classified as high-risk, low-probability extreme operating scenarios.

[0008] Furthermore, the process of determining the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost, includes: Multiple candidate pumped storage capacities are set in a tiered, incremental manner; For each of the candidate capacities, based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost, the annualized comprehensive cost and dispatch scheme corresponding to each of the candidate capacities are obtained. The candidate capacity corresponding to the minimum annualized comprehensive cost among all options is selected as the basic capacity for pumped storage.

[0009] Furthermore, the trigger condition for the new energy drop is expressed as follows: ; The new energy sources mentioned above include wind power and photovoltaic power. The average expected contribution to new energy sources; For window The corresponding average output of new energy sources; This is the threshold for the drop in new energy levels.

[0010] Furthermore, the hill-climbing limit-exceeding trigger condition is expressed as follows: ; in, The risk factor for exceeding the limit while climbing; The total uphill climbing capacity provided by conventional units, including thermal power units, hydropower units, and nuclear power units; For window Maximum net load ramp rate, , and They are respectively and Equivalent net load over the time period , , , , They are respectively Periodic load demand, wind power output, photovoltaic power output, and nuclear power output.

[0011] Furthermore, the annualized comprehensive cost is expressed as: ; in, This indicates that the pumped storage capacity is... Annualized comprehensive cost at that time; This represents the total number of time periods throughout the year. The annualized construction cost of pumped storage hydroelectric power generation; for Operating costs of conventional generating units and tie lines during the specified time period; for The penalty costs for curtailing wind and solar power during certain periods; ; The static comprehensive cost per kilowatt; The benchmark discount rate for construction costs; The economic design life of the power plant; This is the construction cost recovery factor; ; A collection of conventional generating units; For the first The conventional unit in the first Actual output during the time period; and These are the linear fuel cost coefficient and fixed maintenance cost coefficient for the unit, respectively. For the first Power received by the time-limited connection line; The comprehensive electricity price for purchased electricity; ; and The first Wind curtailment and solar curtailment during specific time periods; The unit is the penalty coefficient for power curtailment.

[0012] Furthermore, the constraints include power balance constraints, pumped storage reservoir energy evolution constraints, pumping and power generation operation constraints, nuclear power operation constraints, thermal power operation constraints, new energy consumption constraints, system reserve constraints, regional power input constraints, and annualized curtailment rate constraints. The power balance constraint is expressed as: ; in, For the first Time-of-day load demand; , , The first The output of thermal power, nuclear power and hydropower during the period; and The first Actual grid-connected power of wind and solar power during specific time periods; and The first Pumped storage power generation and pumping power during specific time periods; For the first Power received by the time-period connection line.

[0013] Furthermore, the system reserve constraints include system upward reserve constraints and system downward reserve constraints, respectively expressed as: ; ; in, ;in, and The first Conventional units in the first Upward and downward reserves available during the time period; and Pumped storage is respectively the first Upward and downward reserves available during the time period; , , , These are the reserve demand coefficients corresponding to load and renewable energy fluctuations, respectively.

[0014] Furthermore, after determining the pumped storage capacity increment corresponding to each of the extreme operating conditions, the method further includes determining whether the pumped storage capacity corresponding to each of the extreme operating conditions meets the carbon-energy marginal benefit; the determination of whether the pumped storage capacity corresponding to each of the extreme operating conditions meets the carbon-energy marginal benefit includes: The pumped storage capacity corresponding to each of the extreme operating conditions is obtained by summing the basic capacity and the pumped storage capacity increment corresponding to each of the extreme operating conditions. The pumped storage capacity corresponding to each of the extreme operating conditions is mapped to the corresponding pumped storage candidate capacity according to the steps described above. Calculate the reduction in carbon emissions from coal-fired power generation relative to the previous tier of candidate capacity for pumped storage power generation in each of the extreme operating scenarios. Based on the reduction of carbon emissions from coal-fired power plants and the corresponding threshold, it is determined whether the pumped storage capacity for the corresponding extreme operating conditions meets the carbon-energy margin.

[0015] On the other hand, the present invention also provides a pumped storage capacity resilience configuration system under extreme operating conditions, comprising: The basic capacity optimization module is used to determine the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost. The extreme scenario stripping module is used to identify high-risk, low-probability extreme operating conditions throughout the year based on the load demand data, wind power / photovoltaic predicted output data, and the scheduling scheme. The resilience capacity review module is used to determine the pumped storage capacity increment corresponding to each of the extreme operating conditions based on the basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss under each of the extreme operating conditions, based on the load demand data of each of the extreme operating conditions, the predicted output data of wind power / solar power and the constraints. The configuration scheme output module is used to perform resilience optimization configuration of pumped storage capacity based on the maximum value of each capacity increment and the base capacity, and to determine the pumped storage resilience survival boundary capacity of the power grid system.

[0016] The present invention can achieve at least one of the following beneficial effects: By simultaneously considering the basic capacity of pumped storage in the power grid system under normal operation and the capacity increment required to achieve zero load loss under extreme operating conditions caused by extreme weather, this study clarifies the economic efficiency of pumped storage capacity configuration and quantifies the resilient survival boundary capacity of pumped storage that can ensure the safe operation of the system. It transforms the qualitative judgment of "whether extreme weather occurs" in the existing technology into a capacity boundary identification problem that is scannable (scanning capacity at each level), peelable (identifying extreme operating conditions), inheritable (inheriting the basic capacity and the actual energy state of the reservoir before extreme operating conditions), and microscopically reconstructable (extreme operating conditions).

[0017] By setting multiple candidate capacities in a tiered manner, the power grid system's production process is simulated over a continuous period throughout the year. With the goal of minimizing the annualized comprehensive cost, the basic pumped storage capacity, its corresponding annualized comprehensive cost, and dispatch scheme are determined, thus establishing the basic pumped storage capacity necessary to ensure the normal and stable operation of the power grid system. High-risk, low-probability extreme operating scenarios are identified based on renewable energy drop-off and ramp-up trigger conditions. A unified model is then developed for source-side output deviation, net load ramp-up impact, net load valley pressure depth, and initial energy storage state constraints in these extreme operating scenarios. This provides a quantitative basis for determining the rigid requirements for pumped storage capacity configuration under high-risk, low-probability extreme operating scenarios.

[0018] By minimizing the capacity increment required to achieve zero load loss under each of the aforementioned extreme operating scenarios, the pumped storage capacity increment corresponding to each extreme operating scenario can be directly determined. This means determining the pumped storage resilience survival boundary capacity under each extreme operating scenario, ensuring the safety and defense of the power grid system in extreme operating scenarios, and clearly distinguishing the economic value of pumped storage in normal operation from its safety value in extreme operating scenarios. This solves the problem in existing capacity planning models that only focus on cost optimization and struggle to identify the deep valley absorption and steep slope support needs caused by the distortion of net load patterns after a high proportion of renewable energy grid connection.

[0019] By establishing an asymmetric strongly coupled boundary transfer between continuous simulation (macro) and extreme operating condition scenario (micro) of the power grid system throughout the year, the basic capacity obtained from continuous operation throughout the year and the actual energy state of the reservoir before the extreme operating condition scenario are inherited to the extreme operating condition scenario, so as to avoid overestimating or underestimating the resilience capacity demand due to the idealization of the initial water level in the extreme operating condition scenario.

[0020] By introducing the marginal benefits of carbon and energy, we can identify the cutoff point where the newly added pumped storage capacity shifts from being driven by economic decarbonization to being driven by resilience and safety under extreme operating conditions, providing a quantitative basis for explaining the attributes of capacity investment and construction.

[0021] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0022] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0023] Figure 1 This is a flowchart of the method of the present invention; Figure 2 A schematic diagram illustrating the power output analysis of the power grid system during the normal and stable period in January; Figure 3 This report details the reservoir water levels and pumping operation status of the power grid system during the normal and stable period in January. Figure 4 A schematic diagram illustrating the power output analysis of the power grid system during the normal and stable period in July; Figure 5 This refers to the reservoir water levels and pumping operation status of the power grid system during normal and stable periods. Figure 6 The evolution of power balance sensitivity under different pumped storage capacity configurations in January; Figure 7 The evolution of power balance sensitivity under different pumped storage capacity configurations in July. Detailed Implementation

[0024] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0025] Method Example 1 One embodiment of the present invention discloses a method for configuring the resilience of pumped storage capacity under extreme operating conditions, such as... Figure 1 As shown, the specific steps include S1 to S4.

[0026] Step S1: Based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, determine the basic capacity of pumped storage, the corresponding annualized comprehensive cost, and the dispatch scheme based on the goal of minimizing the annualized comprehensive cost.

[0027] Step S1 includes S11 to S13.

[0028] S11. Set multiple candidate pumped storage capacities in a stepped, incremental manner, and form a candidate capacity set. Represented as: ; and These represent the minimum candidate capacity and the maximum candidate capacity, respectively. For step-by-step increments; The value is determined based on the existing configuration capacity of the power grid system or the basic capacity set according to the construction plan. The value is set by taking into account the upper limit of developable resources, grid connection capacity, investment boundary of planning costs, and the maximum adjustment demand that may be required under extreme operating conditions. The step-by-step increment, i.e., the scanning step size simulating the annual time-series production of the power grid system, is determined empirically; the number of candidate capacities in the set is determined by... , and The value of is determined together. It should be noted that... The value selection should be sufficient to support boundary identification (basic capacity and resilient survival boundary capacity). If the step size is too large, the boundary identification will be coarse; if the step size is too small, the computational load will increase. The specific principle is presented through steps S1 to S3.

[0029] S12. For each of the candidate capacities, based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost, the annualized comprehensive cost and the dispatch scheme corresponding to each of the candidate capacities are obtained.

[0030] Specifically, the annualized comprehensive cost of the power grid system is expressed as follows: ; in, This indicates that the pumped storage capacity is... Annualized comprehensive cost at that time; This represents the total number of time periods throughout the year; generally, it can be set to a value of [value missing]. ; The annualized construction cost of pumped storage hydroelectric power generation; for Operating costs of conventional generating units and tie lines during the specified time period; for The cost of curtailing wind and solar power during certain periods.

[0031] Furthermore, the annualized construction cost of pumped storage is calculated using the following formula: ; The static comprehensive cost per kilowatt; The benchmark discount rate for construction costs; The economic design life of the power plant; The construction cost recovery factor is given; all the above parameters are known quantities.

[0032] Furthermore, the operating costs of conventional generating units and tie lines are calculated using the following formula: ; This invention refers to a collection of conventional generating units, including thermal power units, conventional hydropower units, and nuclear power units. For the first The conventional unit in the first The actual output during a given time period is a process variable; and The linear fuel cost coefficient and fixed maintenance cost coefficient of the unit are known. For the first The power received by the time-period tie line is a process variable. The comprehensive electricity price for purchased electricity is known.

[0033] Furthermore, the penalty cost for wind and solar power curtailment is calculated using the following formula: ; and The first The wind curtailment power and solar curtailment power during the time period are process variables, based on the first... The actual output of wind and solar power during the specified time period is determined; The unit power curtailment penalty coefficient is known.

[0034] Specifically, the constraints include power balance constraints, pumped storage reservoir energy evolution constraints, pumping and power generation operation constraints, nuclear power operation constraints, thermal power operation constraints, new energy consumption constraints, system reserve constraints, regional power input constraints, and annualized curtailment rate constraints.

[0035] The power balance constraint is expressed as: ; in, For the first time in a year Time-specific load demand is based on fundamental planning data and is known. , , The first The output of thermal power, nuclear power, and conventional hydropower during the time period are process variables. and The first The actual grid-connected power of wind and solar power during the time period is a process variable. and The first The power generation and pumping power of pumped storage hydroelectric power during the time period are process variables; For the first The power received by the time-period connection line is a process variable.

[0036] The energy evolution constraint of pumped storage reservoirs is expressed as: ; ; in, For the first The equivalent energy storage capacity of pumped-storage reservoirs during specific time periods is a process variable. and The first The pumping power and power generation of pumped storage systems during different time periods are process variables. and These are the lower and upper limits of the equivalent storage capacity of the reservoir, respectively, which are known. The pumping efficiency is known. The power generation efficiency is known. This refers to the length of the time period, usually one hour. and The first Both the pumping state variable and the power generation state variable are 0 / 1 variables.

[0037] The operational constraints for pumping and power generation are expressed as follows: ; ; ; in, This refers to pumped storage capacity.

[0038] Nuclear power plant operation constraints are expressed as follows: ; in, and These are the lower and upper limits of the technical output of nuclear power units, respectively, which are known. These are available state variables for nuclear power units, and are 0 / 1 variables.

[0039] The operating constraints of thermal power plants are expressed as follows: ; ; in, and These are the lower limit and upper limit of deep peak shaving for thermal power units, respectively, which are known. This is a variable representing the operating status of the thermal power unit, and it is either a 0 or 1 variable. and These are the downward and upward climbing capacities of the thermal power unit, respectively, which are known. The constraint on the absorption of new energy sources is expressed as: ; ; in, and The first The maximum available output of wind and solar power during the specified time period is known and predicted based on historical data.

[0040] System reserve constraints include upward system reserve constraints and downward system reserve constraints, which are represented as follows: ; ; in, ;in, and The first Conventional units in the first The available upward and downward reserves during the time period are known. and Pumped storage is respectively the first The available upward and downward reserves during the time period are known. , , , These are the reserve demand coefficients corresponding to load and renewable energy fluctuations, respectively, and are known.

[0041] The regional power input constraint is represented as: ; in, This indicates the upper limit of the power supply received by the power grid system in the studied area.

[0042] The annualized curtailment rate constraint is expressed as: ; in, This represents the annualized curtailment rate. This is the annualized power curtailment rate threshold; ; .

[0043] Specifically, in step S12, for each candidate capacity, based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the above constraints, the annual time-series production of the power grid system is simulated. With the goal of minimizing the annualized comprehensive cost, the annualized comprehensive cost and scheduling scheme corresponding to each candidate capacity are obtained. For example, the simulation process can be implemented using Matlab.

[0044] S13. Select the candidate capacity corresponding to the minimum annualized comprehensive cost among all options as the basic pumped storage capacity. ;in, This represents the capacity ladder where the candidate capacity corresponding to the minimum annualized comprehensive cost lies. Indicates the basic capacity.

[0045] Record the scheduling scheme corresponding to the candidate capacity, wherein the scheduling scheme includes the actual output of each unit in the power grid system throughout the year.

[0046] like Figures 2 to 5 In a certain study area, under the future medium-term planning vision, the power grid system has formed a high proportion of new energy structures, but has not yet completely lost its regulatory flexibility. Wind power capacity is 42,430 MW, photovoltaic capacity is 30,000 MW, nuclear power capacity is 22,722 MW, hydropower capacity is 12,000 MW, conventional thermal power capacity is 37,920 MW, peak-shaving coal-fired power capacity is 22,266 MW, and coal-fired combined heat and power capacity is 13,400 MW. Through continuous year-round production simulations for all periods, in most normal months, a basic pumped storage capacity of 15,000 MW is sufficient to meet the system's peak shaving and valley filling requirements, long-cycle energy migration, and reservoir water level balance requirements.

[0047] like Figure 2 To ensure that system load and renewable energy output fluctuations are relatively controllable during the normal and stable period in January, such as Figure 3 The display shows that the basic capacity of the 15,000 MW pumped storage hydropower transfers energy through daily pumping and power generation conversion, and the equivalent storage capacity of the reservoir has not reached the upper or lower limit.

[0048] like Figure 4 To ensure a stable period in July, although photovoltaic power generation experienced significant intraday fluctuations, such as... Figure 5 The system can still rely on its 15,000 MW pumped storage capacity to absorb water during the day and support peak water levels at night, keeping the reservoir level within a reasonable range.

[0049] In this embodiment, by setting multiple candidate capacities in a stepped manner, the production process of the power grid system during a continuous period throughout the year is simulated. With the goal of minimizing the annualized comprehensive cost, the basic capacity of pumped storage, as well as the corresponding annualized comprehensive cost and dispatch scheme, are determined. First, the basic capacity of pumped storage that can ensure the normal and stable operation of the power grid system is determined. Considering the economics of pumped storage construction (lowest cost), it can be regarded as the economic basic capacity, providing a preliminary quantitative basis for the construction of pumped storage and laying the foundation for subsequent research on extreme operating conditions.

[0050] Step S2: Based on the load demand data, wind / solar power forecast output data, and the dispatch scheme, determine the high-risk, low-probability extreme operating conditions throughout the year. These high-risk, low-probability extreme operating conditions include extreme operating conditions caused by extreme weather events such as typhoons, heavy rainstorms, and extreme cold.

[0051] Step S2 includes S21 to S23.

[0052] S21. A sliding scan window is set to scan the scheduling scheme, and the duration of the sliding scan window is not less than the shortest duration of the extreme working condition scenario. The sliding scan window is represented as... ; The starting time period, The number of time periods within the window. , This represents the shortest duration for extreme operating conditions.

[0053] S22. Based on the scheduling scheme, calculate the new energy drop magnitude, maximum net load ramp rate, and net load reduction depth for each window. The new energy sources include wind power and photovoltaic power.

[0054] Calculate the drop in energy prices using the following formula: ; in, , is the expected average output of new energy sources, which can be determined based on historical data and is known; For window The corresponding average output of new energy sources is determined based on the aforementioned scheduling scheme. ); This represents the length of the window period.

[0055] Calculate the maximum net load ramp rate using the following formula: ; For window Maximum net load ramp rate; and They are respectively and Equivalent net load defined by time period , , , , They are respectively Time-of-use load demand, wind power output, photovoltaic power output, and nuclear power output; Calculate the net load underpressure depth using the following formula: ; in, This represents the peak load within the window. The net load depressurization depth is used to characterize the depth of the net load trough under the combined effect of new energy and nuclear power baseload.

[0056] S23. Based on the new energy drop amplitude of each window, determine whether the corresponding window meets the new energy drop trigger condition; based on the conventional unit ramping capability of each window, determine whether the corresponding window meets the ramping limit trigger condition; based on the net load depressurization depth of each window, determine whether the corresponding window meets the net load depressurization depth limit condition.

[0057] The trigger condition for the new energy source falling is expressed as follows: ; in, This is the threshold for the drop in new energy levels.

[0058] The hill-climbing limit-exceeding trigger condition is expressed as follows: ; in, The risk factor for exceeding the limit while climbing is determined based on experience; The total uphill climbing capacity provided by conventional units, including thermal power units, conventional hydropower units, and nuclear power units; ;in, A collection of conventional units capable of climbing hills; For the first The uphill ramping capability of the conventional generating unit. The ramping limit triggering condition enables the identification of net load morphological distortion in the system.

[0059] The conditions for exceeding the limit for net load pressure depth are: ; in, This is the threshold for the depth of pressure under net load.

[0060] S24. Windows that simultaneously meet the new energy drop trigger condition and the ramp over-limit trigger condition, or windows that meet the net load down-pressure depth over-limit condition, are judged as high-risk, low-probability extreme working conditions.

[0061] All high-risk, low-probability extreme operating conditions constitute a set of high-risk, low-probability extreme operating conditions, denoted as: .

[0062] It should be noted that by identifying high-risk, low-probability extreme working conditions throughout the year through steps S21 to S24 of step S2, the method of this invention can proceed directly to step S3. If it is necessary to determine typical annual scenarios in practical applications, then the entire set of scenarios corresponding to all sliding windows can be used. Middle stripping Clustering the remaining scenarios to obtain typical scenarios can avoid the average processing of high-impact, low-probability events.

[0063] This embodiment identifies high-risk, low-probability extreme operating conditions based on new energy drop triggering conditions, ramp-up triggering conditions, and net load downpressure depth over-limit conditions. This avoids the long-tail risk of traditional typical daily or mean clustering methods that eliminate extreme weather scenarios, and provides a scientific quantitative basis for subsequent steps to determine the rigid requirements for pumped storage capacity configuration under high-risk, low-probability extreme operating conditions.

[0064] Step S3: Based on the basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss in each of the extreme operating scenarios, determine the pumped storage capacity increment corresponding to each of the extreme operating scenarios based on the load demand data, wind power / photovoltaic predicted output data and the constraints.

[0065] Specifically, after determining the pumped storage capacity in step S1 with the goal of minimizing the annualized comprehensive cost, the operation of the power grid under high-risk, low-probability extreme operating conditions was not considered. Therefore, load shedding may occur during operation under extreme conditions. In this case, the power balance expression for the power grid system is: ; in, This represents the power at which the load is lost.

[0066] To achieve zero load loss under each of the aforementioned extreme operating conditions, then we have That is, satisfying the power balance constraint. .

[0067] Furthermore, for any of the aforementioned extreme operating conditions, let the starting time period be... The boundary value inheritance of pumped storage capacity is then: .

[0068] The initial energy inheritance of the reservoir is: ; in, For the first A high-risk, low-probability extreme working condition scenario; This represents the pumped storage capacity corresponding to the initial period under this extreme operating condition. Basic capacity; The equivalent energy storage capacity of the reservoir in the period leading up to the occurrence of extreme working conditions; This is to provide the initial reservoir equivalent energy storage for extreme operating conditions.

[0069] Furthermore, in extreme working conditions... With the goal of minimizing the capacity increment required to achieve zero load loss, this study is based on extreme operating conditions. The load demand data, wind / solar power forecast output data, and the aforementioned constraints were used to simulate extreme operating conditions. Corresponding increase in pumped storage capacity .but The corresponding pumped storage capacity to achieve zero load loss is This capacity is the first The resilience and survival boundary capacity of pumped storage under extreme operating conditions.

[0070] The so-called resilient survival boundary capacity refers to the minimum flexibility capacity that a power grid system must possess to ensure that it does not cut off loads, break down reserve constraints, or exceed the upper and lower limits of reservoir energy when encountering high-impact, low-probability extreme events. This capacity may be higher than the base capacity, and the additional portion may not necessarily bring significant operating cost savings or carbon emission reduction benefits, but it is a physical necessity to prevent the power grid from becoming unstable under extreme shocks.

[0071] This embodiment, by aiming to minimize the capacity increment required to achieve zero load loss under each of the aforementioned extreme operating scenarios, directly determines the pumped storage capacity increment corresponding to each extreme operating scenario. This means determining the pumped storage resilience survival boundary capacity under each extreme operating scenario, ensuring the safety and defense of the power grid system in extreme operating scenarios. It clearly distinguishes between the economic value of pumped storage in normal operation (minimum operating cost in step S1) and its safety value in extreme operating scenarios (zero load loss in step S3). This solves the problem in existing capacity planning models that only focus on cost optimization and struggle to identify the deep valley absorption and steep slope support needs caused by the distortion of net load patterns after a high proportion of new energy grid connection.

[0072] By establishing an asymmetric strongly coupled boundary transfer between continuous simulation (macro) and extreme operating condition scenario (micro) of the power grid system throughout the year, the basic capacity obtained from continuous operation throughout the year and the actual energy state of the reservoir before the extreme operating condition scenario are inherited to the extreme operating condition scenario, so as to avoid overestimating or underestimating the resilience capacity demand due to the idealization of the initial water level in the extreme operating condition scenario.

[0073] Step S4: Based on the maximum value among the capacity increments and the base capacity, perform resilience optimization configuration of the pumped storage capacity to determine the pumped storage resilience survival boundary capacity of the power grid system.

[0074] Specifically, the resilient survivability boundary capacity of pumped storage is: ; in, This is the final determined resilient survival boundary capacity for pumped storage.

[0075] like Figure 6 and Figure 7 The power balance sensitivity evolution processes for different pumped storage capacity configurations in January and July are presented respectively. Through simulation and comparison of multiple capacity levels, it was found that as the pumped storage capacity increases, the system's ability to absorb new energy sources during the midday trough period and its upward support capacity during the evening peak period strengthens. Simulation scans show that a base capacity of 15,000 MW cannot fully cover the reserve and peak-shaving needs under extreme operating conditions. Through review of extreme operating scenarios, the resilience survival boundary capacity of pumped storage was determined to be 19,000 MW. Figure 3 / 4 / 5 / 6, the medium-term planning vision of the studied area shows a binary differentiation characteristic of "normal basic capacity - extreme resilience capacity", that is, the capacity required for normal operation is 15,000 MW, and the capacity required to defend against HILP extreme operating conditions is 19,000 MW.

[0076] It should be noted that the differences in power output and pumped storage power generation under different capacities are not obvious because the number of units on the vertical axis is large. The technical solution and principle of this invention are mainly described in text, and the pictures are used for auxiliary illustration.

[0077] In this embodiment, under the long-term vision of a leap forward, the studied region is projected to see wind power capacity increase to 52,440 MW, photovoltaic capacity to 40,000 MW, and nuclear power capacity to 25,640 MW. Compared to the medium term, wind power capacity increases by 10,010 MW, photovoltaic capacity increases by 10,000 MW, and the combined increase from wind and solar power is approximately 20,010 MW, or about 20.01 GW. The simultaneous increase in wind and solar power capacity and the rigid baseload of nuclear power causes a more pronounced valley-like distortion in the system's net load curve.

[0078] Under this long-term vision of a significant leap forward, the midday peak load of photovoltaic power and the base load of nuclear power together suppress the net load, resulting in insufficient downward adjustment space for the system. In the evening, the rapid withdrawal of photovoltaic power, the increase in load, and the uncertainty of wind power combine to cause a sharp increase in the demand for upward ramping of the system. At this time, pumped storage is no longer just a resource for peak shaving and valley filling in normal economic operation, but becomes a rigid support resource for maintaining the safety boundary of the power grid.

[0079] After optimizing the normal basic capacity, identifying net load distortion, identifying extreme operating conditions, and reviewing the resilience of extreme operating conditions through the method described in this invention, the final recommended pumped storage capacity under the long-term vision is rigidly converged to 23,000 MW.

[0080] This result indicates that once the penetration rate of new energy sources crosses the critical point of system regulation capacity, capacity allocation no longer exhibits the "normal-extreme" hierarchical structure envisioned in the medium-term vision, but rather enters a state of absolute resilience constraint driven by multiple scenarios throughout the year. At this point, the 23,000 MW capacity is no longer determined solely by cost-optimal economics, but rather by the physical demands of the system to avoid load shedding, maintain reserves, and overcome extreme troughs and uphill impacts.

[0081] This embodiment, by simultaneously considering the basic pumped storage capacity of the power grid system under normal operation and the capacity increment required to achieve zero load loss under extreme operating conditions, clarifies the economic efficiency of pumped storage capacity configuration and quantifies the resilient survival boundary capacity of pumped storage that can ensure the safe operation of the system. It transforms the qualitative judgment of "whether extreme weather occurs" in the prior art into a capacity boundary identification problem that can be scanned, stripped, inherited, and reviewed.

[0082] Method Example 2 In another specific embodiment of the present invention, a method for configuring the resilience of pumped storage capacity under extreme operating conditions is disclosed. The specific steps are the same as steps S1 to S4 in the first embodiment of the method, and step S5 is also included.

[0083] Step S5: Determine whether the pumped storage capacity corresponding to each extreme operating scenario meets the carbon-energy marginal benefit. Specifically, this includes steps S51 to S52.

[0084] S51. The pumped storage capacity corresponding to each extreme operating condition scenario is obtained by summing the basic capacity and the pumped storage capacity increment corresponding to each extreme operating condition scenario.

[0085] Specifically, extreme working conditions The corresponding pumped storage capacity to achieve zero load loss is .

[0086] S52. The pumped storage capacity corresponding to each of the extreme operating conditions is mapped to the corresponding pumped storage candidate capacity according to the steps.

[0087] Specifically, the nearest step method is used to... Candidate capacity set is categorized by step. The corresponding candidate pumped storage capacity is expressed as .

[0088] S53. Calculate the reduction in coal-fired power carbon emissions relative to the previous tier of candidate pumped storage capacity for each extreme operating scenario.

[0089] ; in, The pumped storage capacity is Carbon emissions from coal-fired power plants in the current system; This indicates the reduction in carbon emissions from coal-fired power plants resulting from the increase in pumped storage capacity per unit.

[0090] S54. Based on the reduction of carbon emissions from coal-fired power plants and the corresponding threshold, determine whether the pumped storage capacity for the corresponding extreme operating conditions meets the marginal benefits of carbon-energy.

[0091] Specifically, the corresponding thresholds include the threshold for the marginal benefit of carbon-energy approaching zero and the threshold for changes in the marginal benefit of carbon-energy.

[0092] Pumped storage capacity is deemed to meet carbon-energy marginal benefits when one of the following two conditions is met: ; or ; in, The threshold for the marginal benefit of carbon-energy to approach zero; This represents the threshold for changes in the marginal benefits of carbon-energy.

[0093] In this embodiment, steps S4 and S5 are not limited to a specific order and can be performed simultaneously.

[0094] In this embodiment, by introducing the marginal benefit of carbon-energy, the cutoff point in extreme operating scenarios where the newly added pumped storage capacity shifts from being driven by economic carbon reduction to being driven by resilience and safety can be identified, providing a quantitative basis for explaining the attributes of capacity investment and construction.

[0095] System Implementation Examples Another specific embodiment of the present invention discloses a pumped storage capacity resilience configuration system under extreme operating conditions, including a basic capacity optimization module, an extreme scenario stripping module, a resilience capacity review module, and a configuration scheme output module.

[0096] The basic capacity optimization module is used to determine the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost. The extreme scenario stripping module is used to identify high-risk, low-probability extreme operating conditions throughout the year based on the load demand data, wind power / photovoltaic predicted output data, and the scheduling scheme. The resilience capacity review module is used to determine the pumped storage capacity increment corresponding to each of the extreme operating conditions based on the basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss under each of the extreme operating conditions, based on the load demand data of each of the extreme operating conditions, the predicted output data of wind power / solar power and the constraints. The configuration scheme output module is used to perform resilience optimization configuration of pumped storage capacity based on the maximum value of each capacity increment and the base capacity, and to determine the pumped storage resilience survival boundary capacity of the power grid system.

[0097] Compared to existing technologies, the beneficial effects of the pumped storage resilient survival boundary capacity configuration system under extreme operating conditions provided in this embodiment are basically the same as those provided in the method embodiment, and will not be elaborated here.

[0098] It should be noted that the above embodiments are based on the same inventive concept, and any parts not described repeatedly can be referenced from each other.

[0099] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for configuring the resilience of pumped storage capacity under extreme operating conditions, characterized in that, Includes the following steps: Based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme are determined with the goal of minimizing the annualized comprehensive cost. Based on the load demand data, wind power / solar power forecast output data and the scheduling scheme, high-risk, low-probability extreme operating conditions throughout the year are identified. Based on the aforementioned basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss under each of the aforementioned extreme operating conditions, the pumped storage capacity increment corresponding to each of the aforementioned extreme operating conditions is determined based on the load demand data of each of the aforementioned extreme operating conditions, the predicted output data of wind power / solar power, and the aforementioned constraints. Based on the maximum value among the aforementioned capacity increments and the aforementioned base capacity, the pumped storage capacity is configured with resilience optimization to determine the pumped storage resilience survival boundary capacity of the power grid system.

2. The pumped storage capacity resilience configuration method according to claim 1, characterized in that, Based on the load demand data, wind / solar power forecast output data, and the dispatch scheme, the high-risk, low-probability extreme operating conditions identified throughout the year include: A sliding scan window is set to scan the scheduling scheme; the duration of the sliding scan window is not less than the shortest duration of the extreme working condition scenario; Based on the scheduling scheme, the new energy drop amplitude, maximum net load ramp rate, and net load depressurization depth of each window are calculated; Based on the new energy drop amplitude of each window, determine whether the corresponding window meets the new energy drop trigger condition; based on the maximum net load ramp rate of each window, determine whether the corresponding window meets the ramp over-limit trigger condition; based on the net load down-pressure depth of each window, determine whether the corresponding window meets the net load down-pressure depth over-limit condition. Windows that simultaneously meet the trigger conditions for new energy drop and ramp-up trigger conditions, or windows that meet the limit conditions for net load downpressure depth, are classified as high-risk, low-probability extreme operating scenarios.

3. The pumped storage capacity resilience configuration method according to claim 2, characterized in that, Based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, the determination of the pumped storage basic capacity, the corresponding annual comprehensive cost, and the dispatch scheme, with the goal of minimizing the annualized comprehensive cost, includes: Multiple candidate pumped storage capacities are set in a tiered, incremental manner; For each of the candidate capacities, based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost, the annualized comprehensive cost and dispatch scheme corresponding to each of the candidate capacities are obtained. The candidate capacity corresponding to the minimum annualized comprehensive cost among all options is selected as the basic capacity for pumped storage.

4. The pumped storage capacity resilience configuration method according to claim 2, characterized in that, The trigger condition for the new energy source falling is expressed as follows: ； The new energy sources mentioned above include wind power and photovoltaic power. The average expected contribution to new energy sources; For window The corresponding average output of new energy sources; This is the threshold for the drop in new energy levels.

5. The method for configuring pumped storage capacity resilience according to claim 2, characterized in that, The hill-climbing limit-exceeding trigger condition is expressed as follows: ； in, The risk factor for exceeding the limit while climbing; The total uphill climbing capacity provided by conventional units, including thermal power units, hydropower units, and nuclear power units; For window Maximum net load ramp rate, , and They are respectively and Equivalent net load over the time period , , , , They are respectively Periodic load demand, wind power output, photovoltaic power output, and nuclear power output.

6. The pumped storage capacity resilience configuration method according to claim 3, characterized in that, The annualized comprehensive cost is expressed as follows: ； in, This indicates that the pumped storage capacity is... Annualized comprehensive cost at that time; This represents the total number of time periods throughout the year. The annualized construction cost of pumped storage hydroelectric power generation; for Operating costs of conventional generating units and tie lines during the specified time period; for The penalty costs for curtailing wind and solar power during certain periods; ； The static comprehensive cost per kilowatt; The benchmark discount rate for construction costs; The economic design life of the power plant; This is the construction cost recovery factor; ； A collection of conventional generating units; For the first The conventional unit in the first Actual output during the time period; and These are the linear fuel cost coefficient and fixed maintenance cost coefficient for the unit, respectively. For the first Power received by the time-limited connection line; The comprehensive electricity price for purchased electricity; ； and The first Wind curtailment and solar curtailment during specific time periods; The unit is the penalty coefficient for power curtailment.

7. The pumped storage capacity resilience configuration method according to claim 3, characterized in that, The constraints include power balance constraints, pumped storage reservoir energy evolution constraints, pumping and power generation operation constraints, nuclear power operation constraints, thermal power operation constraints, new energy consumption constraints, system reserve constraints, regional power input constraints, and annualized curtailment rate constraints. The power balance constraint is expressed as: ； in, For the first Time-of-day load demand; , , The first Power output of thermal power, nuclear power and hydropower during the period; and The first Actual grid-connected power of wind and solar power during specific time periods; and The first Pumped storage power generation and pumping power during specific time periods; For the first Power received by the time-period connection line.

8. The pumped storage capacity resilience configuration method according to claim 7, characterized in that, The system reserve constraints include upward system reserve constraints and downward system reserve constraints, which are represented as follows: ； ； in, ;in, and The first Conventional units in the first Upward and downward reserves available during the time period; and Pumped storage is respectively the first Upward and downward reserves available during the time period; , , , These are the reserve demand coefficients corresponding to load and renewable energy fluctuations, respectively.

9. The method for configuring pumped storage capacity resilience according to claim 3, characterized in that, After determining the pumped storage capacity increment corresponding to each extreme operating condition scenario, the method further includes determining whether the pumped storage capacity corresponding to each extreme operating condition scenario meets the carbon-energy marginal benefit. The determination of whether the pumped storage capacity corresponding to each of the extreme operating scenarios meets the carbon-energy marginal benefit includes: The pumped storage capacity corresponding to each of the extreme operating conditions is obtained by summing the basic capacity and the pumped storage capacity increment corresponding to each of the extreme operating conditions. The pumped storage capacity corresponding to each of the extreme operating conditions is mapped to the corresponding pumped storage candidate capacity according to the steps described above. Calculate the reduction in carbon emissions from coal-fired power generation relative to the previous tier of candidate capacity for pumped storage power generation in each of the extreme operating scenarios. Based on the reduction of carbon emissions from coal-fired power plants and the corresponding threshold, it is determined whether the pumped storage capacity for the corresponding extreme operating conditions meets the carbon-energy marginal benefit.

10. A pumped storage capacity resilience configuration system under extreme operating conditions, characterized in that, include: The basic capacity optimization module is used to determine the pumped storage basic capacity, the corresponding annualized comprehensive cost, and the dispatch scheme based on the annual load demand data of the power grid system, the predicted output data of wind power / solar power, and the set constraints, with the goal of minimizing the annualized comprehensive cost. The extreme scenario stripping module is used to identify high-risk, low-probability extreme operating conditions throughout the year based on the load demand data, wind power / photovoltaic predicted output data, and the scheduling scheme. The resilience capacity review module is used to determine the pumped storage capacity increment corresponding to each of the extreme operating conditions based on the basic capacity, with the goal of minimizing the capacity increment required to achieve zero load loss under each of the extreme operating conditions, based on the load demand data of each of the extreme operating conditions, the predicted output data of wind power / solar power and the constraints. The configuration scheme output module is used to perform resilience optimization configuration of pumped storage capacity based on the maximum value of each capacity increment and the base capacity, and to determine the pumped storage resilience survival boundary capacity of the power grid system.

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