Pumped storage multi-year capacity optimization method and system considering wind and solar continuous low output

Abstract

The application considers a pumped storage multi-year capacity optimization method and system considering continuous low output of wind and light, the method comprising: constructing a target function considering economy and new energy consumption demand comprehensively, constructing pumped storage construction constraints, typical scenario constraints and extreme scenario constraints; the pumped storage multi-year capacity optimization model considering continuous low output of wind and light is composed of the target function, the pumped storage construction constraints, the typical scenario constraints and the extreme scenario constraints, taking typical week scenarios and extreme week scenarios as inputs, and using a solver to optimize and solve, and finally obtaining an optimized configuration scheme of pumped storage capacity. The system comprises a target function construction module, a constraint construction module and a model construction and solving module. The application solves potential extreme power supply problems of a power system.

Description

Technical Field

[0001] This invention belongs to the field of power system operation planning, specifically involving a method and system for optimizing the multi-year capacity of pumped storage considering continuous low-output wind and solar power. Background Technology

[0002] With the rapid advancement of new energy power generation technologies such as wind and solar power, a high proportion of new energy sources being integrated into the grid has become a key characteristic of new power systems. However, due to the significant randomness and volatility inherent in new energy power generation, future power systems will face a series of severe challenges in planning and operation, including increased difficulty in ensuring a secure power supply, continued pressure to absorb new energy sources, and increasingly prominent issues related to system security and stability. Therefore, flexible adjustment resources capable of guaranteeing power supply, supporting the absorption of new energy sources, and enhancing system stability are extremely crucial for the construction of new power systems.

[0003] Pumped storage is currently the most mature, economically efficient, and large-scale development-adjustable power source.

[0004] Traditional pumped storage capacity optimization methods typically rely on wind and solar power output characteristics and load characteristics, employing typical scenarios for optimization solutions. These methods focus on short-term daily power balance, providing capacity planning schemes that meet system economic and reliability requirements. However, with the increasing frequency of extreme weather events, new power systems with a high proportion of renewable energy face severe power balance risks. In extreme scenarios with multiple consecutive days of no wind or solar power, the power system will face power shortages during several consecutive peak load periods due to a significant decrease in wind and solar power output. The load supply situation will be extremely severe, potentially leading to large-scale load shedding events, resulting in serious socio-economic losses and jeopardizing the overall security of the power system. Existing pumped storage capacity optimization methods have not fully considered the medium- and long-term power imbalance risks caused by extreme and continuous low output from renewable energy sources and their impact on pumped storage capacity optimization schemes.

[0005] In summary, it is urgent to identify and extract extreme scenarios based on the extreme low output fluctuations and output levels of new energy sources. Considering the constraints of extreme scenarios, including load shedding constraints, and taking into account the economic efficiency and reasonable absorption requirements of typical scenarios, while also taking into account the supply guarantee needs of extreme scenarios, we need to construct a pumped storage capacity optimization model that considers the continuous low output of wind and solar power in extreme scenarios. We need to conduct in-depth research on how to improve the system's flexible adjustment capability and power supply reliability under extreme conditions by optimizing pumped storage capacity, and analyze the mechanism of pumped storage in ensuring peak supply in scenarios of continuous low output of new energy sources. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing pumped storage capacity optimization methods and, considering the power supply requirements under extreme scenarios of continuous low wind and solar power output, propose a multi-year pumped storage capacity optimization method and system that takes into account such scenarios. This method avoids large-scale load shedding under extreme conditions by constructing a pumped storage capacity optimization method that avoids such constraints. By identifying and extracting extreme scenarios of continuous low wind and solar power output, the method comprehensively describes the fluctuation characteristics of such scenarios and explores how to optimize pumped storage capacity configuration to improve power supply pressure under extreme conditions, thereby promoting the solution of potential extreme power supply problems in the power system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A multi-year capacity optimization method for pumped storage hydropower with continuous low output from wind and solar power includes the following steps:

[0009] Step 1: Construct an objective function that comprehensively considers economic efficiency and the demand for renewable energy consumption;

[0010] Step 2: Combining construction scale limitations and unit operation relationships, constrain investment decisions to ensure the feasibility of the plan and establish constraints for pumped storage construction;

[0011] Step 3: Construct typical scenario constraints by comprehensively considering various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits, and power balance conditions;

[0012] Step 4: Identify and extract low-output scenarios based on historical data, appropriately relax the load shedding restrictions, and construct extreme scenario constraints for safety verification;

[0013] Step 5: The multi-year capacity optimization model for pumped storage, which considers continuous low-output wind and solar power, is composed of the objective function, pumped storage construction constraints, typical scenario constraints, and extreme scenario constraints. The model is then optimized using a solver with typical and extreme weekly scenarios as inputs, and finally the optimized configuration scheme of pumped storage capacity is obtained.

[0014] A further improvement of this invention is that, in step one, an objective function is constructed that comprehensively considers economic efficiency and the demand for renewable energy consumption, including:

[0015] With the goal of minimizing the overall system cost, the objective function includes: investment depreciation, coal consumption, start-up and shutdown, power curtailment and load shedding costs, and is weighted and summed according to typical scenario weights, and then converted to annual values.

[0016] The specific mathematical expression of the objective function is as follows:

[0017]

[0018] In the formula: k represents the typical scenario designation; h represents the year designation; t represents the time designation; w represents the new energy base designation; n represents the load node designation; g represents the thermal power unit designation; N K N represents the total number of typical scenarios. H N is the capacity planning lifespan; T is the total duration of the calculation cycle, taken as 168; N W N represents the total number of new energy bases. N N represents the total number of load nodes. G P represents the number of each thermal power unit; k q represents the sampling probability for each typical scenario. h The conversion factor for converting weekly operating costs to annual operating costs; K w K represents the penalty coefficient for curtailment of renewable energy. n This is the load shedding penalty factor; To provide power for the prediction of new energy sources for the system at time t. The actual renewable energy output absorbed by the system at time t; For the load shedding amount at each load node; C g,Ge C is the slope of the approximated coal consumption function. g,min The coal consumption cost for each thermal power unit with minimum technical output; For the actual output of each thermal power unit, P g,min Minimum technical output for each thermal power unit; S gz S represents the shutdown cost coefficient for thermal power units. gy This is the start-up cost coefficient for thermal power units; For thermal power units, the 0-1 state variables are used. For the 0-1 shutdown action variable of thermal power unit; r is the variable for the 0-1 start-up action of the thermal power unit. h The discount factor for year h; Investment costs for pumped storage units;

[0019]

[0020]

[0021] In the formula: ps refers to the designation of the pumped storage power station; c refers to the designation of the constant-speed, constant-frequency pumped storage unit in ps; v refers to the designation of the variable-speed, constant-frequency pumped storage unit in ps; N PS C represents the number of pumped storage power stations; c,h C v,h Y represents the investment depreciation factor for each pumped-storage unit; c,h Y v,h For each pumped-storage unit, r represents the state variable during its commissioning; m,c / v is the annual value factor of the pumped-storage unit's c / v, i is the discount rate (taken as 6%), and m is the operating years of the pumped-storage unit's c / v.

[0022] A further improvement of this invention is that, in step two, by combining the construction scale limitations and the relationship between the units, investment decisions are constrained to ensure the feasibility of the scheme, and constraints on pumped storage construction are constructed, including: annual maximum investment constraints, maximum investment constraints for a single power station, constraints on the order of power station construction, constraints on the order of power station unit construction, constraints on the relationship between construction and unit output, and constraints on the relationship between construction actions and status.

[0023] A further improvement of this invention is that, in step three, various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits and power balance conditions are comprehensively considered to construct typical scenario constraints, including: thermal power unit status constraints, thermal power unit operation constraints, minimum continuous start-up and shutdown time constraints, thermal power unit reserve constraints, pumped storage unit constraints, new energy power operation constraints, load shedding constraints, power balance constraints, power flow safety constraints and total reserve constraints.

[0024] A further improvement of this invention is that the constraints of the pumped-storage unit are modeled for both constant-speed constant-frequency units and variable-speed constant-frequency units.

[0025] Modeling a constant-speed, constant-frequency pumped-storage unit, namely:

[0026]

[0027]

[0028]

[0029] In the formula: This represents the actual power output of the constant-speed pumped-storage unit c; This indicates that the constant-speed pumped-storage unit C is in standby mode. This indicates the maximum and minimum power output of the constant-speed pumped-storage unit c; This represents the power generation state variable of constant-speed pumped-storage unit c; This indicates that the constant-speed pumped-storage unit C is in standby mode. This represents the actual pumping power of the constant-speed pumped storage unit c;

[0030] This indicates the constant-speed pumping power of the constant-speed pumped storage unit c; This represents the pumping state variable of the constant-speed pumped storage unit c;

[0031] Simultaneously, a model is constructed for the variable-speed constant-frequency pumped-storage unit, namely:

[0032]

[0033]

[0034]

[0035]

[0036] In the formula: This represents the actual power output of the variable-speed pumped-storage unit v; This represents the actual pumping power of the variable speed pumped storage unit (v). This represents the power generation state variable of the variable-speed pumped-storage unit v; This represents the pumping state variable of the variable-speed pumped storage unit v; This indicates the maximum and minimum generating capacity of the variable speed pumped storage unit v; This indicates the maximum and minimum pumping power of the variable speed pumped storage unit v; This indicates the upward standby of the variable speed pumped storage unit v; This indicates the downward standby of variable speed pumped storage unit v;

[0037] Pumped storage cannot be in both power generation and pumping states simultaneously.

[0038]

[0039] In addition, it is necessary to construct storage capacity balance constraints:

[0040]

[0041]

[0042]

[0043]

[0044] In the formula: This indicates the real-time reservoir capacity of the pumped storage power station (ps). This represents the initial reservoir capacity of the pumped storage power station ps; η represents the reservoir capacity of the pumped storage power station at time psT; p and η g These represent pumping efficiency and power generation efficiency, respectively. and These represent the maximum and minimum reservoir capacity of the pumped storage power station ps, respectively.

[0045] A further improvement of this invention lies in the fact that, in the constraints of new energy power operation, the output of new energy is less than the total resource volume, and the limitation of new energy absorption rate is also considered:

[0046] First, the power generation must meet the constraint that it is less than the resource quantity;

[0047]

[0048] In the formula: This represents the actual wind and solar power output of the new energy base w at time t under typical scenario k; This represents the predicted wind and solar power of the new energy base w at time t under typical scenario k;

[0049] At the same time, it is necessary to ensure that the output of new energy sources is within a reasonable range of consumption.

[0050]

[0051] In the formula: μ represents the reasonable renewable energy consumption rate, which is taken as 95%.

[0052] A further improvement of this invention is that, in the load shedding constraint, the total load shedding amount in a single scenario is less than a certain threshold:

[0053]

[0054] In the formula: This represents the upper limit of the total load shedding under typical scenario k.

[0055] A further improvement of the present invention is that the total reserve constraint takes into account the reserve capacity requirement due to load forecasting error and new energy forecasting error.

[0056]

[0057]

[0058] In the formula: ω is the spinning reserve rate, which is taken as 5%; ω represents the maximum system load under typical scenario k; w This represents a coefficient for the increased spinning reserve capacity in response to random fluctuations in new energy sources, taken as 25%.

[0059] A further improvement of the present invention is that, in step four, the extreme scenario constraints further relax the load shedding limit on the basis of the typical scenario constraints, and at the same time, the extreme scenario variables are not included in the objective function, but only in the constraints for extreme supply security verification.

[0060] Replace the variables in various power sources and pumped storage constraints with variables under extreme scenarios, and introduce extreme scenario constraints for reservoir capacity balance constraints (12)-(15):

[0061]

[0062]

[0063]

[0064]

[0065] Similarly, the constraints for other typical scenarios are rewritten.

[0066] Considering a multi-year capacity optimization system for pumped-storage hydropower with continuous low-output wind and solar power, including:

[0067] The objective function construction module constructs an objective function that comprehensively considers economic efficiency and the demand for renewable energy consumption.

[0068] The first constraint construction module, in combination with construction scale limitations and unit operation relationships, constrains investment decisions to ensure the feasibility of the scheme and constructs pumped storage construction constraints.

[0069] The second constraint construction module comprehensively considers various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits and power balance conditions to construct typical scenario constraints.

[0070] The third constraint construction module identifies and extracts low-output scenarios based on historical data, appropriately relaxes load shedding limits, and constructs extreme scenario constraints for safety verification.

[0071] The model building and solution module consists of an objective function, pumped storage construction constraints, typical scenario constraints, and extreme scenario constraints. It is a multi-year capacity optimization model for pumped storage considering continuous low output of wind and solar power. The model is optimized and solved using a solver with typical and extreme weekly scenarios as inputs, and finally obtains the optimized configuration scheme of pumped storage capacity.

[0072] Compared with the prior art, the present invention has at least the following beneficial technical effects:

[0073] This invention focuses on the power supply guarantee requirements of new energy power generation in extreme low-output scenarios. Based on the requirements of power system safety and reliability, it considers system load shedding limits and constructs extreme scenario constraints. The optimization model simultaneously takes into account the economic objectives under typical scenarios, the demand for new energy consumption, and the safety verification under extreme conditions.

[0074] Compared to existing methods, this model more precisely characterizes the fluctuation characteristics of wind and solar power generation under extreme and sustained low output conditions. It also incorporates extreme scenario constraints into the multi-year capacity optimization configuration model for pumped storage, effectively demonstrating the week-scale regulation capability of pumped storage in response to sustained low output. Specifically, this model considers power supply constraints during periods of extreme low output. By configuring more pumped storage units, it significantly reduces the risk of load shedding under extreme scenarios, improving the reliability and security of power supply, thus showcasing its significant advantages in coping with extreme weather. Attached Figure Description

[0075] Figure 1 This is the overall flowchart of the present invention.

[0076] Figure 2 Here is the load curve of the example system, where Figure 2 (a) is a typical scenario 1. Figure 2 (b) is typical scenario 2. Figure 2 (c) is typical scenario 3. Figure 2 For (d) typical scenario 4, Figure 2 (e) represents extreme scenario 1. Figure 2 (f) represents extreme scenario 2.

[0077] Figure 3 Here are the wind and solar resource curves for the example system, where Figure 3 (a) is typical scenario 1. Figure 3 (b) is typical scenario 2. Figure 3 (c) is typical scenario 3. Figure 3 (d) is typical scenario 4. Figure 3 (e) represents extreme scenario 1. Figure 3 (f) represents extreme scenario 2.

[0078] Figure 4 The output accumulation curves of each unit in a typical scenario are shown. Figure 4 (a) is typical scenario 1. Figure 4 (b) is typical scenario 2. Figure 4 (c) is typical scenario 3. Figure 4 (d) is typical scenario 4.

[0079] Figure 5 Stacked images for extreme scenarios, among which Figure 5 (a) represents extreme scenario 1. Figure 5 (b) represents extreme scenario 2.

[0080] Figure 6 The graph shows the changes in pumping capacity of pumped storage tanks. Figure 6 (a) represents extreme scenario 1. Figure 6 (b) represents extreme scenario 2.

[0081] Figure 7 This is a map showing the real-time changes in reservoir capacity, where... Figure 7 (a) represents extreme scenario 1. Figure 7 (b) represents extreme scenario 2.

[0082] Figure 8 This is a structural block diagram of the present invention. Detailed Implementation

[0083] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0084] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0085] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0086] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0087] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0088] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0089] Example 1

[0090] The present invention provides a method for optimizing the multi-year capacity of pumped storage hydropower considering continuous low-output wind and solar power, comprising:

[0091] First, the objective function of the pumped storage capacity optimization model is determined, with the goal of minimizing the overall system cost. This cost includes the investment and depreciation costs of pumped storage, coal consumption costs of thermal power, unit start-up and shutdown costs, curtailment costs, and load shedding costs. For each typical scenario, the costs are calculated separately and then weighted and summed according to scenario weights to obtain the overall system cost. Second, pumped storage construction constraints are incorporated, considering the construction scale limitations of pumped storage power stations and the relationship between unit construction and output, to constrain investment decisions and ensure the feasibility of the planning scheme. Next, based on the output and load fluctuation characteristics of wind and solar power, representative typical days are selected to construct typical scenario constraints, comprehensively considering thermal power unit status constraints, thermal power unit output constraints, start-up and shutdown constraints, reserve capacity constraints, pumped storage operation constraints, new energy power generation output constraints, load shedding constraints, power balance constraints, power flow security constraints, and the total system reserve capacity constraint. Then, based on statistical analysis of historical wind, solar, and load data, low output standards are set, and extreme continuous low-output scenarios of wind and solar power are identified and extracted to construct extreme scenario constraints. Based on the constraints of typical scenarios, the load shedding constraints were appropriately relaxed, allowing for a higher degree of load shedding. Extreme scenario variables were not included in the objective function; system safety was only verified through constraints to ensure that the planning scheme, while considering economic efficiency and power absorption requirements, also possessed resilience and power supply security under extreme weather conditions. Finally, with the goal of minimizing the overall system cost, a multi-year capacity optimization model for pumped storage, considering construction constraints, typical scenario constraints, and extreme scenario constraints, was constructed. Using several typical and extreme scenarios as inputs, a solver was used for optimization to obtain the optimal capacity configuration scheme for pumped storage.

[0092] The above description of the modeling process for the multi-year capacity optimization method of pumped storage considering continuous low-output wind and solar power includes the following steps, the flowchart of which is shown below. Figure 1 As shown.

[0093] Step 1: This model aims to minimize the overall system cost, comprehensively considering multiple factors such as the investment cost of pumped storage power stations, the operating cost of thermal power units, the cost of curtailment losses, and the cost of load shedding. It also performs a weighted summation for several typical scenarios. Its objective function can be expressed as:

[0094]

[0095] In the formula: k represents the typical scenario designation; h represents the year designation; t represents the time designation; w represents the new energy base designation; n represents the load node designation; g represents the thermal power unit designation; N K N represents the total number of typical scenarios. H N is the capacity planning lifespan; T is the total duration of the calculation cycle, taken as 168; N WN represents the total number of new energy bases. N N represents the total number of load nodes. G P represents the number of each thermal power unit; k q represents the sampling probability for each typical scenario. h The conversion factor for converting weekly operating costs to annual operating costs; K w K represents the penalty coefficient for curtailment of renewable energy. n This is the load shedding penalty factor; To provide power for the prediction of new energy sources for the system at time t. The actual renewable energy output absorbed by the system at time t; For the load shedding amount at each load node; C g,Ge C is the slope of the approximated coal consumption function. g,min The coal consumption cost for each thermal power unit with minimum technical output; For the actual output of thermal power units, P g,min Minimum technical output for each thermal power unit; S gz S represents the shutdown cost coefficient for thermal power units. gy This is the start-up cost coefficient for thermal power units; For thermal power units, the 0-1 state variables are used. For the 0-1 shutdown action variable of thermal power unit; r is the variable for the 0-1 start-up action of the thermal power unit. h The discount factor for year h; Investment costs for pumped storage units.

[0096]

[0097]

[0098] In the formula: ps refers to the designation of the pumped storage power station; c refers to the designation of the constant-speed, constant-frequency pumped storage unit in ps; v refers to the designation of the variable-speed, constant-frequency pumped storage unit in ps; N PS C represents the number of pumped storage power stations; c,h C v,h Y represents the investment depreciation factor for each pumped-storage unit; c,h Y v,h For each pumped-storage unit, r represents the state variable during its commissioning; m,c / v is the annual value factor of the pumped-storage unit's c / v, i is the discount rate (taken as 6%), and m is the operating years of the pumped-storage unit's c / v.

[0099] Step Two: To ensure the feasibility of the optimized scheme, construction constraints for pumped storage are introduced into the model. These mainly include the following aspects:

[0100] 1) Maximum annual investment constraints

[0101]

[0102] In the formula: This indicates the maximum installed capacity of constant speed unit c; This indicates the maximum installed capacity of the variable speed unit v; X represents the maximum construction capacity in year h; c,h X v,h These are the variables for the commissioning and construction of each pumped-storage unit.

[0103] 2) Maximum investment constraints for a single power plant

[0104] Considering construction schedule and resource constraints, ensuring planning feasibility and safety, and limiting the maximum capacity of each pumped storage power station.

[0105]

[0106] In the formula: This indicates the maximum installed capacity of the power plant throughout its entire lifecycle.

[0107] 3) Constraints on the order of power plant construction

[0108]

[0109] In the formula: X ps,h The variable represents the construction action of power plant ps; the above formula indicates that power plant ps1 was constructed before ps2.

[0110] 4) Constraints on the order of commissioning of power plant units

[0111] Y c ≤Y ps ,c∈ps(7)

[0112] Y v ≤Y ps ,v∈ps(8)

[0113] The above formula indicates that the power plant PS was built before the generating units C and V were built.

[0114] 5) Constraints on the relationship between investment and unit output

[0115]

[0116]

[0117]

[0118]

[0119] The above formula means that a unit can only participate in power generation or pumping if it is already under construction.

[0120] 6) Constraints on the relationship between construction actions and states

[0121] Similar to the start-stop constraints of thermal power units, the same variable X is set for the construction action. c,h and the state variable Y of the construction c,h And constrain the relationship between the two.

[0122] Y c / v,h -Y c / v,h-1 =X c / v,h (13)

[0123] X c / v,h ≤Y c / v,h (14)

[0124] Step 3: Based on historical landscape and load data, select representative typical weeks and construct typical scenario constraints. The main constraints include:

[0125] 1) State constraints of thermal power units

[0126]

[0127]

[0128] The above formula represents the coupling relationship between the start-up and shutdown state variables and the start-up and shutdown action variables of a thermal power unit.

[0129] 2) Operating constraints of thermal power units

[0130] The output of thermal power units must meet the minimum technical output and installed capacity limits, and reserve capacity to cope with sudden increases or decreases in the output of new energy sources.

[0131]

[0132]

[0133]

[0134] In the formula: P g,min The minimum technical output of thermal power unit g; P g,max To achieve the maximum technical output of thermal power unit g; is the maximum upward climbing rate of thermal power unit g; Let g be the maximum downward ramp rate of the thermal power unit.

[0135] 3) Minimum continuous start-up and shutdown time constraints for generating units

[0136]

[0137]

[0138] In the formula: This indicates the minimum continuous start-up and shutdown time of a thermal power unit;

[0139] 4) Standby constraints for thermal power units

[0140]

[0141]

[0142]

[0143]

[0144] In the formula: This indicates that thermal power unit g is in standby mode. Indicates the downward standby of thermal power unit g; T r This indicates the spin-off standby response time (10 min).

[0145] 5) Constraints of pumped-storage units

[0146] Modeling a constant-speed, constant-frequency pumped-storage unit, namely:

[0147]

[0148]

[0149]

[0150] In the formula: This represents the actual power output of the constant-speed pumped-storage unit c; This indicates that the constant-speed pumped-storage unit C is in standby mode. This indicates the maximum and minimum power output of the constant-speed pumped-storage unit c; This represents the power generation state variable of constant-speed pumped-storage unit c; This indicates that the constant-speed pumped-storage unit C is in standby mode. This represents the actual pumping power of the constant-speed pumped storage unit c;

[0151] This indicates the constant-speed pumping power of the constant-speed pumped storage unit c; This represents the pumping state variable of the constant-speed pumped storage unit c.

[0152] Simultaneously, a model is constructed for the variable-speed constant-frequency pumped-storage unit, namely:

[0153]

[0154]

[0155]

[0156]

[0157] In the formula: This represents the actual power output of the variable-speed pumped-storage unit v; This represents the actual pumping power of the variable speed pumped storage unit (v). This represents the power generation state variable of the variable-speed pumped-storage unit v; This represents the pumping state variable of the variable-speed pumped storage unit v; This indicates the maximum and minimum generating capacity of the variable speed pumped storage unit v; This indicates the maximum and minimum pumping power of the variable speed pumped storage unit v; This indicates the upward standby of the variable speed pumped storage unit v; This indicates that the variable-speed pumped-storage unit v is in standby mode.

[0158] Pumped storage cannot be in both power generation and pumping states simultaneously.

[0159]

[0160] In addition, it is necessary to construct storage capacity balance constraints:

[0161]

[0162]

[0163]

[0164]

[0165] In the formula: This indicates the real-time reservoir capacity of the pumped storage power station (ps). This represents the initial reservoir capacity of the pumped storage power station ps; η represents the reservoir capacity of the pumped storage power station at time psT; p and η g These represent pumping efficiency and power generation efficiency, respectively. and These represent the maximum and minimum reservoir capacity of the pumped storage power station ps, respectively.

[0166] 6) Operational constraints of new energy power

[0167] First, the amount of electricity generated must be less than the amount of resources.

[0168]

[0169] In the formula: This represents the actual wind and solar power output of the new energy base w at time t under typical scenario k; This represents the predicted wind and solar power of the new energy base w at time t under typical scenario k;

[0170] At the same time, it is necessary to ensure that the output of new energy sources is within a reasonable range of consumption.

[0171]

[0172] In the formula: μ represents the reasonable renewable energy consumption rate, which is taken as 95% in this paper.

[0173] 7) Load shedding constraint

[0174]

[0175] In the formula: This represents the upper limit of the total load shedding under typical scenario k.

[0176] 8) Power balance constraints

[0177]

[0178] In the formula: D n,t,h This represents the injected power at node n.

[0179] 9) Current safety constraints

[0180]

[0181] In the formula: P l,min P l,max These represent the lower and upper limits of the transmission power of line l, respectively; and These represent the power flow distribution factors of pumped storage power station ps, thermal power unit g, new energy base w, and load node n on line l, respectively.

[0182] 10) Total system reserve constraints

[0183]

[0184]

[0185] In the formula: ω is the spinning reserve rate, which is taken as 5% in this paper; ω represents the maximum system load under typical scenario k; w The coefficient represents the spinning reserve capacity to cope with the increase in random fluctuations of new energy sources; in this paper, it is taken as 25%.

[0186] Step 4: In order to improve the system's reliability and resilience under extreme weather conditions, extreme low-output scenarios are identified and screened based on the analysis of historical wind power, photovoltaic and load data.

[0187] The criteria for determining extreme scenarios with sustained low power output from wind and solar power are as follows:

[0188]

[0189] t2-t1≥θ (46)

[0190] This article sets the average daily power output of wind and solar power ρ. ave Less than the rated output ρ of new energy max When the output is α times that of the solar power (10% in this paper) and the duration exceeds θ hours (72 in this paper), it is determined that an extreme continuous low output scenario of wind and solar power has occurred.

[0191] To address these extreme scenarios, variables in various power source and pumped storage constraints are replaced with variables specific to the extreme scenarios, and extreme scenario constraints are introduced (taking load shedding constraints (40), power balance constraints (41), and power flow security constraints (42) as examples):

[0192]

[0193]

[0194]

[0195] In the formula: This represents the upper limit of the total load shedding under extreme scenario e.

[0196] Similarly, rewrite equations (15)-(39) and (43)-(44).

[0197] Step 5: With the goal of minimizing the overall system cost, and considering constraints on pumped storage construction, typical scenarios, and extreme scenarios, a multi-year capacity optimization model for pumped storage, taking into account continuous low-output wind and solar power, is constructed. Furthermore, considering the load demand of the power system under different seasonal conditions and the output characteristics of wind and solar power, several typical and extreme scenarios are introduced as model inputs, along with the operating parameters and investment cost coefficients of the pumped storage power station and its units to be built. An appropriate solution accuracy is set, and a mathematical optimization solver is used to solve the constructed capacity optimization model. Within the constraints, the globally optimal solution that achieves the optimal overall cost is found, yielding the multi-year capacity optimization configuration scheme for pumped storage.

[0198] Example 2

[0199] This paper uses an adapted version of IEEE-RTS79 as an example for analysis. Hydropower units and some thermal power units are replaced with new energy bases. After replacement, the installed capacity of thermal power is 4000MW, wind power is 2000MW, and photovoltaic power is 2000MW. Two pumped-storage power stations are planned for construction, each capable of supporting four constant-speed pumped-storage units and four variable-speed pumped-storage units, for a total planned pumped-storage capacity of 960MW. The parameters of the planned pumped-storage power stations and units are shown in Tables 1-3. The maximum system load is 4000MW. Wind and solar power output and load data are derived from actual statistical data from a province in Northwest my country. The example uses four typical cycles and two extreme cycles, with hourly resolution. The model solution accuracy is 0.1%. The program is based on MATLAB, using the commercial solver Gurobi.

[0200] Table 1 Construction parameters for pumped storage power stations

[0201]

[0202]

[0203] The constant-speed pumped-storage unit and the variable-speed pumped-storage unit each include one model, with the following parameters:

[0204] Table 2 Single-unit parameters of constant-speed pumped-storage units

[0205]

[0206] Table 3 Individual Unit Parameters of Variable Speed ​​Pumped Storage Units

[0207]

[0208] To analyze system demand and scheduling characteristics under different scenarios, this paper constructs load curves and wind / solar power generation curves. Both load curves and wind / solar power output curves are based on typical seasonal demand characteristics, selecting typical weeks from spring, summer, autumn, and winter to reflect the average renewable energy output level and load characteristics of each season. For extreme scenarios, it is assumed that renewable energy output remains at a continuously low level for a certain period, forming a persistent low-output state. The selected load curves and wind / solar resource curves are shown below. Figure 2 , Figure 3 As shown.

[0209] Based on the established pumped storage capacity optimization model that considers continuous low output under extreme wind and solar conditions, the results of pumped storage capacity configuration are summarized in Table 4, using typical scenario example data.

[0210] Table 4. Typical Scenarios and Pumped Storage Capacity Configuration Results

[0211]

[0212] At the same time, the power output accumulation curves of each unit were obtained, such as Figure 4 As shown.

[0213] Figure 4 The data shows the output of each unit and the pumped-storage hydropower generation during four typical weeks. It can be seen that pumped-storage hydropower tends to pump water during periods of high wind and solar power generation, and generates power during periods of high system electricity demand and low wind and solar power output. This demonstrates that pumped-storage hydropower and wind and solar power output complement each other, smoothing out fluctuations in wind and solar power output and alleviating system peak-shaving pressure.

[0214] Based on the above typical scenario analysis, extreme scenarios are further introduced to analyze their impact on the construction demand of pumped storage units. The results of pumped storage capacity configuration considering extreme scenarios are shown in Table 5.

[0215] Table 5. Results of Pumped Storage Capacity Configuration Considering Extreme Scenarios

[0216]

[0217] In extreme scenarios, the low wind and solar power output places higher demands on the system's regulation capabilities and reliability. The above results indicate that, after introducing extreme scenarios and adding constraints, the investment demand for pumped storage power stations increases by 25% compared to considering only typical scenarios.

[0218] The impact of extreme supply guarantee scenarios on the model solution results is further analyzed from three aspects: green, economic, and safety, as shown in Table 6. The load shedding amount in extreme scenarios is not considered because the pumped storage capacity configuration scheme is consistent with the typical scenario, and only the load shedding amount obtained from the extreme scenario is optimized.

[0219] Table 6 Comparison of Solution Results with and without Considering Extreme Scenarios

[0220]

[0221] Considering extreme scenarios, the increased scale of pumped storage construction leads to a lower system curtailment rate and improved renewable energy integration. However, the overall economic efficiency decreases due to the increased total system cost. Simultaneously, the reduced load shedding under extreme power supply scenarios significantly enhances the system's safety in such conditions.

[0222] Meanwhile, the demand for pumped storage varies under different supply requirements. Table 7 was created to analyze the impact of different supply requirements on the scale of pumped storage construction.

[0223] Table 7 Pumped Storage Construction under Different Supply Guarantee Requirements

[0224]

[0225] As supply requirements increase, the system's load shedding rate decreases, while the demand for pumped storage capacity increases accordingly. This indicates that under high supply requirements, in order to reduce load shedding and improve the system's power supply reliability, the system needs to rely on more pumped storage capacity to provide flexible adjustment capabilities.

[0226] In addition, the power output distribution diagrams of various units, pumped storage, wind and solar power under extreme scenarios are studied, such as... Figure 5 As shown.

[0227] exist Figure 5 It can be observed that wind and solar power curtailment has significantly decreased, but at the same time, the output fluctuations of thermal power units have intensified. Furthermore, it shows that load shedding occurred at certain times, which is unacceptable under normal operating conditions, reflecting the severe challenges the system faces in coping with supply-demand imbalances under extreme supply guarantee scenarios.

[0228] Further analysis of the mechanism by which pumped storage participates in extreme water supply security was conducted, and graphs showing the changes in pumping output and real-time reservoir capacity were plotted. Figures 6-7 As shown.

[0229] from Figure 6 It can be seen that, to cope with extremely low power output scenarios, pumped storage hydroelectric power plants store energy in the upper reservoir by pumping water in advance before the low-output period arrives. When the low-output period arrives, the pumped storage units release the energy stored in the upper reservoir to ensure power supply. This process can also be seen from... Figure 7 This has been verified: before the low-output period, the reservoir capacity will reach a relatively high level in advance, providing sufficient reserves for subsequent energy release.

[0230] Therefore, to meet the power supply requirements under extremely low output scenarios, the model plans for more pumped storage capacity. Before the arrival of low output periods, the pumped storage units store energy by pumping water in advance; during low output periods, the stored energy is gradually released to achieve peak shaving and power supply guarantee functions on a weekly time scale, thereby effectively alleviating the power supply pressure under extremely continuous low output conditions.

[0231] If multi-year capacity optimization is to be implemented, the capacity planning period N needs to be changed. H Then, by configuring and adjusting the corresponding parameters, the solution can be optimized.

[0232] Example 3

[0233] like Figure 8 As shown, the pumped-storage energy system for multi-year capacity optimization considering continuous low-output wind and solar power provided by the present invention includes:

[0234] The objective function construction module constructs an objective function that comprehensively considers economic efficiency and the demand for renewable energy consumption.

[0235] The first constraint construction module, in combination with construction scale limitations and unit operation relationships, constrains investment decisions to ensure the feasibility of the scheme and constructs pumped storage construction constraints.

[0236] The second constraint construction module comprehensively considers various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits and power balance conditions to construct typical scenario constraints.

[0237] The third constraint construction module identifies and extracts low-output scenarios based on historical data, appropriately relaxes load shedding limits, and constructs extreme scenario constraints for safety verification.

[0238] The model building and solution module consists of an objective function, pumped storage construction constraints, typical scenario constraints, and extreme scenario constraints. It is a multi-year capacity optimization model for pumped storage considering continuous low output of wind and solar power. The model is optimized and solved using a solver with typical and extreme weekly scenarios as inputs, and finally obtains the optimized configuration scheme of pumped storage capacity.

[0239] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0240] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuous low power output, characterized in that, Comprising the following steps: Step one: build a target function considering economy and new energy consumption demand, including: With the goal of minimizing the comprehensive cost of the system, the target function includes: investment depreciation, coal consumption, start-stop, abandoned electricity and load shedding cost, and is weighted by the typical scenario weight and summed, and is converted into equal annual value; The specific mathematical expression of the target function is as follows: In the formula: refers to the typical scenario label; refers to the year label; refers to the time label; refers to the new energy base label; refers to the load node label; refers to the thermal power unit label; is the total number of typical scenarios; is the capacity planning year limit; T is the total duration of the calculation period, taking 168; is the total number of new energy bases; is the total number of load nodes; is the number of each thermal power unit; is the sampling probability of each typical scenario; is the conversion factor of the weekly operation cost to the annual operation cost; is the new energy curtailment penalty coefficient; is the load shedding penalty coefficient; is is the new energy predicted output of the system at the moment; is is the actual new energy output of the system at the moment; is the load shedding amount of each load node; is the slope of the approximation of the coal consumption function; is the coal consumption cost of the minimum technical output of each thermal power unit; is the actual output of each thermal power unit, is the minimum technical output of each thermal power unit; is the shutdown cost coefficient of the thermal power unit; is the start-up cost coefficient of the thermal power unit; is the 0-1 state variable of the thermal power unit; is the 0-1 shutdown action variable of the thermal power unit; is the 0-1 start-up action variable of the thermal power unit; is the discount factor of the year; is the investment cost of the pumped storage unit; In the formula: denotes the index of pumped storage power station; denotes pumped storage power station denotes the index of constant speed constant frequency pumped storage unit in pumped storage power station; denotes pumped storage power station denotes the index of variable speed constant frequency pumped storage unit in pumped storage power station; is the number of pumped storage power stations; , is the investment depreciation coefficient of each pumped storage unit; , is the construction state variable of each pumped storage unit; is the equivalent annual value coefficient of constant speed constant frequency pumped storage unit or variable speed constant frequency pumped storage unit , is the discount rate, which is 6%, is the operation life of constant speed constant frequency pumped storage unit or variable speed constant frequency pumped storage unit ; Step two: combined with the construction scale limit and the unit operation relationship, the investment decision is constrained to ensure the feasibility of the scheme, and the pumped storage construction constraint is built; Step three: considering various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits and power balance conditions, typical scenario constraints are built; Step four: based on historical data identification and extraction of low output scenarios, the load shedding limit is moderately relaxed, and extreme scenario constraints are built for safety check; Step five: the pumped storage multi-year capacity optimization model considering wind and light continuous low output is composed of the target function, pumped storage construction constraint, typical scenario constraint and extreme scenario constraint, with typical week scenarios and extreme week scenarios as input, and the solver is used for optimization solution, and finally the optimized configuration scheme of pumped storage capacity is obtained.

2. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 1, characterized in that, In step two, combined with the construction scale limit and the unit operation relationship, the investment decision is constrained to ensure the feasibility of the scheme, and the pumped storage construction constraint is built, including: annual maximum construction constraint, single power station maximum construction constraint, power station construction sequence constraint, power station unit construction sequence constraint, construction and unit output relationship constraint, construction action and state relationship constraint.

3. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 1, characterized in that, In step three, considering various power sources and pumped storage operation, reserve capacity, transmission line upper and lower limits and power balance conditions, typical scenario constraints are built, including: thermal power unit state constraint, thermal power unit operation constraint, minimum continuous start-stop time constraint of unit, thermal power unit reserve constraint, pumped storage unit constraint, new energy power operation constraint, load shedding constraint, power balance constraint, power flow safety constraint and total reserve constraint.

4. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 3, characterized in that, The pumped storage unit constraint models the constant speed constant frequency unit and the variable speed constant frequency unit respectively; The constant speed constant frequency pumped storage unit is modeled as: In the formulae: represents the actual power generation of the constant-speed pumped storage unit ; represents the upward reserve of the constant-speed pumped storage unit ; , represents the maximum and minimum power generation of the constant-speed pumped storage unit ; represents the power generation state variable of the constant-speed pumped storage unit ; represents the downward reserve of the constant-speed pumped storage unit ; represents the actual pumping power of the constant-speed pumped storage unit ; represents the constant-speed pumping power of the constant-speed pumped storage unit ; represents the pumping state variable of the constant-speed pumped storage unit ; At the same time, the variable speed constant frequency pumped storage unit is modeled as: In the formulae: denotes the actual power generation of the variable speed pump storage unit ; denotes the actual pumping power of the variable speed pump storage unit ; denotes the power generation state variable of the variable speed pump storage unit ; denotes the pumping state variable of the variable speed pump storage unit ; , denotes the maximum, minimum power generation of the variable speed pump storage unit ; , denotes the maximum, minimum pumping power of the variable speed pump storage unit ; denotes the upward reserve of the variable speed pump storage unit ; denotes the downward reserve of the variable speed pump storage unit ; Pumped storage cannot be in power generation state and pumped water state at the same time, that is In addition, the reservoir capacity balance constraint needs to be built: In the formulae: represents the real-time reservoir capacity of the pumped storage power station ; represents the initial reservoir capacity of the pumped storage power station ; represents the reservoir capacity of the pumped storage power station at the time t; ; and respectively represent the pumping and power generation efficiencies; and respectively represent the maximum and minimum reservoir capacities of the pumped storage power station .

5. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 3, characterized in that, In the new energy power operation constraint, the new energy output is less than the total resource quantity, and the new energy consumption rate limit is considered: Firstly, the power generation quantity needs to meet the constraint of being less than the resource quantity; wherein: represent the actual wind and solar power at the time of the typical scenario under consideration represent the predicted wind and solar power at the time of the typical scenario under consideration represent the actual wind and solar power at the time of the typical scenario under consideration represent the predicted wind and solar power at the time of the typical scenario under consideration At the same time, it is necessary to ensure that the new energy output is within a reasonable consumption range; In the formula: The new energy reasonable consumption rate is represented by 95%.

6. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 3, characterized in that, In the load shedding constraint, the total load shedding quantity of a single scenario is less than a certain threshold: In the formula: represents the upper limit of the total amount of cut load under a typical scenario .

7. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 4, characterized in that, The total reserve constraint considers the reserve capacity demand caused by load prediction error and new energy prediction error; In the formula: represents the upward reserve of thermal power units . is the spinning reserve rate, taking 5%; is the maximum load of the system under a typical scenario . represents the coefficient of the spinning reserve capacity increased to cope with the random fluctuations of new energy, taking 25%; represents the downward reserve of thermal power units .

8. The method for optimizing the multi-year capacity of a pumped storage plant considering wind and solar continuity low power output according to claim 4, characterized in that, In step four, the extreme scenario constraint further relaxes the load shedding limit based on the typical scenario constraint, and the extreme scenario variable is not included in the target function, but only in the constraint for extreme power supply safety check; Replace the variables in the constraints of various power sources and pumped storage with the variables in the extreme scenario, and introduce the extreme scenario constraint. For the reservoir capacity balance constraints (12)-(15):

9. A pumped storage multi-year capacity optimization system considering wind and solar continuous low power output, characterized in that, By analogy, the remaining typical scenario constraints are rewritten. Including: An objective function construction module constructs an objective function considering economy and new energy consumption demand, including: Taking the minimization of the system comprehensive cost as the target, the objective function includes: investment depreciation, coal consumption, start-stop, abandoned electricity and load shedding cost, and is weighted and summed according to the typical scene weight, and is equal to the annual value conversion; The specific mathematical expression of the objective function is as follows: In the formula: Refers to the typical scenario label; Refers to the year label; Refers to the time label; Refers to the new energy base label; Refers to the load node label; Refers to the thermal power unit label; The total number of typical scenarios; The capacity planning year limit; T is the total duration of the calculation period, taking 168; The total number of new energy bases; The total number of load nodes; The number of each thermal power unit; The sampling probability of each typical scenario; The conversion factor of the weekly operation cost to the annual operation cost; The new energy curtailment penalty coefficient; The load shedding penalty coefficient; The new energy predicted output of the system at the moment, The actual new energy output of the system at the moment; The load shedding amount of each load node; The slope of the approximation of the coal consumption function; The coal consumption cost of the minimum technical output of each thermal power unit; The actual output of each thermal power unit, The minimum technical output of each thermal power unit; The shutdown cost coefficient of the thermal power unit; The start-up cost coefficient of the thermal power unit; The 0-1 state variable of the thermal power unit; The 0-1 shutdown action variable of the thermal power unit; The 0-1 start-up action variable of the thermal power unit; The discount factor of the year; The investment cost of the pumped storage unit;​​ In the formula: denotes the index of pumped storage power station; denotes pumped storage power station denotes the index of constant speed constant frequency pumped storage unit in pumped storage power station; denotes pumped storage power station denotes the index of variable speed constant frequency pumped storage unit in pumped storage power station; is the number of pumped storage power stations; , is the investment depreciation coefficient of each pumped storage unit; , is the construction state variable of each pumped storage unit; is the equivalent annual value coefficient of constant speed constant frequency pumped storage unit or variable speed constant frequency pumped storage unit , is the discount rate, which is 6%, is the operation life of constant speed constant frequency pumped storage unit or variable speed constant frequency pumped storage unit ; A first constraint construction module combines the construction scale limit and the unit operation relationship, constrains the investment decision to ensure the feasibility of the scheme, constructs the pumped storage construction constraint; A second constraint construction module comprehensively considers various power sources and pumped storage operation, standby capacity, transmission line upper and lower limits and power balance conditions, and constructs a typical scene constraint; A third constraint construction module identifies and extracts low-power scenes based on historical data, moderately relaxes the load shedding limit, constructs an extreme scene constraint for safety check; The model construction and solution module is composed of the objective function, the pumped storage construction constraint, the typical scene constraint and the extreme scene constraint to form the pumped storage multi-year capacity optimization model considering wind and light continuous low output, takes the typical week scene and the extreme week scene as the input, uses the solver for optimization solution, and finally obtains the optimized configuration scheme of the pumped storage capacity.

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