Pumped storage unit capacity planning method and device

Abstract

The invention relates to the technical field of power system optimization and dispatching, in particular to a pumped storage unit capacity planning method and device, and the method comprises the steps: obtaining the effective power supply capability, maintenance space and maintenance margin of a power system, and calculating the unit maintenance satisfaction degree in a maintenance time period based on a plurality of unit maintenance constraints. On the basis, according to the effective power supply capacity, the maintenance space, the maintenance margin and the unit maintenance satisfaction degree, a joint optimization model of pumped storage capacity planning and water and electricity participating in the medium-and-long-term electric energy market is constructed. And then, converting a double-layer model problem of the joint optimization model into a single-layer problem by using KKT condition conversion, and further solving the joint optimization model to obtain a pumped storage unit capacity planning result of the power system. Therefore, the problem that the maintenance space utilization efficiency, the market benefit and the like are affected due to the fact that pumped storage capacity planning does not fully consider the influence of medium and long term transactions in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the technical field of power system optimization and dispatching, and in particular to a method and device for capacity planning of a pumped storage unit. Background Art

[0002] In related technologies, pumped storage, as a highly efficient regulating power source, plays the role of "reservoir" and "stabilizer" in the power system. By optimizing the capacity planning of pumped storage units, it is not only possible to smooth out the fluctuations in the output of new energy, but also to improve the efficiency of maintenance space utilization and provide a more flexible time window for unit maintenance.

[0003] However, in related technologies, pumped storage capacity planning often fails to fully consider the impact of medium- and long-term transactions, which are the core link of the electricity market, involving contract performance, market benefits and electricity supply and demand balance, and urgently need to be improved. Summary of the invention

[0004] The present application provides a method and device for capacity planning of a pumped storage unit to solve the problem in related technologies that pumped storage capacity planning does not fully consider the impact of medium- and long-term transactions, thereby affecting the utilization efficiency of maintenance space and market benefits.

[0005] The first aspect of the present application provides a method for capacity planning of a pumped-storage unit, comprising the following steps: obtaining the effective power supply capacity, maintenance space and maintenance margin of the power system; calculating the unit maintenance satisfaction within the maintenance period based on multiple unit maintenance constraints; constructing a joint optimization model for pumped storage capacity planning and hydropower participation in the medium- and long-term electricity energy market based on the effective power supply capacity, the maintenance space, the maintenance margin and the unit maintenance satisfaction; converting the double-layer model problem of the joint optimization model into a single-layer problem through KKT condition conversion to solve the joint optimization model and obtain the pumped-storage unit capacity planning result of the power system.

[0006] Through the above technical solution, the embodiment of the present application can obtain the effective power supply capacity, maintenance space and maintenance margin of the power system, combine the maintenance constraints of multiple units, and accurately calculate the satisfaction of the computer unit during the maintenance period, thereby constructing a joint optimization model that comprehensively considers pumped storage capacity planning and hydropower participation in the medium- and long-term electricity energy market. By converting the double-layer model problem into a single-layer problem, the solution process is significantly simplified, and the solution efficiency and accuracy of the model are improved. This method not only optimizes the operational flexibility and reliability of the power system, but also enhances the competitiveness of power generators in the market, which has important theoretical and practical significance.

[0007] Optionally, in one embodiment of the present application, the calculation formula for the unit maintenance satisfaction is:

[0008]

[0009] Among them, is the overall willingness level; is the willingness level for the best start time period of maintenance; is the willingness level for the worst start time period of maintenance.

[0010] Through the above technical solution, the embodiment of the present application can evaluate the satisfaction of the power generation with the maintenance arrangement by comparing the overall willingness level of the current time period with the willingness levels of the best and worst start time periods of maintenance, can flexibly reflect the maintenance preferences of power generators in different time periods, and ensure that while the maintenance arrangement meets the system requirements, the market benefits and satisfaction of power generators are maximized.

[0011] Optionally, in an embodiment of the present application, the objective function of the pumped storage capacity planning is:

[0012] max(λ 1 ·σ + λ 2 ·C MBC,total )

[0013]

[0014] Among them, S t is the maintenance space at time period t; T is the annual maintenance demand; C i is the single-unit installed capacity; D i is the number of days of maintenance required for a single unit per year; C MBC,i,t is the maintenance satisfaction degree (maintenance willingness level) of unit i at time period t; λ 1 , λ 2 are weight parameters for balancing the maintenance margin and maintenance satisfaction degree; σ is the maintenance margin; C MBC,total is the total maintenance satisfaction degree; δ jx,i,t is the maintenance state variable of hydroelectric unit i at time period t (1 represents maintenance, 0 represents normal operation).

[0015] Through the above technical solution, the embodiment of the present application can maximize the comprehensive benefits of the maintenance margin and maintenance satisfaction degree through the objective function of the pumped storage capacity planning to achieve the optimal dispatching of the power system, and balance the maintenance margin and maintenance satisfaction degree through the weight parameters, thereby improving the operation efficiency and market competitiveness of the generating units.

[0016] Optionally, in an embodiment of the present application, the objective function of the joint optimization model of the pumped storage capacity planning and the participation of hydropower in the medium- and long-term electric energy market is:

[0017]

[0018] Among them, R sc,tis the market benefit for period t; C yx,t is the operating cost of the hydropower and pumped-storage units; C pc,t is the penalty cost for insufficient contract performance; π sc,t and π pc,t are the market benefit and deviation cost coefficients respectively; is the medium- and long-term market contract power; ΔP pc,t is the contract deviation power.

[0019] Through the above technical solution, the embodiment of the present application can maximize the market benefit through the objective function of the joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term energy market, comprehensively considering the operating cost and the penalty cost for insufficient contract performance, and can effectively improve the competitiveness and economic benefits of power generators in the power market. At the same time, the model introduces the market benefit and deviation cost coefficients, enabling power generators to flexibly respond to market changes in a dynamic power market environment and ensuring the stability and reliability of power supply.

[0020] Optionally, in an embodiment of the present application, solving the joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electrical energy market includes: setting the mixed-integer linear programming problem of the model as a minimization problem; relaxing the integer constraint, transforming the mixed-integer linear programming problem into a linear programming problem, and finding the optimal solution of the original integer problem; obtaining the pumped-storage unit capacity planning result based on the optimal solution.

[0021] Through the above technical solution, the embodiment of the present application can simplify the solution process and improve the calculation efficiency by transforming the mixed-integer linear programming problem into a linear programming problem, and can quickly find the optimal solution of the original integer problem, thereby providing a scientific basis for the capacity planning of pumped-storage units.

[0022] An embodiment of the second aspect of the present application provides a pumped-storage unit capacity planning device, including: an acquisition module, configured to acquire the effective power supply capacity, maintenance space, and maintenance margin of the power system; a calculation module, configured to calculate the unit maintenance satisfaction during the maintenance period based on multiple unit maintenance constraints; a construction module, configured to construct a joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electrical energy market based on the effective power supply capacity, the maintenance space, the maintenance margin, and the unit maintenance satisfaction; a solution module, configured to transform the double-layer model problem of the joint optimization model into a single-layer problem through KKT condition conversion to solve the joint optimization model and obtain the pumped-storage unit capacity planning result of the power system.

[0023] Through the above technical solution, the embodiments of the present application can accurately calculate the satisfaction degree of the unit during the maintenance period by obtaining the effective power supply capacity, maintenance space and maintenance margin of the power system, and combining the maintenance constraints of multiple units, so as to construct a joint optimization model that comprehensively considers the pumped-storage capacity planning and the participation of hydropower in the medium- and long-term electric energy market. By transforming the two-layer model problem into a single-layer problem, the solution process is significantly simplified, and the solution efficiency and accuracy of the model are improved. This method not only optimizes the operation flexibility and reliability of the power system, but also enhances the competitiveness of power generators in the market, which has important theoretical and practical significance.

[0024] Optionally, in an embodiment of the present application, the calculation module includes: The calculation formula for the maintenance satisfaction degree of the unit is:

[0025]

[0026] Wherein, is the total willingness level; is the willingness level at the best start maintenance time period; is the willingness level at the worst start maintenance time period.

[0027] Through the above technical solution, the embodiments of the present application can evaluate the satisfaction degree of the power generation on the maintenance arrangement by comparing the total willingness level in the current time period with the willingness levels at the best and worst start maintenance time periods, which can flexibly reflect the maintenance preferences of power generators in different time periods, ensure that the maintenance arrangement meets the system requirements, and maximize the market benefits and satisfaction degree of power generators.

[0028] Optionally, in an embodiment of the present application, the construction module includes: The objective function of the pumped-storage capacity planning is:

[0029] max(λ 1 ·σ + λ 2 ·C MBC,total )

[0030]

[0031] Wherein, S t is the maintenance space at time period t; T is the annual maintenance demand; C i is the installed capacity of a single unit; D i is the number of days required for annual maintenance of a single unit; S MBC,i,t is the maintenance satisfaction degree (maintenance willingness level) of unit i at time period t; λ 1 , λ 2 are weight parameters for balancing the maintenance margin and the maintenance satisfaction degree; σ is the maintenance margin; C MBC,total is the total maintenance satisfaction degree; δ jx,i,tIt is the maintenance status variable of the hydropower unit i at time period t (1 represents maintenance, 0 represents normal operation).

[0032] Through the above technical solution, the embodiment of the present application can maximize the comprehensive benefits of maintenance margin and maintenance satisfaction through the objective function of pumped storage capacity planning to achieve the optimal dispatching of the power system, and balance the maintenance margin and maintenance satisfaction through the weight parameter, thereby improving the operation efficiency and market competitiveness of the generating units.

[0033] Optionally, in an embodiment of the present application, the construction module includes: The objective function of the joint optimization model of pumped storage capacity planning and hydropower participation in the medium and long-term electric energy market is as follows:

[0034]

[0035] where R sc,t is the market benefit at time period t; C yx,t is the operating cost of hydropower and pumped storage units; C pc,t is the penalty cost for insufficient contract performance; π sc,t , π pc,t are the market benefit and deviation cost coefficients respectively; is the medium and long-term market contract electricity quantity; ΔP pc,t is the contract deviation electricity quantity.

[0036] Through the above technical solution, the embodiment of the present application can maximize the market benefit through the objective function of the joint optimization model of pumped storage capacity planning and hydropower participation in the medium and long-term energy market, comprehensively considering the operating cost and the penalty cost for insufficient contract performance, and can effectively enhance the competitiveness and economic benefits of power generators in the power market. At the same time, the model introduces the market benefit and deviation cost coefficients, enabling power generators to flexibly respond to market changes in a dynamic power market environment and ensuring the stability and reliability of power supply.

[0037] Optionally, in an embodiment of the present application, the solving module includes: a setting unit for setting the mixed-integer linear programming problem of the model as a minimization problem; an optimization unit for relaxing the integer constraint, converting the mixed-integer linear programming problem into a linear programming problem, and finding the optimal solution of the original integer problem; a planning unit for obtaining the capacity planning result of the pumped storage unit based on the optimal solution.

[0038] Through the above technical solution, the embodiment of the present application can simplify the solving process and improve the calculation efficiency by converting the mixed-integer linear programming problem into a linear programming problem, and can quickly find the optimal solution of the original integer problem, thereby providing a scientific basis for the capacity planning of pumped storage units.

[0039] In a third aspect embodiment of the present application, an electronic device is provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the pumped-storage unit capacity planning method as described in the above embodiments.

[0040] In a fourth aspect embodiment of the present application, a computer-readable storage medium is provided, where the computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the above-mentioned pumped-storage unit capacity planning method.

[0041] In a fifth aspect embodiment of the present application, a computer program product is provided, including a computer program, which is used to implement the above-mentioned pumped-storage unit capacity planning method when the computer program is executed.

[0042] Embodiments of the present application can accurately calculate the effective power supply capacity, maintenance space, and maintenance margin of the power system, and construct a joint optimization model that comprehensively considers pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market in combination with the maintenance constraints of the units. By transforming the double-layer problem into a single-layer problem, this model significantly simplifies the solution process, improves efficiency and accuracy, thereby optimizing the operation flexibility and reliability of the power system, and enhancing the market competitiveness of power generators. At the same time, by evaluating the satisfaction degree of power generators with the maintenance arrangements, it flexibly reflects their maintenance preferences in different time periods, ensuring that the maintenance arrangements not only meet the system requirements but also maximize the market benefits of power generators. This method balances the weights of the two by maximizing the comprehensive objective function of the maintenance margin and satisfaction degree, further improving the operation efficiency and market competitiveness of the generating units. In addition, the model comprehensively considers the operating cost and the penalty cost for insufficient contract performance, enabling power generators to flexibly respond to changes in the dynamic power market environment and ensuring the stability and reliability of power supply. Finally, by transforming the mixed-integer linear programming problem into a linear programming problem, the solution process is simplified, and the optimal solution can be quickly found, providing a scientific basis for the capacity planning of pumped-storage units, which has important theoretical and practical significance.

[0043] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0045] Figure 1 It is a flowchart of a pumped-storage unit capacity planning method according to an embodiment of the present application;

[0046] Figure 2Flow chart of the solution principle of the model algorithm according to an embodiment of the present application;

[0047] Figure 3 Schematic diagram of the power generation and maintenance space of a power generator in a certain year according to a specific embodiment of the present application;

[0048] Figure 4 Schematic diagram of the structure of a pumped-storage unit capacity planning device provided according to an embodiment of the present application;

[0049] Figure 5 Schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. Detailed implementation manners

[0050] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, but should not be construed as limiting the present application.

[0051] The pumped-storage unit capacity planning method and device according to the embodiments of the present application will be described below with reference to the accompanying drawings. In view of the problem in the related art mentioned in the above background art that the pumped-storage capacity planning does not fully consider the impact of medium- and long-term transactions, thereby affecting the utilization efficiency of the maintenance space and market benefits, etc., the present application provides a pumped-storage unit capacity planning method. In this method, the effective power supply capacity, maintenance space, and maintenance margin of the power system can be obtained, and combined with the maintenance constraints of multiple units, the satisfaction of the units during the maintenance period can be accurately calculated, so as to construct a joint optimization model that comprehensively considers the pumped-storage capacity planning and the participation of hydropower in the medium- and long-term electric energy market. By transforming the double-layer model problem into a single-layer problem, the solution process is significantly simplified, and the solution efficiency and accuracy of the model are improved. This method not only optimizes the operation flexibility and reliability of the power system, but also enhances the competitiveness of power generators in the market, and has important theoretical and practical significance. Thus, the problem in the related art that the pumped-storage capacity planning does not fully consider the impact of medium- and long-term transactions, thereby affecting the utilization efficiency of the maintenance space and market benefits, etc., is solved.

[0052] Specifically, Figure 1 Schematic flow chart of a pumped-storage unit capacity planning method provided by an embodiment of the present application.

[0053] As Figure 1 shown, the pumped-storage unit capacity planning method includes the following steps:

[0054] In step S101, the effective power supply capacity, maintenance space, and maintenance margin of the power system are obtained.

[0055] Among them, effective power supply capacity refers to the maximum output power that the power system or power generation facility can stably provide after taking into account factors such as system reliability, load fluctuations, dispatch response, and equipment availability. It not only reflects the rated power or maximum power of the equipment, but is also closely related to the system's ability to respond to load demand fluctuations, faults, or other external disturbances. The core of effective power supply capacity is to prevent the occurrence of a balance gap, that is, the phenomenon of insufficient power supply that may occur when the power supply capacity is insufficient to meet the load demand. The power system needs to have sufficient regulation capabilities to ensure that when the load demand exceeds expectations or an emergency occurs, it can avoid insufficient power supply or power supply below load demand by activating standby units or adjusting output power, thereby maintaining the stable operation of the system and the continuity of power supply.

[0056] Specifically, the method for calculating the effective power supply capacity of a power supply includes the following two aspects:

[0057] 1) Hydropower

[0058] Because the power generation of hydropower units is greatly affected by the seasons (flood season, flat season and dry season), the daily fluctuation is not large. During the flood season, the water volume is sufficient, the power generation capacity is strong, and the power supply is sufficient; during the flat season, the water volume is moderate, the power generation is stable, but there may be fluctuations; and during the dry season, the water volume is insufficient, the power generation decreases, and it may not be able to meet the demand, and it needs to rely on other energy sources to supplement. The calculation of the effective power supply capacity of hydropower is:

[0059]

[0060] Among them, R HC The growth rate of hydropower installed capacity at any time compared with the same period in the past; is the maximum hydropower generating capacity in the same period in the past; P H (t 0 ) is determined on a quarterly basis.

[0061] 2) New energy

[0062] The output of renewable energy is greatly affected by natural conditions, and is intermittent and volatile. It cannot guarantee stable and continuous power generation. Therefore, its power generation is greatly affected by weather, season and time period. The effective power generation capacity of renewable energy is usually estimated by evaluating factors including but not limited to its available capacity, meteorological data, historical power generation data, etc., mainly considering the dispatchability and stability of the system. The effective power generation capacity is generally measured by availability or effective utilization hours, reflecting the actual contribution capacity of renewable energy power generation under specific conditions. Based on the statistical data of many years, the 24-hour P N100％ (t 0 ), in view of the peak and valley characteristics of the load within the day, in order to simplify the analysis, the P N100％ (t 0) As a reference standard. That is:

[0063]

[0064] Among them, R NC represents the growth rate of the new energy installed capacity compared with the same period at any time; P N100％ (t 0 ) represents the guaranteed output obtained by statistical analysis of historical data.

[0065] The maintenance space refers to the available capacity or spare capacity reserved for equipment maintenance, repair or restoration in a power system or power generation facility. It usually refers to the redundant power generation capacity reserved to ensure the safety of equipment and the stability of the system during normal operation of the generator set or power system, so as not to affect the power supply capacity of the system during equipment failure or maintenance. The maintenance space can be provided by standby units, peaking units or flexible dispatching mechanisms to ensure that the system can still meet the load demand during the maintenance or failure of some equipment, and avoid power supply interruption or overload.

[0066] Based on the effective power supply capacity, it is necessary to ensure that the effective power supply capacity at any time during the maintenance period is greater than the load and the necessary reserve capacity.

[0067] That is

[0068]

[0069] Among them, is the effective power supply capacity of the nuclear power unit; is the actual effective power supply capacity of each power source.

[0070] Then the power generation maintenance space S is:

[0071]

[0072] Among them, is the maximum effective power generation capacity calculated according to the basic parameters without considering maintenance; min{P ∑ (t)} is the minimum requirement for the effective power supply capacity.

[0073] The actual measurement method of the maintenance space includes three aspects, as follows:

[0074] 1) Daily power generation

[0075] From the definition of effective power generation capacity, we have:

[0076]

[0077] The daily power generation maintenance space S d is:

[0078]

[0079] 2) Annual power generation

[0080] The annual power generation maintenance space is the accumulation of the daily power generation maintenance space within a year, that is:

[0081]

[0082] 3) Reserve for backup

[0083] Due to the change of daily load, the daily maintenance space will also be affected and fluctuate greatly. To cope with this situation, it is necessary to reserve some backup, that is:

[0084] R(t) = R 事故 (t) + R 检修 (t)

[0085] The maintenance margin refers to the additional available power generation capacity in the power system to ensure that the system can still meet the load demand during the maintenance period of the generating unit. It is the redundant capacity set to ensure the stable operation of the system during a certain maintenance or repair period. The power generation maintenance margin is usually expressed as a percentage of the available capacity, reflecting the backup capacity required for the system to ensure reliable power supply during planned maintenance, emergency fault repair or other maintenance operations. This margin can be ensured through the coordinated operation of multiple units, the commissioning of standby units or other dispatching strategies to avoid power supply shortages or grid instability caused by maintenance. The calculation formula of the maintenance margin is:

[0086] v = (S - T) / T × 100%

[0087] Among them, T is the power generation maintenance demand (single unit capacity multiplied by the maintenance days).

[0088] The embodiments of the present application can ensure the stable operation of the power system from multiple dimensions and provide a data basis for the scientific dispatching and efficient planning of the power system.

[0089] In step S102, the maintenance satisfaction of the generating units during the maintenance period is calculated based on the maintenance constraints of multiple units.

[0090] Due to the differences in electricity prices and unit operating conditions in different periods, the preferences of power generators for arranging maintenance or keeping the units running in each period will be different. Therefore, the concept of C MBC is introduced to represent the willingness intensity of power generators for unit maintenance or operation in a specific period. C MBC If it is positive, it means that the power generator wants to carry out unit maintenance in this period, and the larger the value, the higher the expectation; if C MBC is negative, it means that the power generator wants to operate in this period, and the larger the absolute value, the higher the expectation.

[0091] In most embodiments, the following two constraints should be considered during the unit maintenance:

[0092] 1) Unit maintenance continuity constraint: The unit maintenance should be completed within the specified duration without interruption, that is:

[0093] x(t)-x(t - 1)≤x(t + D - 1)

[0094] 2) Unit maintenance duration constraint: The unit must complete the maintenance task within the specified time, that is

[0095]

[0096] where N T is the number of maintenance time periods.

[0097] Based on this, the total willingness level can be obtained That is

[0098]

[0099] where t is the starting time period of maintenance.

[0100] From the above calculations, the optimal starting maintenance time period t best is:

[0101]

[0102] The worst starting maintenance time period t worst is:

[0103]

[0104] Thus, the calculation formula for the unit maintenance satisfaction degree is:

[0105]

[0106] where is the total willingness level; is the willingness level of the optimal starting maintenance time period; is the willingness level of the worst starting maintenance time period. If V SD (t) is positive, it means that the power generator hopes to maintain the unit within the time period, between 0 and 1, and the larger the value, the higher the satisfaction degree for the maintenance in this time period. V SD (t best ) = 1; if V SD is negative, it means that the power generator hopes the unit to operate in this time period, between 0 and -1, and the larger the absolute value, the more it hopes the unit to operate. V SD (t worst ) = -1; if V SDIf it is 0, it means that the sensitivity to this period is low. The analysis of the above maintenance satisfaction ensures the integrity of the following optimization model.

[0107] The embodiment of the present application can measure the willingness intensity of the power generator to maintain or operate the unit in different periods, taking into account the impact of the differences in electricity prices and unit operating conditions in different periods on the decision-making of the power generator. The setting of the unit maintenance continuity constraint and the duration constraint makes the maintenance plan more reasonable and operable, ensuring the smooth progress of the unit maintenance work. Based on these constraints, the total willingness level, the best and worst start maintenance periods are calculated, and then the calculation formula of the unit maintenance satisfaction is obtained, which can quantify the satisfaction of the power generator with different maintenance periods. This not only helps the power generator to reasonably arrange the maintenance plan according to its own interests and system requirements, but also ensures the integrity of the subsequent optimization model, providing strong support for constructing a more scientific and practical power system optimal dispatching model.

[0108] In step S103, based on the effective power supply capacity, maintenance space, maintenance margin and unit maintenance satisfaction, a joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market is constructed.

[0109] The joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market is a two-layer model, where the two-layer model includes an upper-layer model and a lower-layer model.

[0110] The upper-layer model is a pumped-storage unit capacity planning model. On the basis of ensuring the satisfaction of maintenance requirements, the maintenance margin is maximized. The calculation methods of the maintenance space and the maintenance margin are given in step S101. At the same time, the capacity of the pumped-storage unit is planned, and the objective function is:

[0111] max(λ 1 ·σ + λ 2 ·C MBC,total )

[0112]

[0113] Among them, S t is the maintenance space in period t; T is the annual maintenance requirement; C i is the single-unit installed capacity; D i is the number of days required for single-unit maintenance per year; C MBC,i,t is the maintenance satisfaction (maintenance willingness level) of unit i in period t; λ 1 , λ 2 are the weight parameters for balancing the maintenance margin and the maintenance satisfaction; σ is the maintenance margin; C MBC,total is the total maintenance satisfaction; δ jx,i,t is the maintenance status variable of hydropower unit i in period t (1 represents maintenance, 0 represents normal operation).

[0114] Specifically, the constraint conditions of the objective function include:

[0115] 1) Power supply gap supplement constraint (when the maintenance space is less than the maintenance demand):

[0116] ΔS t = max(0, T t - S t )

[0117] 2) Annual maintenance demand constraint:

[0118] The maintenance time of each hydropower unit shall not exceed the specified annual maintenance days.

[0119]

[0120] Among them, δ jx,i,t δ jx,i,t is the maintenance status variable of hydropower unit i at time period t (1 represents maintenance, 0 represents normal operation).

[0121] 3) Maintenance space meets demand constraint:

[0122] The maintenance space S of the system at each time period t must meet the total demand of the units under maintenance

[0123]

[0124] 4) Pumped-storage unit capacity constraint:

[0125]

[0126] Among them, P CX,t is the power of the pumped-storage at time period t; E CX,t is the capacity of the pumped-storage at time period t.

[0127] 5) Pumped-storage unit investment cost constraint:

[0128]

[0129] Among them, α and β are the investment cost coefficients per unit capacity.

[0130] The lower-layer model is the optimal scheduling of hydropower and pumped-storage participating in the medium- and long-term market. On the premise of the given pumped-storage unit capacity planning results, the medium- and long-term market benefits are maximized, and the objective function is:

[0131]

[0132] Among them, R sc,t is the market benefit at time period t; C yx,tis the operating cost of hydropower and pumped storage units; C pc,t is the penalty cost for underperformance of the contract; sc,t , π pc,t are the market benefit and deviation cost coefficients respectively; is the mid- to long-term market contract electricity; ΔP pc,t The contract deviation quantity.

[0133] Specifically, the constraints include:

[0134] 1) Total power supply capacity constraints:

[0135] The total output of hydropower and pumped storage must meet the contractual electricity demand

[0136]

[0137] 2) Market performance deviation:

[0138]

[0139] 3) Generator output limit constraints:

[0140] The output of hydropower units is constrained by installed capacity and maintenance status:

[0141]

[0142] 4) Satisfaction weight constraint:

[0143]

[0144] In the embodiment of the present application, on the one hand, the upper model plans the capacity of the pumped-storage unit with the goal of maximizing the maintenance margin and taking into account the maintenance satisfaction, comprehensively considering the constraints of power supply gap supplementation, annual maintenance demand, maintenance space to meet the demand, unit capacity and investment cost, etc., to ensure the reliability of the power system during equipment maintenance, rationally plan the resources of the pumped-storage unit, balance the maintenance demand and economic benefits, and avoid over-investment. On the other hand, the lower model maximizes the medium- and long-term market benefits based on the given upper-level capacity planning results. Its constraints include total power supply capacity, market performance deviation, generator unit output limit and satisfaction weight, etc., to ensure that hydropower and pumped-storage units can effectively control costs and improve market competitiveness while meeting the market power supply demand, and take into account the maintenance willingness of power generators. The upper and lower models cooperate with each other to comprehensively optimize the capacity planning of pumped-storage units and the dispatch of hydropower in the medium- and long-term electricity market, realize the unity of power system operation reliability, economy and market benefits, and improve the comprehensive operation level of the power system.

[0145] In step S104, the bilevel model problem of the joint optimization model is transformed into a single-level problem through KKT condition transformation to solve the joint optimization model, and the capacity planning result of the pumped-storage units in the power system is obtained.

[0146] For convenience of explanation, the upper and lower level objective functions in step S103 are represented by Z up and Z low respectively. The lower-level model is embedded into the upper-level model, and combined with the lower-level optimization result, the upper-level objective function is adjusted. The original upper-level objective function is modified as:

[0147] max Z up = α·σ·(C PL ) + β·Z low (C PL )

[0148] where C PL is the pumped-storage capacity; Z low (C PL ) is explicitly represented by the solution of the lower-level model and embedded into the upper-level optimization.

[0149] Furthermore, for linearization processing, if the embedded objective function is non-linear, the following methods can be used for linearization:

[0150] 1) Piecewise linear optimization: The non-linear part Z low (C PL ) is divided into several linear segments:

[0151]

[0152] where f i (C PL ) is a piecewise function and w i is the weight.

[0153] 2) Introduction of auxiliary variables: For the non-linear terms R sc,t , C yx,t , new variables y t , z t are introduced, and the optimization problem is transformed into:

[0154] y t = R sc,t

[0155] z t = C yx,t

[0156] And linearization constraints are added.

[0157] 3) Formation of a single-level optimization model: After adjustment, the objective function and constraints are combined into a single-level optimization problem:

[0158]

[0159] Further, solve the model. It should be understood that the objective function of a mixed-integer programming problem is usually linear, that is, it is composed of the product of a coefficient vector c and a decision variable x. The form of the objective function is:

[0160] min c T x

[0161] where c = [c 1 , c 2 ,..., c n T is the coefficient vector of the objective function, x = [x 1 , x 2 ,..., x n T is the decision variable vector, and the objective function can be to solve for the minimum benefit, maximum profit, shortest path, etc.

[0162] Specifically, the decision variable x can be divided into two parts: x c ∈R n represents the continuous variable part; x I ∈Z m represents the integer variable part, where m is the number of integer variables. The constraint conditions are:

[0163] Ax ≤ b

[0164] where A ∈ R p×n is the constraint matrix, b ∈ R p is the constraint vector, representing the right-hand constant of each constraint. There are also integer constraints, non-negativity constraints, etc.

[0165] Optionally, in an embodiment of the present application, solving the joint optimization model of pumped storage capacity planning and hydropower participation in the medium- and long-term electric energy market includes: setting the mixed-integer linear programming problem of the model as a minimization problem; relaxing the integer constraints, transforming the mixed-integer linear programming problem into a linear programming problem, and finding the optimal solution of the original integer problem; obtaining the pumped storage unit capacity planning result based on the optimal solution.

[0166] In the specific solution process, the branch and cut method can be used. The branch and cut method is a hybrid algorithm that combines the branch and bound method and the cutting plane method. In the traditional branch and bound method, when solving each sub-problem, the lower bound of the sub-problem is estimated through linear relaxation, and then pruning is performed based on these lower bounds. The cutting plane method excludes non-integer solutions in the relaxation problem by introducing new constraints, thereby reducing the search space and improving the solution efficiency. The algorithm principle is as Figure 2 shown, and specifically can be understood as:

[0167] ​​1) Problem: Given a mixed-integer linear programming problem P MIP , set as a minimization problem, where some variable constraints are integer constraints, for example, the decision variable xx must be an integer 0, 1, 2.

[0168] 2) Bounding: Relax the integer constraints and transform the mixed-integer linear programming problem P MIP into a linear programming problem For example, if the decision variable x must be an integer 0, 1, 2, after relaxation, it becomes 0.0 ≤ x ≤ 2.0; solve it using the linear programming algorithm Since the solution space of P MIP is a subset of the solution space, then the optimal solution provides a lower bound for the optimal solution of P MIP ; If the obtained optimal solution satisfies one of the following two conditions, the optimal solution of the original integer problem is found; The optimal solution satisfies p MIP all integer constraints; any feasible solution of p MIP provides an upper bound for the optimal solution; if the upper bound is equal to the lower bound, the optimal solution of P MIP is found.

[0169] 3) Branching: If the above optimal solution does not satisfy all integer constraints, then there is a situation where the value of an integer variable in the obtained solution is non-integer; select a variable from the variables that do not satisfy the integer constraints and create two branch nodes (when the node search tree is non-empty).

[0170] 4) Node selection: Select a target branch node from the search tree.

[0171] 5) Linear programming re-optimization: Similar to the method of setting problems in the above steps, relax the node integer problem to a linear programming problem and solve the relaxed linear programming problem using the linear programming solution algorithm.

[0172] 6) Bounding: Prune the nodes according to the solution result of the linear programming problem. If the relaxed linear programming problem has no solution, prune the node; if the optimal solution of the relaxed linear programming problem exceeds the current optimal solution upper bound, prune the node; if the optimal solution of the relaxed linear programming problem does not exceed the current optimal solution upper bound and the current solution is a feasible solution of the integer problem, update the current upper bound and the current optimal solution.

[0173] 7) If the node cannot be pruned, further branch, create nodes and add them to the search tree.

[0174] The following uses a specific embodiment to illustrate the beneficial effects that the present application can achieve. Specifically, as Figure 3 shown, Figure 3 it is the annual maintenance space considering peak summer load, that is, no maintenance during winter and summer.

[0175] To verify the effectiveness of the invention, the following settings will be simulated: the analysis of the maintenance space margin for three hydropower stations in a river basin under different load scenarios. The maximum installed capacities of the three hydropower stations are 800MW, 1200MW, and 600MW respectively; the load scenarios are high, medium, and low load scenarios; the maintenance time for each unit is 30 - 60 days; the weights of maintenance satisfaction are set to 0.6 and 0.4 respectively. The performance comparisons under different load scenarios are shown in Table 1.

[0176] Table 1

[0177]

[0178] Through the comparative analysis of high, medium, and low load scenarios, it can be seen that the optimization method proposed in this application can significantly improve the maintenance space and margin under different load levels, especially showing higher flexibility in the low load scenario; at the same time, by introducing the comprehensive trade-off of maintenance satisfaction and market benefits, it not only ensures the reliability of system power supply but also improves the market competitiveness and benefit optimization ability of power generators, demonstrating the potential and advantages for wide application in actual power systems.

[0179] The embodiment of this application can transform the two-layer problem of the joint optimization model into a single-layer problem, reducing the complexity of model solving, making the originally complex joint optimization problem of pumped-storage unit capacity planning and hydropower participation in the medium- and long-term electric energy market easier to handle, and improving the solving efficiency. In the transformation process, for possible non-linear problems, piecewise linear optimization and the introduction of auxiliary variables and other linearization means are adopted to ensure that the model can adapt to a wider range of actual situations and enhance the applicability of the model. Secondly, the branch-and-cut method is used to solve the mixed-integer linear programming problem, combining the advantages of the branch-and-bound method and the cutting plane method. Through steps such as relaxing integer constraints, bounding, branching, node selection, and re-optimization, the search space is effectively reduced, and the optimal solution of the original integer problem can be quickly found, improving the solving accuracy.

[0180] According to the pumped-storage unit capacity planning method proposed in the embodiment of this application, by obtaining the effective power supply capacity, maintenance space, and margin of the power system, and combining the maintenance constraints of multiple units, the satisfaction of the units during the maintenance period can be accurately calculated, thereby constructing a joint optimization model that comprehensively considers pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market. By transforming the two-layer model problem into a single-layer problem, the solving process is significantly simplified, and the solving efficiency and accuracy of the model are improved. This method not only optimizes the operation flexibility and reliability of the power system but also enhances the competitiveness of power generators in the market, having important theoretical and practical significance.

[0181] Next, a pumped-storage unit capacity planning device according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0182] Figure 4 It is a block diagram of the pumped-storage unit capacity planning device according to an embodiment of the present application.

[0183] As Figure 4 shown, the pumped-storage unit capacity planning device 10 includes: an acquisition module 100, a calculation module 200, a construction module 300, and a solution module 400.

[0184] Specifically, the acquisition module 100 is configured to acquire the effective power supply capacity, maintenance space, and maintenance margin of the power system.

[0185] The calculation module 200 is configured to calculate the unit maintenance satisfaction during the maintenance period based on multiple unit maintenance constraints.

[0186] The construction module 300 is configured to construct a joint optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market based on the effective power supply capacity, maintenance space, maintenance margin, and unit maintenance satisfaction.

[0187] The solution module 400 is configured to convert the double-layer model problem of the joint optimization model into a single-layer problem through KKT condition transformation to solve the joint optimization model and obtain the pumped-storage unit capacity planning result of the power system.

[0188] Optionally, in an embodiment of the present application, the calculation module 200 includes: The calculation formula for unit maintenance satisfaction is:

[0189]

[0190] Where is the total willingness level; is the willingness level at the best start maintenance time period; is the willingness level at the worst start maintenance time period.

[0191] Optionally, in an embodiment of the present application, the construction module 300 includes: The objective function of pumped-storage capacity planning is:

[0192] max(λ 1 ·σ + λ 2 ·C MBC,total )

[0193]

[0194] Where S t is the maintenance space at time period t; T is the annual maintenance demand; C i is the single-unit installed capacity; D iis the number of days required for annual maintenance of a single unit; C MBC,i,t is the maintenance satisfaction (maintenance willingness level) of unit i in period t; λ 1 and λ 2 are the weight parameters for balancing the maintenance margin and maintenance satisfaction; σ is the maintenance margin; C MBC,total is the total maintenance satisfaction; δ jx,i,t is the maintenance status variable of hydropower unit i in period t (1 represents maintenance, 0 represents normal operation).

[0195] Optionally, in an embodiment of the present application, the construction module 300 includes: The objective function of the combined optimization model of pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market is:

[0196]

[0197] where R sc,t is the market benefit in period t; C yx,t is the operating cost of hydropower and pumped-storage units; C pc,t is the penalty cost for insufficient contract performance; π sc,t and π pc,t are the market benefit and deviation cost coefficients respectively; is the medium- and long-term market contract electricity quantity; ΔP pc,t is the contract deviation electricity quantity.

[0198] Optionally, in an embodiment of the present application, the solving module 400 includes: a setting unit, an optimization unit, and a planning unit.

[0199] Among them, the setting unit is used to set the mixed-integer linear programming problem of the model as a minimization problem.

[0200] The optimization unit is used to relax the integer constraint, transform the mixed-integer linear programming problem into a linear programming problem, and find the optimal solution of the original integer problem.

[0201] The planning unit is used to obtain the pumped-storage unit capacity planning result based on the optimal solution.

[0202] It should be noted that the foregoing explanation of the embodiment of the pumped-storage unit capacity planning method also applies to the pumped-storage unit capacity planning device of this embodiment, and will not be repeated here.

[0203] The pumped-storage unit capacity planning device proposed according to the embodiments of the present application can accurately calculate the satisfaction of the unit during the maintenance period by obtaining the effective power supply capacity, maintenance space, and maintenance margin of the power system, and combining the maintenance constraints of multiple units, so as to construct a joint optimization model that comprehensively considers pumped-storage capacity planning and hydropower participation in the medium- and long-term electric energy market. By transforming the two-layer model problem into a single-layer problem, the solution process is significantly simplified, and the solution efficiency and accuracy of the model are improved. This method not only optimizes the operation flexibility and reliability of the power system, but also enhances the competitiveness of power generators in the market, and has important theoretical and practical significance.

[0204] Figure 5 The structural schematic diagram of the electronic device provided by the embodiment of the present application. The electronic device may include:

[0205] A memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.

[0206] When the processor 502 executes the program, it implements the pumped-storage unit capacity planning method provided in the above embodiment.

[0207] Further, the electronic device further includes:

[0208] A communication interface 503 for communication between the memory 501 and the processor 502.

[0209] The memory 501 is used to store a computer program executable on the processor 502.

[0210] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0211] If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 can be interconnected through a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 5 only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0212] Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a single chip, the memory 501, the processor 502, and the communication interface 503 can communicate with each other through an internal interface.

[0213] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0214] The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned pumped-storage unit capacity planning method is implemented.

[0215] The embodiments of the present application also provide a computer program product, including a computer program, and when the computer program is executed, it is used to implement the above-mentioned pumped-storage unit capacity planning method.

[0216] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0217] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0218] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of this application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of this application pertain.

[0219] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing a logical function, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion with one or N wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0220] It should be understood that the various parts of this application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0221] Those of ordinary skill in the art can understand that all or part of the steps carried out in the method of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0222] In addition, in each of the embodiments of the present application, the functional units can be integrated into one processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0223] The storage medium mentioned above can be a read-only memory, a magnetic disk, an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for capacity planning of a pumped storage unit, characterized in that: The following steps are involved: Obtain the effective power supply capacity, maintenance space and maintenance margin of the power system; Calculate the unit maintenance satisfaction within the maintenance period based on multiple unit maintenance constraints; Based on the effective power supply capacity, the maintenance space, the maintenance margin and the unit maintenance satisfaction, a joint optimization model of pumped storage capacity planning and hydropower participation in the medium- and long-term electricity energy market is constructed; The double-layer model problem of the joint optimization model is transformed into a single-layer problem through KKT condition conversion to solve the joint optimization model and obtain the capacity planning result of the pumped storage unit of the power system.

2. The method according to claim 1, characterized in that The calculation formula for the unit maintenance satisfaction is: in, is the overall willingness level; The willingness level for the best time period to start maintenance; The willingness level for the worst maintenance start time period.

3. The method according to claim 1, characterized in that The objective function of the pumped storage capacity planning is: mx(λ1·σ+λ2·C MBC,total ) Among them, S t is the maintenance space in time period t; T is the annual maintenance demand; C i is the installed capacity of a single machine; D i C is the number of maintenance days required for a single machine per year; MBC,i,t is the maintenance satisfaction (maintenance willingness level) of unit i in period t; λ1 and λ2 are weight parameters for balancing maintenance margin and maintenance satisfaction; σ is the maintenance margin; C MBC,total is the total maintenance satisfaction; jx,i,t is the maintenance state variable of hydropower unit i in period t (1 represents maintenance, 0 represents normal operation).

4. The method according to claim 1, characterized in that: The objective function of the joint optimization model of pumped storage capacity planning and hydropower participation in the medium- and long-term electricity energy market is: Among them, R sc,t is the market efficiency in period t; C yx,t is the operating cost of hydropower and pumped storage units; C pc,t is the penalty cost for underperformance of the contract; sc,t , π pc,t are the market benefit and deviation cost coefficients respectively; is the mid- to long-term market contract electricity; ΔP pc,t The contract deviation quantity.

5. The method according to claim 1, characterized in that The method for solving the joint optimization model of pumped storage capacity planning and hydropower participation in the medium- and long-term electricity energy market includes: The mixed integer linear programming problem of the model is formulated as a minimization problem; Relaxing the integer constraints, transforming the mixed integer linear programming problem into a linear programming problem, and finding the optimal solution of the original integer problem; The capacity planning result of the pumped storage unit is obtained based on the optimal solution.

6. A pumped storage unit capacity planning device, characterized in that: include: An acquisition module, used to obtain the effective power supply capacity, maintenance space and maintenance margin of the power system; A calculation module, used for calculating the unit maintenance satisfaction within the maintenance period based on multiple unit maintenance constraints; A construction module is used to construct a joint optimization model of pumped storage capacity planning and hydropower participation in the medium- and long-term electric energy market based on the effective power supply capacity, the maintenance space, the maintenance margin and the unit maintenance satisfaction; A solution module is used to transform the double-layer model problem of the joint optimization model into a single-layer problem through KKT condition conversion, so as to solve the joint optimization model and obtain the capacity planning result of the pumped storage unit of the power system.

7. The device according to claim 6, characterized in that The calculation module includes: the calculation formula of the unit maintenance satisfaction is: in, is the overall willingness level; The willingness level for the best time period to start maintenance; The willingness level for the worst maintenance start time period.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for capacity planning of a pumped storage unit as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the pumped storage unit capacity planning method as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the pumped storage unit capacity planning method according to any one of claims 1 to 5.

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