Method and system for quantitative evaluation of pumped storage peak regulation effect

Abstract

The invention discloses a method and a system for quantitative evaluation of a pumped storage peak regulation effect, and belongs to the technical field of optimal dispatching operation of a new energy power system. The method comprises the following steps: aiming at a new energy power system, according to actual operation characteristics of a pumped storage power station, constructing a pumped storage power supply operation mathematical model; aiming at the new energy power system, according to the pumped storage power supply and the system operation constraint, constructing a new energy power system operation mathematical model containing the pumped storage power supply; based on a time sequence production simulation technology, according to the pumped storage power supply operation mathematical model and the new energy power system operation mathematical model, constructing an operation optimization model for the new energy power system, and solving the operation optimization model; and outputting a quantitative evaluation result of the pumped storage peak regulation effect of the new energy power system. The operation effect of the pumped storage supporting system can be evaluated from the multi-dimensional angles of the peak regulation demand side, the peak regulation supply side and the system side.

Description

Technical Field

[0001] The present invention relates to the technical field of optimized dispatching and operation of new energy power systems, and more specifically, to a method and system for quantitatively evaluating the peak-shaving effect of pumped storage. Background Art

[0002] In the context of building a new power system in my country, the scale of new energy installed capacity continues to maintain rapid development, and the proportion of power generation continues to increase. The randomness, volatility and intermittent characteristics of its output are further highlighted. Therefore, the peak load regulation pressure of conventional power sources is relatively large, and the system balance and high-level consumption of new energy are difficult. In order to adapt to the needs of new power system construction and large-scale high-proportion new energy development, pumped storage has developed rapidly as a flexible and fast regulating power source.

[0003] At present, my country's peak-shaving resources are mainly conventional power sources such as coal-fired power. With the rapid increase in the proportion of new energy power generation, the progress of conventional coal-fired power flexibility transformation is relatively slow, so the problem of peak-shaving resource supply structure is prominent. Pumped storage, as a regulating and energy storage power source with mature technology, reliable operation and economy, plays a supporting role in two-way peak-shaving for the power system, and has outstanding potential to participate in system peak-shaving with coal-fired power units. The traditional pumped storage operation simulation model method is mainly a time series optimization simulation on a medium- and long-term time scale, lacks consideration of the daily operation law of pumped storage power stations, and the simulation results are quite different from the dispatch plan. At the same time, there is no evaluation system for evaluating the peak-shaving effect of pumped storage power stations, so it is difficult to quantify and carry out effective evaluation of the peak-shaving efficiency of pumped storage power stations.

[0004] Moreover, there are the following deficiencies in the quantitative evaluation of the peak-shaving effect of the pumped-storage support system: First, in actual operation, dispatching agencies often arrange the daily plan curves of pumped-storage power stations in various places in fixed modes such as "one pumping and one generating" or "one pumping and two generating", while the operation optimization model for pumped storage usually does not take this actual operation law into consideration, resulting in a large deviation between the pumped-storage operation results and the actual output, which is not conducive to accurately evaluating the actual peak-shaving effect of the pumped-storage support system; Second, in current actual work, the peak-shaving effect of pumped storage is mainly calculated and evaluated by the pumping and power generation of pumped storage during periods of difficulty in balancing or difficulty in absorbing new energy. The indicators are difficult to reflect the regulatory role of pumped storage in response to fluctuations in new energy and loads, and cannot meet the analysis needs of the regulatory power support capacity under the new power system. Summary of the invention

[0005] In view of the above problems, the present invention proposes a method for quantitatively evaluating the peak-shaving effect of pumped storage, comprising:

[0006] For the new energy power system, a pumped storage power supply operation mathematical model is constructed according to the actual operation characteristics of the pumped storage power station;

[0007] For the new energy power system, according to the pumped storage power supply and system operation constraints, a mathematical model of the new energy power system operation containing pumped storage power supply is constructed;

[0008] Based on the time-series production simulation technology, according to the pumped-storage power supply operation mathematical model and the new energy power system operation mathematical model, an operation optimization model for the new energy power system is constructed, and the operation optimization model is solved;

[0009] Construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output the quantitative evaluation results of the peak-shaving effect of pumped storage in the new energy power system.

[0010] Optionally, the mathematical model for the operation of the pumped storage power source includes: power constraints, extraction state constraints, storage capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

[0011] Optionally, a mathematical model for the operation of a new energy power system containing a pumped storage power source, including: power source operation constraints and system operation constraints;

[0012] The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage;

[0013] The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

[0014] Optionally, the operation optimization model includes: an operation optimization model of a power system including pumped storage power and an operation optimization model of a power system excluding pumped storage power;

[0015] The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness;

[0016] The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

[0017] Optional, evaluation indicators of pumped storage peak regulation effect, including: direct indicators and indirect indicators;

[0018] The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage;

[0019] The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

[0020] Optional, direct indicators include:

[0021] The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station.

[0022] The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants;

[0023] The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation;

[0024] During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity;

[0025] During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity;

[0026] The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

[0027] Optional, indirect indicators include:

[0028] The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations;

[0029] The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy;

[0030] The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving;

[0031] The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving;

[0032] The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

[0033] In another aspect, the present invention further proposes a system for quantitatively evaluating the peak-shaving effect of pumped storage, comprising:

[0034] The first modeling unit is used to construct a pumped storage power supply operation mathematical model for the new energy power system according to the actual operation characteristics of the pumped storage power station;

[0035] The second modeling unit is used to construct a new energy power system operation mathematical model containing a pumped storage power source according to the pumped storage power source and system operation constraints for the new energy power system;

[0036] A solving unit, for constructing an operation optimization model for the new energy power system based on the time-series production simulation technology and the operation mathematical model of the pumped storage power supply and the operation mathematical model of the new energy power system, and solving the operation optimization model;

[0037] The quantitative evaluation unit is used to construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output the quantitative evaluation results of the peak-shaving effect of pumped storage in the new energy power system.

[0038] Optionally, the mathematical model for the operation of the pumped storage power source includes: power constraints, extraction state constraints, storage capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

[0039] Optionally, a mathematical model for the operation of a new energy power system containing a pumped storage power source, including: power source operation constraints and system operation constraints;

[0040] The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage;

[0041] The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

[0042] Optionally, the operation optimization model includes: an operation optimization model of a power system including pumped storage power and an operation optimization model of a power system excluding pumped storage power;

[0043] The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness;

[0044] The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

[0045] Optional, evaluation indicators of pumped storage peak regulation effect, including: direct indicators and indirect indicators;

[0046] The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage;

[0047] The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

[0048] Optional, direct indicators include:

[0049] The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station.

[0050] The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants;

[0051] The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation;

[0052] During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity;

[0053] During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity;

[0054] The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

[0055] Optional, indirect indicators include:

[0056] The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations;

[0057] The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy;

[0058] The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving;

[0059] The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving;

[0060] The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

[0061] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0062] a processor for executing one or more programs;

[0063] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0064] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The present invention provides a method for quantitatively evaluating the peak-shaving effect of pumped storage, including: for a new energy power system, according to the actual operation characteristics of a pumped storage power station, constructing a pumped storage power supply operation mathematical model; for a new energy power system, according to the pumped storage power supply and system operation constraints, constructing a new energy power system operation mathematical model containing a pumped storage power supply; based on the time series production simulation technology, according to the pumped storage power supply operation mathematical model and the new energy power system operation mathematical model, constructing an operation optimization model for the new energy power system, and solving the operation optimization model; constructing a pumped storage peak-shaving effect evaluation index, evaluating the solution result, and outputting a quantitative evaluation result of the pumped storage peak-shaving effect of the new energy power system. The present invention can evaluate the operation effect of the pumped storage support system from multiple perspectives of the peak-shaving demand side, the peak-shaving supply side and the system side. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 is a flow chart of the method of the present invention;

[0068] Figure 2 is a flow chart of an embodiment of the method of the present invention;

[0069] Figure 3 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0070] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0071] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0072] Embodiment 1:

[0073] The present invention proposes a method for quantitatively evaluating the peak-shaving effect of pumped storage. Figure 1 As shown, including:

[0074] Step 1: For the new energy power system, a pumped storage power supply operation mathematical model is constructed according to the actual operation characteristics of the pumped storage power station;

[0075] Step 2: For the new energy power system, a mathematical model of the new energy power system operation including pumped storage power source is constructed according to the pumped storage power source and system operation constraints;

[0076] Step 3: Based on the time-series production simulation technology, according to the pumped-storage power supply operation mathematical model and the new energy power system operation mathematical model, an operation optimization model for the new energy power system is constructed, and the operation optimization model is solved;

[0077] Step 4: Construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output the quantitative evaluation results of the peak-shaving effect of pumped storage in the new energy power system.

[0078] Among them, the mathematical model of pumped storage power supply operation includes: power constraints, extraction state constraints, reservoir capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

[0079] Among them, the mathematical model of the operation of the new energy power system containing pumped storage power sources includes: power supply operation constraints and system operation constraints;

[0080] The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage;

[0081] The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

[0082] The operation optimization model includes: an operation optimization model of a power system including pumped storage and an operation optimization model of a power system excluding pumped storage power;

[0083] The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness;

[0084] The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

[0085] Among them, the evaluation indicators of pumped storage peak regulation include: direct indicators and indirect indicators;

[0086] The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage;

[0087] The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

[0088] Among them, direct indicators include:

[0089] The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station.

[0090] The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants;

[0091] The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation;

[0092] During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity;

[0093] During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity;

[0094] The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

[0095] Among them, indirect indicators include:

[0096] The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations;

[0097] The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy;

[0098] The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving;

[0099] The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving;

[0100] The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

[0101] The present invention is further described below with reference to specific cases:

[0102] Case flow, such as Figure 2 As shown, including:

[0103] Step 1: Pumped Storage Power Supply Model Construction:

[0104] Conventional constraints of pumped storage power stations mainly include power generation constraints, pumping power constraints, pumping and discharge state constraints and reservoir capacity constraints. In addition, pumped storage power station constraints also include long-term power generation constraints, daily power generation constraints and short-time window power generation constraints.

[0105] Power Constraints:

[0106] Power constraints are used to constrain the power of pumped storage power stations in different operating states to not exceed their operating output limits.

[0107]

[0108] X t ∈{0,1} (2)

[0109] Where: The power generation capacity of the pumped storage power station; and The upper and lower limits of the power generation capacity of the pumped storage power station; X t is a 0-1 integer variable, where X t =1 means the pumped storage power station is in power generation state, X t =0 means that the pumped storage power station is not generating electricity.

[0110]

[0111] Y t ∈{0,1} (4)

[0112] Where: is the pumping power of the pumped storage power station; and The upper and lower limits of the pumping power of the pumped storage power station; Yt is a 0-1 integer variable, where Y t =1 means the pumped storage power station is in the pumping state, Y t =0 means that the pumped storage power station is not pumping water.

[0113] Extraction status constraints:

[0114] The pumping state constraint is used to constrain the pumped storage power station from being in the pumping and generating state at the same time.

[0115] X t +Y t ≤1 (5)

[0116] Storage capacity constraints:

[0117] Storage capacity constraints are used to describe the reservoir capacity limitations of pumped storage power stations.

[0118]

[0119] Where: W 0 is the initial water volume of the pumped storage power station reservoir; W max and W min is the maximum and minimum water volume of the reservoir; η G and η S is the average water / electricity conversion factor for power generation and pumping.

[0120] Long-term power generation constraints:

[0121] Long-term power generation constraints are mainly aimed at medium- and long-term time scales such as annual or monthly, and are used to constrain pumped-storage power stations to meet the expected power generation utilization hours in the medium and long periods.

[0122]

[0123] Where: k is a constant, which is determined by the pumped storage power generation constraint cycle parameter, usually in years or months; are the upper and lower limits of the power generation utilization hours of the pumped storage power station in time period k.

[0124] The long-term pumping power constraint is used to constrain the pumped storage power station to meet the expected pumping utilization hours in the long term.

[0125]

[0126] Where: k is a constant, which is determined by the pumped storage power constraint cycle parameter, usually in years or months; are the upper and lower limits of the pumping utilization hours of the pumped-storage power station in time period k, respectively.

[0127] Daily draw frequency limit:

[0128] The daily pumping frequency constraint is used to limit the number of times the pumped-storage power station is in a continuous pumping (power generation) state every day, and to constrain the pumped-storage power station to not frequently switch operating states during the day, so that the optimization results are consistent with the actual operating conditions.

[0129]

[0130] Where: X t-1 and X t They are the power generation states of the pumped storage power station at time t-1 and time t, and their product represents the change from non-power generation state (X t =0) switches to power generation state (X t =1) times, It is the maximum number of times in continuous power generation within a day.

[0131]

[0132] Where: Y t-1 and Y t They are the pumping states of the pumped storage power station at time t-1 and time t, and their product represents the change from non-pumping state (Y t =0) Switch to pumping state (Y t =1) times, It is the maximum number of consecutive pumping times in a day.

[0133] Short-term window power generation constraints:

[0134] The short-time window power generation constraint is mainly aimed at the short-term time scale of three to seven days, and is used to avoid the operating results of intermittent pumping or power generation in pumped-storage power stations within a short time period, that is, the situation where no power generation is performed for a long time after occasional pumping or a fixed high water level is maintained for a long time before power generation.

[0135]

[0136] Where: ΔT is the time window for setting the pumping power constraint, which is generally 3-7 days; δ is the allowable deviation between the pumped power and the generated power, to ensure that the pumped power and generated power are similar within ΔT.

[0137] Step 2: Construction of system operation optimization model including pumped storage power source:

[0138] An electric power system operation optimization model is established, which mainly includes two aspects: power supply operation constraints and system operation constraints.

[0139] Power supply operating constraints:

[0140] Based on the pumped storage power supply model constructed in step 1, the operation models of various power sources in the power system are established, mainly including thermal power units, adjustable hydropower units, and new energy storage.

[0141] The model of thermal power units is mainly composed of unit power output constraints, unit power ramp rate constraints, and unit start and stop constraints. The power output constraints of thermal power units are as follows:

[0142]

[0143] Where: is the minimum technical output of the thermal power unit at time t, P th,t The output of the thermal power unit at time t, is the maximum technical output of the thermal power unit at time t, s t is the unit state of the thermal power unit at time t, which is a 0-1 variable, s t =0 means shutdown, s t =1 means power on.

[0144] The power ramp rate constraints of thermal power units are as follows:

[0145]

[0146] Where: They are respectively the downward climbing amount and upward climbing amount of the thermal power unit.

[0147] The start and stop constraints of thermal power units are as follows:

[0148] (s t-1 -s t )(T on,t-1 -T on )≥0 (16)

[0149] (s t -s t-1 )(T off,t-1 -T off )≥0 (17)

[0150] Where: T on , T off They are the minimum continuous operation time and the minimum continuous shutdown time of thermal power units, T on,t-1 , T off,t-1 They are the continuous operation time and continuous shutdown time of the unit at time t-1 respectively.

[0151] The adjustable hydropower unit model consists of hydropower unit output constraints, power generation constraints and reservoir capacity constraints. The hydropower unit output constraints are as follows:

[0152]

[0153] Where: is the minimum technical output of the hydropower unit at time t, P hy,t The output of the hydropower unit at time t, It is the maximum technical output of the hydropower unit at time t.

[0154] The power generation constraint of adjustable hydropower units is as follows:

[0155] [P hy,t +P hy,t+1 +…+P hy,t+k ]ΔT≤E hy,max (19)

[0156] [-P hy,t -P hy,t+1 -…-P hy,t+k ]ΔT≤E hy,min (20)

[0157] Where: E hy,max 、E hy,min are the upper and lower limits of the power generation of the hydropower unit, respectively; k is a constant determined by the power generation constraint cycle parameters of the hydropower unit.

[0158] The storage capacity constraint of adjustable hydropower units is as follows:

[0159] C hy,t =C hy,t-1 +R in,t ΔT-R out,t ΔT (21)

[0160]

[0161] Where: C hy,t is the storage capacity of the reservoir at time t, R in,t , R out,t are the inbound and outbound flows at time t, are the minimum storage capacity limit and the maximum storage capacity limit at time t respectively.

[0162] The new energy storage model is mainly composed of the new energy storage charging and discharging state and times, charging and discharging power, state of charge and capacity constraints. The new energy storage charging and discharging state and times constraints are as follows:

[0163]

[0164]

[0165] Where: is the charging state of the new energy storage at time t (0 or 1), is the discharge state of the new energy storage at time t (0 or 1), and N is the total charge and discharge times of the new energy storage.

[0166] The new energy storage charging and discharging power constraints are as follows:

[0167]

[0168]

[0169] Where: is the minimum charging power of the new energy storage, P ch,t is the charging power of the new energy storage at time t, The maximum charging power of the new energy storage system. is the minimum discharge power of the new energy storage, P disch,t is the discharge power of the new energy storage at time t, It is the maximum discharge power of the new energy storage.

[0170] The new energy storage state of charge and capacity constraints are as follows:

[0171]

[0172] System operation constraints:

[0173] The constraints of the model include system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints, etc.

[0174] The system power balance constraint is as follows:

[0175]

[0176] Where: is the total optimized output of the g-type power supply at time t; P NE,t is the total optimized output of the new energy station at time t; D is the number of load nodes, P d,t is the predicted load of the dth node; L is the number of tie lines, P l,t is the power of the lth tie line at time t.

[0177] New energy output constraints include constraints on wind power and photovoltaic output, so that their output does not exceed the total predicted output.

[0178] The new energy output constraint is as follows:

[0179] 0≤P w,t ≤P w,forcast,t (30)

[0180] 0≤P pv,t ≤P pv,forcast,t (31)

[0181] Where: P w,t and P pv,tRespectively represent the output of wind power and photovoltaic power at time t; P w,forcast,t and P pv,forcast,t They represent the predicted output of wind power and photovoltaic power at time t respectively.

[0182] The tie line constraint is as follows:

[0183] P l min ≤P l,t ≤P l max (32)

[0184] Where: P l min is the lower limit of the transmission capacity of the lth tie line; P l max is the upper limit of the transmission capacity of the lth tie line.

[0185] Step 3: Power system operation optimization based on time-series production simulation:

[0186] In order to meet the evaluation needs of pumped storage peak regulation, two power system operation optimization models including pumped storage and excluding pumped storage power sources are established based on time series production simulation technology. The optimization objectives of the above two types of power system operation optimization models are both to optimize cleanliness, that is, to maximize the consumption of new energy power generation within the optimization period, and the expression is as follows:

[0187]

[0188] Where: N is the total number of aggregated power grids contained in the power system; n is the number of the aggregated power grid; T is the total length of the dispatch time; t is the simulation time variable; P w (t,n) and P pv (t,n) are the actual wind power or photovoltaic power generation output of the aggregated grid n in time period t.

[0189] Model constraints are divided into two categories: power supply operation constraints and system operation constraints. The constraints of the power system operation optimization model including pumped storage are equations (1) to (13), and the constraints of the power system operation optimization model without pumped storage are equations (14) to (32).

[0190] The unit combination optimization models established above are all mixed integer linear models. The CPLEX solver is used to solve the unit combination optimization results of the two types of power system operation optimization models, and the pumping operation results of pumped storage, the output results of conventional power sources, new energy, and the charging and discharging results of energy storage are obtained respectively. The weekly rolling solution means that the results of this week will be used as the initial variables of the next week and so on for 52 weeks throughout the year.

[0191] Step 4: Construction of evaluation index for peak regulation effect of pumped storage:

[0192] The key evaluation indicators of the peak-shaving effect of pumped-storage power stations can be divided into direct indicators and indirect indicators. Direct indicators mainly analyze the time-series operation simulation data of pumped storage to quantitatively evaluate the peak power generation capacity and energy storage capacity of pumped-storage power stations. Indirect indicators mainly analyze the time-series operation simulation data of other system resources such as net load and thermal power generation capacity to indirectly evaluate the impact of pumped-storage power stations on the peak-shaving demand side, supply side and system side after participating in the operation of the power system.

[0193] Direct indicators:

[0194] According to the power system operation optimization model including pumped storage in step 3, the sequential operation results of the pumped storage power station are solved. Based on the above results, the proportion of power generation (maximum / daily average) and power generation of the pumped storage power station during peak load periods, the ratio of pumped power to available output of new energy (maximum / daily average) and pumped power during non-peak load periods are calculated.

[0195] Maximum power generation share of pumped storage power stations during peak load periods It is used to evaluate the maximum peak capacity of a pumped storage power station, and its expression is as follows:

[0196]

[0197] Where: T peak To evaluate the collection of peak load periods on each day within the period, peak load is related to regional electricity consumption characteristics and should be based on the actual division of dispatching departments in each region; is the power generation capacity of the pumped storage power station at time t; PS is all power types in the power system; P i,t is the actual power generation of the i-th unit.

[0198] Average power generation share of pumped storage power stations during peak load periods It is used to evaluate the average peak capacity of pumped storage power stations, and its expression is as follows:

[0199]

[0200] Where: N TP is the number of peak load periods within the evaluation period.

[0201] The proportion of electricity consumed by pumped storage power stations during peak load periods μ hp,peak It is used to evaluate the contribution of pumped storage power stations to support the power balance of the system through peak-shaving power generation. The expression is as follows:

[0202]

[0203] During off-peak load periods, the maximum ratio of pumped power of pumped storage power stations to available output of renewable energy The expression used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity is as follows:

[0204]

[0205] Where: T non_peak is the set of non-peak load periods of each day within the evaluation period; is the pumping power of the pumped storage power station at time t; P w,t and P pv,t are the available power of wind power or photovoltaic power at time t respectively.

[0206] During off-peak load periods, the average ratio of pumped power of pumped storage power stations to the available output of renewable energy It is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity. The expression is as follows:

[0207]

[0208] Where: N TNP is the number of off-peak load hours during the evaluation period.

[0209] The proportion of pumped electricity during off-peak hours of pumped storage power station load μ hp,non_peak It is used to evaluate the contribution of pumped storage power stations to the consumption of new energy in the system through peak load regulation. The expression is as follows:

[0210]

[0211] Indirect indicators:

[0212] According to the two types of power system operation optimization models including pumped storage (HP) or not including pumped storage (NHP) in step 3, the operation results of new energy, load and various power sources are solved respectively. By comparing the time series operation results of HP and NHP, the evaluation index of pumped storage peak regulation effect is established from the peak regulation demand side (load, new energy), peak regulation supply side (conventional power source) and system side.

[0213] On the peak demand side, the main indicators include two types of indicators: the reduction rate of net load peak-to-valley difference and the difference in new energy utilization rate.

[0214] The net load peak-to-valley difference reduction rate ΔPVR is used to evaluate the regulation ability of pumped storage power stations to smooth out new energy and load fluctuations. The specific expression is as follows:

[0215]

[0216] Where: and are the net load values ​​of the power system without pumped storage and with pumped storage at time t respectively; N D is the number of days in the assessment period; and They are the maximum and minimum values ​​of net load on day d excluding the pumped storage power system; and They are the maximum and minimum net load values ​​of the pumped storage power system on day d, respectively.

[0217] The difference in new energy utilization rate Δη is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy. The specific expression is as follows:

[0218] Δη=η HP -η NHP (43)

[0219] Where: η HP and η NHP They are respectively the utilization rates of new energy in power systems with and without pumped storage during the assessment period.

[0220] On the peak-shaving supply side, the main indicators include two types of indicators: the average reduction rate of thermal power capacity and the difference in the average number of thermal power units.

[0221] Average thermal power capacity reduction rate ΔC th It is used to evaluate the reduction rate of the average daily peak-shaving demand of thermal power after the pumped-storage power station participates in the system peak-shaving. The expression is as follows:

[0222]

[0223] Where: and They are the average daily operating capacity of the power system with and without pumped storage during the assessment period.

[0224] Average reduction rate of the number of thermal power units in operation ΔN th It is used to evaluate the reduction rate of the average daily number of thermal power plants after the pumped storage power station participates in the system peak regulation. The expression is as follows:

[0225]

[0226] Where: and They are respectively the average daily number of operating units of power systems with and without pumped storage during the assessment period.

[0227] On the system side, the peak load capacity difference of the system is The overall evaluation of the effectiveness of pumped storage in system peak regulation is as follows:

[0228]

[0229] Where: ΔPth,d is the adjustment space of the thermal power unit on day d in the system, that is, the difference between the maximum technical output of thermal power on day d and the minimum technical output of thermal power. The calculation method for other units is the same; ΔP hy,d is the adjustment space of the hydropower unit on day d in the system; ΔP bat,d Adjustment space for the new energy storage unit on day d in the system; ΔP hp,d Adjust the space for the d-day pumped storage units in the system; and They are the average daily regulation space of power systems with and without pumped storage during the assessment period.

[0230] Step 5: Construction of evaluation method for peak regulation effect of pumped storage:

[0231] First, the operation optimization model of the power system including pumped storage is solved to obtain the time sequence operation results of pumped storage and other power sources. The operation results include the startup status, startup capacity, and power generation of each unit at each time during the evaluation period, as well as the available power, actual power generation, and abandoned power of wind power and photovoltaic power in the system. Based on the above results, formulas (34) to (39) are calculated to output the maximum power generation proportion of the pumped storage power station during the peak load period. Average power generation share Power generation ratio μ hp,peak , and the maximum pumping power ratio during off-peak hours Average pumping power ratio Pumped electricity ratio μ hp,non_peak Indicator results. If and μ hp,peak If the index is higher (such as higher than the previous evaluation cycle or the expected index value), it means that the peak effect of the pumped storage power station during the peak load period is stronger (increased), otherwise it means that the peak effect of the pumped storage power station is lower (decreased); similarly, if and μ hp,non_peak A higher index (such as higher than the previous evaluation cycle or the expected index value) means that the energy storage effect of the pumped-storage power station during non-peak load periods is stronger (increased), otherwise it means that the energy storage effect of the pumped-storage power station is lower (decreased).

[0232] Secondly, the optimization model of the power system operation without pumped storage is optimized and solved to obtain the timing operation results of various power sources. Combined with the operation results of various power sources in the power system operation model with pumped storage, equations (40) to (47) are calculated. In terms of demand regulation, the output net load peak-to-valley difference reduction rate ΔPVR and the new energy utilization rate difference Δη are used; in terms of peak regulation supply, the output thermal power average startup capacity reduction rate ΔC th , the difference in the average number of thermal power units in operation ΔN th Two types of indicators; in terms of the overall system, the difference in the peak load capacity of the output system If the ΔPVR and Δη indicators are non-negative and higher than the previous evaluation period or the expected indicator value, it means that the pumped storage power station has a strong effect in smoothing the net load fluctuation of the power system or promoting the consumption of new energy, otherwise it is relatively low; if ΔC th and ΔN th If the indicator result is non-negative and higher than the previous evaluation cycle or the expected indicator value, it means that the pumped storage power station has a strong effect in reducing the start-up of thermal power through peak load regulation, otherwise it is lower; if If the indicator result is non-negative and higher than the previous evaluation cycle or the expected indicator value, it means that the pumped-storage power station will have a stronger effect on improving the overall peak-shaving capacity of the system after it participates in operation, otherwise it will be lower.

[0233] Embodiment 2:

[0234] The present invention also proposes a system 200 for quantitatively evaluating the peak-shaving effect of pumped storage, such as Figure 3 As shown, including:

[0235] The first modeling unit 201 is used to construct a pumped storage power supply operation mathematical model for the new energy power system according to the actual operation characteristics of the pumped storage power station;

[0236] The second modeling unit 202 is used to construct a new energy power system operation mathematical model containing a pumped storage power source according to the pumped storage power source and system operation constraints for the new energy power system;

[0237] A solving unit 203 is used to construct an operation optimization model for the new energy power system based on the time-series production simulation technology and the operation mathematical model of the pumped storage power supply and the operation mathematical model of the new energy power system, and solve the operation optimization model;

[0238] The quantitative evaluation unit 204 is used to construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output a quantitative evaluation result of the peak-shaving effect of pumped storage in the new energy power system.

[0239] Among them, the mathematical model of pumped storage power supply operation includes: power constraints, extraction state constraints, reservoir capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

[0240] Among them, the mathematical model of the operation of the new energy power system containing pumped storage power sources includes: power supply operation constraints and system operation constraints;

[0241] The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage;

[0242] The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

[0243] The operation optimization model includes: an operation optimization model of a power system including pumped storage and an operation optimization model of a power system excluding pumped storage power;

[0244] The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness;

[0245] The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

[0246] Among them, the evaluation indicators of pumped storage peak regulation include: direct indicators and indirect indicators;

[0247] The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage;

[0248] The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

[0249] Among them, direct indicators include:

[0250] The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station.

[0251] The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants;

[0252] The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation;

[0253] During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity;

[0254] During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity;

[0255] The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

[0256] Among them, indirect indicators include:

[0257] The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations;

[0258] The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy;

[0259] The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving;

[0260] The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving;

[0261] The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

[0262] The present invention takes into account the complex characteristics of the sequential operation of pumped-storage power stations, and aims at the dispatching and operation requirements of pumped-storage power stations. Based on the sequential production simulation technology, an optimization model for the operation of the power system including pumped-storage power stations is established, which can accurately simulate the startup status and output results of various power sources. This patent proposes 14 evaluation indicators from both direct and indirect levels for the peak-shaving effect of pumped-storage power stations on the power system, and establishes a quantitative evaluation index system and method for the peak-shaving effect of pumped-storage power stations, which can evaluate the operation of the pumped-storage support system from multiple perspectives, including the peak-shaving demand side, the peak-shaving supply side, and the system side.

[0263] Embodiment 3:

[0264] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0265] Embodiment 4:

[0266] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0267] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0268] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0269] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0270] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0271] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0272] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for quantitatively evaluating the peak-shaving effect of pumped storage, characterized in that: include: For the new energy power system, a pumped storage power supply operation mathematical model is constructed according to the actual operation characteristics of the pumped storage power station; For the new energy power system, according to the pumped storage power supply and system operation constraints, a mathematical model of the new energy power system operation containing pumped storage power supply is constructed; Based on the time-series production simulation technology, according to the pumped-storage power supply operation mathematical model and the new energy power system operation mathematical model, an operation optimization model for the new energy power system is constructed, and the operation optimization model is solved; Construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output the quantitative evaluation results of the peak-shaving effect of pumped storage in the new energy power system.

2. The method according to claim 1, characterized in that The pumped storage power supply operation mathematical model includes: power constraints, extraction state constraints, storage capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

3. The method according to claim 1, characterized in that The operation mathematical model of the new energy power system containing pumped storage power source includes: power supply operation constraints and system operation constraints; The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage; The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

4. The method according to claim 1, characterized in that The operation optimization model includes: an operation optimization model of a power system including pumped storage power and an operation optimization model of a power system without pumped storage power; The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness; The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

5. The method according to claim 1, characterized in that The evaluation index of the peak regulation effect of pumped storage includes: direct index and indirect index; The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage; The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

6. The method according to claim 5, characterized in that The direct indicators include: The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station. The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants; The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation; During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity; During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity; The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

7. The method according to claim 5, characterized in that The indirect indicators include: The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations; The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy; The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving; The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving; The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

8. A system for quantitative evaluation of the peak-shaving effect of pumped storage, characterized in that: include: The first modeling unit is used to construct a pumped storage power supply operation mathematical model for the new energy power system according to the actual operation characteristics of the pumped storage power station; The second modeling unit is used to construct a new energy power system operation mathematical model containing a pumped storage power source according to the pumped storage power source and system operation constraints for the new energy power system; A solving unit, for constructing an operation optimization model for the new energy power system based on the time-series production simulation technology and the operation mathematical model of the pumped storage power supply and the operation mathematical model of the new energy power system, and solving the operation optimization model; The quantitative evaluation unit is used to construct an evaluation index for the peak-shaving effect of pumped storage, evaluate the solution results, and output the quantitative evaluation results of the peak-shaving effect of pumped storage in the new energy power system.

9. The system according to claim 8, characterized in that The pumped storage power supply operation mathematical model includes: power constraints, extraction state constraints, storage capacity constraints, long-cycle extraction power constraints, daily extraction times constraints and short-time window extraction power constraints.

10. The system according to claim 8, characterized in that The operation mathematical model of the new energy power system containing pumped storage power source includes: power supply operation constraints and system operation constraints; The power supply operation constraints include: power output constraints, power ramp rate constraints and start-stop constraints of thermal power units, power generation constraints and storage capacity constraints of adjustable hydropower units, charging and discharging state and number constraints, charging and discharging power constraints, and charge state and capacity constraints of new energy storage; The system operation constraints include: system load balance constraints under all renewable energy output scenarios, conventional power supply operation constraints, renewable energy output constraints and interconnection line constraints.

11. The system according to claim 8, characterized in that The operation optimization model includes: an operation optimization model of a power system including pumped storage power and an operation optimization model of a power system without pumped storage power; The optimization objectives of the power system operation optimization model including pumped storage and the power system operation optimization model without pumped storage power are both optimal cleanliness; The cleanliness is optimal, which means that the consumption of new energy power generation is maximized within the optimization period.

12. The system according to claim 8, characterized in that The evaluation index of the peak regulation effect of pumped storage includes: direct index and indirect index; The direct index is used to evaluate the solution results of the power system operation optimization model containing pumped storage; The indirect index is used to evaluate the solution results of the power system operation optimization model including pumped storage power source and the power system operation optimization model without pumped storage power source.

13. The system according to claim 12, characterized in that The direct indicators include: The maximum power generation ratio of a pumped storage power station during peak load hours is used to evaluate the maximum peak capacity of a pumped storage power station. The average proportion of power generation of pumped storage power plants during peak load periods is used to evaluate the average peak capacity of pumped storage power plants; The proportion of electricity generated by pumped-storage power stations during peak load periods is used to assess the contribution of pumped-storage power stations to supporting the power balance of the system through peak load generation; During off-peak load periods, the maximum ratio of pumped power of a pumped storage power station to the available output of renewable energy is used to evaluate the maximum capacity of a pumped storage power station to store renewable energy electricity; During off-peak load periods, the average ratio of pumped power of pumped storage power stations to available output of renewable energy is used to evaluate the average capacity of pumped storage power stations to store renewable energy electricity; The proportion of pumped electricity during non-peak hours of the pumped-storage power station is used to evaluate the contribution of the pumped-storage power station to promoting the consumption of new energy in the system through peak-shaving pumping.

14. The system according to claim 12, characterized in that The indirect indicators include: The net load peak-to-valley difference reduction rate on the peak demand side is used to evaluate the pumped storage power station's ability to smooth out new energy and load fluctuations; The difference in the utilization rate of new energy on the peak demand side is used to evaluate the role of pumped storage power stations in promoting the consumption of new energy; The average thermal power capacity reduction rate on the peak-shaving supply side is used to evaluate the average daily thermal power peak-shaving demand reduction rate after the pumped-storage power station participates in the system peak-shaving; The average reduction rate of the number of thermal power units in operation on the peak-shaving supply side is used to evaluate the reduction rate of the average daily number of thermal power units after the pumped-storage power station participates in the system peak-shaving; The difference in system peak-shaving capacity on the system side is used to comprehensively evaluate the effectiveness of pumped storage in participating in system peak-shaving.

15. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 7 is implemented.

16. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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