New energy consumption flexibility assessment method considering adjustment effect of pumped storage power station

Abstract

A new energy consumption flexibility evaluation method considering the adjustment effect of a pumped storage power station relates to the technical field of power system planning, and comprises the steps of generating output scenes with different probabilities, obtaining the flexibility demand of each scene according to a day-ahead output plan, and obtaining the flexibility demand of each scene through the flexibility supply-demand relationship and the flexibility index obtained by combining with the supply. And then constructing a flexibility deficiency expectation and probability model, setting a correction coefficient according to the flexibility deficiency probability to redistribute and evaluate the wind and light abandoning quantity, and finally considering the adjustment effect of the pumped storage power station to obtain the comprehensive evaluation indexes of the system flexibility under different new energy power generation ratio conditions. According to the method, the flexibility requirement of the power system can be evaluated more accurately, power resource configuration is optimized, energy waste is reduced, and the economical efficiency and reliability of the power system are improved. More effective decision support can be provided for an electric power system operator, and efficient utilization of new energy and sustainable development of an electric power system are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and in particular to a method for evaluating the flexibility of new energy consumption taking into account the regulating effect of a pumped-storage power station. Background Art

[0002] In recent years, the proportion of renewable energy power generation in my country's power system has increased year by year. The total installed capacity of wind power, solar power and biomass power generation has reached 1.27 billion kilowatts, accounting for 40.7% of the total installed power generation capacity. In order to adapt to the rapid development of renewable energy, there are higher requirements for the operational flexibility of the power system. Through research, it is found that insufficient flexibility is the root cause of the large-scale grid connection and high-level consumption of wind and solar energy. How to reasonably and economically consume renewable energy and provide flexibility has become an urgent problem to be solved.

[0003] Flexibility refers to the ability of the power system to respond to fluctuations in power generation, grid operation, and load demand in an economical and efficient manner within a specific time frame by optimizing the scheduling of available resources to ensure stable and reliable power supply. Current research generally believes that flexibility has the following characteristics: directionality, intrinsic characteristics, and must be evaluated at a certain time scale. Traditional research on flexibility evaluation is based on the evaluation of power system flexibility based on deterministic evaluation indicators. This method cannot accurately reflect the impact of uncertain factors and ignores the dynamic changes and uncertainties of renewable energy generation. In addition, existing methods often regard wind and solar power abandonment as a direct consequence of insufficient flexibility, without in-depth analysis of its specific impact on system flexibility, and without proposing effective solutions. Summary of the invention

[0004] The purpose of the present invention is to provide a method for evaluating the flexibility of new energy consumption taking into account the regulating effect of pumped-storage power stations, so as to more accurately evaluate the flexibility requirements of the power system, optimize the allocation of power resources, reduce energy waste, and improve the economy and reliability of the power system.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solution: a method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations, comprising the following steps:

[0006] (1) Generate output scenarios with different probabilities;

[0007] (2) Determine the flexibility requirements for each scenario based on the day-ahead output plan;

[0008] (3) Combined with supply capacity, obtain flexibility supply and demand relationship and flexibility evaluation indicators;

[0009] (4) Constructing the expectation and probability model of inflexibility deficiency;

[0010] (5) Set a correction factor based on the probability of insufficient flexibility, and redistribute and evaluate the amount of wind and solar power curtailment;

[0011] (6) Considering the regulating effect of pumped-storage power stations, the comprehensive evaluation index of system flexibility under different proportions of renewable energy power generation is obtained.

[0012] Preferably, in step (1), kernel density estimation and coupla function are used to generate output scenarios with different probabilities. The method includes the following steps:

[0013] (1.1) Take n samples of the random variable X: x1, x2, x3, …, xn;

[0014] (1.2) The wind and solar power output data are processed using the kernel density method to obtain the probability distribution function of each time period:

[0015]

[0016] Where: h is the window width; Y is the output of the fan at the nth hour on the i-th day; i n is the photovoltaic power output at the nth hour on the i-th day; K(·) is the kernel density function;

[0017] (1.3) The binary Frank-Copula function is used to model the wind and solar power output in each period to obtain its joint probability distribution function:

[0018]

[0019] Where: F n (x i ,y i ) is the wind-solar joint distribution function in a fixed period; C(·) is the binary Frank-Copula function; u i 、v i are the distribution functions of wind power and photovoltaic units respectively;

[0020] (1.4) The obtained joint distribution function is used to sample data from all fixed time periods, and the wind turbine and photovoltaic output of each time period is obtained through inverse transformation, and finally a typical daily curve is generated that takes into account the correlation and randomness of wind and photovoltaic power.

[0021] More preferably, in step (2), the flexibility requirement F i,m,t It is defined as the difference between the mth scenario and the planned output of the wind-solar cluster i at time t. When the planned power generation curve is lower than the wind-solar cluster curve, the difference is the upward flexibility demand. When the planned power generation curve is higher than the wind-solar cluster curve, the difference is the downward flexibility demand. It is expressed as follows:

[0022]

[0023] Where: and They respectively increase and decrease the flexibility requirement of the system at time t for the mth scenario of cluster i.

[0024] More preferably, in step (3), the flexibility supply and demand relationship obtained includes the flexibility supply of hydropower units and the flexibility supply of pumped storage;

[0025] The flexibility supply of the hydropower unit is expressed as:

[0026]

[0027] Where: τ is the time scale; Increase flexibility supply capacity for hydropower plants; Hydropower stations reduce their flexibility supply capacity; is the ramp rate of the nth hydropower station; is the down-ramp rate of the nth hydropower station; It is the maximum output of conventional units; It is the minimum output of conventional units. Under different time scales, the adjustable range of the units is different.

[0028] The pumped storage flexibility supply is expressed as:

[0029]

[0030] Where: The pumped storage provides upward flexibility for cluster i at time t, The pumped storage unit provides downward flexibility for cluster i at time t, is the climbing capacity of pumped storage unit i, are the upper and lower limits of the output of pumped storage unit i at time t respectively.

[0031] More preferably, in step (3), the flexibility evaluation index includes the probability of insufficient flexibility upward adjustment, the probability of insufficient flexibility downward adjustment, the expectation of insufficient flexibility upward adjustment and the expectation of insufficient flexibility downward adjustment.

[0032] More preferably, the flexibility deficiency expectation and probability model constructed in step (4) includes: flexibility increase deficiency probability:

[0033]

[0034] Where: The probability of insufficient supply capacity for cluster i in period t is adjusted upward flexibly; is a set of scenarios where the flexible upward adjustment of supply capacity is insufficient in cluster i at time t; The flexibility increase supply capacity provided by the flexibility resource to cluster i in time period t;

[0035] Probability of insufficient flexibility reduction:

[0036]

[0037] Where: is the probability of insufficient supply capacity for cluster i in period t; A set of scenarios for cluster i to flexibly adjust its supply capacity in time period t; The flexibility of the flexible resource provided to cluster i in time period t is adjusted downward;

[0038] Flexibility increase falls short of expectations:

[0039]

[0040] In the formula is the flexibility increase of cluster i at time t that is less than the expectation, MW;

[0041] Flexibility downgraded below expectations:

[0042]

[0043] In the formula The flexibility of cluster i at time t is adjusted downward less than expected, MW.

[0044] More preferably, the objective function is to minimize the sum of the expected inflexibility deficiency of each cluster and the sum of the inflexibility deficiency probability:

[0045]

[0046]

[0047] More preferably, the constraints on the flexibility evaluation index include flexibility adjustment capability, water balance constraint, initial and final water level constraint, reservoir water level constraint, power generation flow constraint, outflow flow constraint, and hydropower station output constraint.

[0048] More preferably, in step (5), let d k d1 is the area with the largest area of ​​insufficient flexibility adjustment capacity, and d2 is the area with the smallest area of ​​insufficient flexibility adjustment capacity. k Lower the probability of insufficient flexibility to 1 and set the correction factor to X:

[0049]

[0050] D=d1+d2+…+d k

[0051] d k >…>d2>d1

[0052] d k >d>d1

[0053] Where: D is the sum of the areas with insufficient flexibility adjustment capacity, d is the area between d k Any region between d1 and d2, in d k The probability of insufficient downward flexibility in the area between d1 is:

[0054]

[0055] At this time, the allowed amount of wind and solar power abandonment is allocated according to the corrected probability:

[0056]

[0057] Where: W is the amount of wind and solar power that can be abandoned; W t ′ is the amount of wind and solar power abandoned at time t.

[0058] More preferably, in step (6), the mode of considering the regulation effect of the pumped storage power station is expressed as:

[0059]

[0060] in, Provide downward flexibility for pumped storage.

[0061] Compared with the prior art, the present invention not only incorporates the phenomenon of wind and solar power abandonment into the consideration of flexibility assessment, but also innovatively introduces the regulating role of pumped-storage power stations, and constructs a flexibility assessment system that comprehensively considers the characteristics of renewable energy power generation and the synergistic effects of pumped-storage power stations. This method can more accurately assess the flexibility needs of the power system, optimize the allocation of power resources, reduce energy waste, and improve the economy and reliability of the power system. Through this method, more effective decision-making support can be provided to power system operators, promoting the efficient use of new energy and the sustainable development of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of the scenery scene generation steps in the embodiment;

[0063] Figure 2 A schematic diagram for quantifying flexibility requirements in an embodiment;

[0064] Figure 3 Schematic diagram of the regulation capability of hydropower units at different time scales in the embodiment;

[0065] Figure 4Schematic diagram of the evaluation process in the embodiment;

[0066] Figure 5 It is a schematic diagram of the wind-solar cluster output curve in the embodiment;

[0067] Figure 6 This is a schematic diagram of the supply and demand relationship of downward adjustment flexibility on a typical day during the dry season in the embodiment;

[0068] Figure 7 Schematic diagram of downward flexibility index for different wind power penetration rates when not in operation in the embodiment. DETAILED DESCRIPTION

[0069] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0070] The new energy consumption flexibility assessment method considering the regulation effect of the pumped storage power station in this embodiment mainly includes the following steps:

[0071] (1) Kernel density estimation and Coupla function are used to generate output scenarios with different probabilities.

[0072] The use of Copula functions can effectively characterize the nonlinearity, asymmetry and tail correlation between wind and solar power outputs, while capturing the temporal and spatial relationships between wind and solar power outputs. Its theoretical framework connects the joint distribution of multivariate random variables with their respective marginal distribution functions. The binary Copula function has tail symmetry and can reveal the positive and negative correlations between variables; among them, the Gumbel and Clayton Copula functions can only describe specific types of correlations, while the Frank-Copula function is superior to the t-Copula and normal Copula functions in fitting accuracy. Therefore, this embodiment uses the Frank-Copula function to model the correlation between wind and solar power outputs. The distribution function of the binary Frank-Copula function is as follows:

[0073]

[0074] Where: u i 、v i , i are all related parameters. i The value of is in the interval [0,1], which means u i and v i There is a positive correlation between them; if the value of iλ is in the interval [–1,0], it means that u i and v i There is a negative correlation between i Approaching 0, it means u i and vi The specific process of generating wind and solar power output scenarios is as follows: Figure 1 As shown, the specific steps are as follows:

[0075] (1.1) Take n samples of the random variable X: x1, x2, x3, …, xn;

[0076] (1.2) The wind and solar power output data are processed using the kernel density method to obtain the probability distribution function of each time period:

[0077]

[0078] Where: h is the window width; Y is the output of the fan at the nth hour on the i-th day; i n is the photovoltaic power output at the nth hour on the i-th day; K(·) is the kernel density function;

[0079] (1.3) The binary Frank-Copula function is used to model the wind and solar power output in each period to obtain its joint probability distribution function:

[0080]

[0081] Where: F n (x i ,y i ) is the wind-solar joint distribution function in a fixed period; C(·) is the binary Frank-Copula function; u i 、v i are the distribution functions of wind power and photovoltaic units respectively;

[0082] (1.4) The obtained joint distribution function is used to sample data from all fixed time periods, and the wind turbine and photovoltaic output of each time period is obtained through inverse transformation, and finally a typical daily curve is generated that takes into account the correlation and randomness of wind and photovoltaic power.

[0083] In view of the excessive amount of wind and solar data, in order to generate scenes quickly and accurately, this embodiment uses the K-means clustering method to cluster the sampled data, and reduces the scenes by minimizing the weighted average distance between the samples and the cluster centers to obtain k representative typical scenes of wind and solar output.

[0084] (2) Determine the flexibility requirements for each scenario based on the day-ahead output plan.

[0085] Flexibility requirements i,m,t It is defined as the difference between the mth scenario and the planned output of the wind-solar cluster i at time t. When the planned power generation curve is lower than the wind-solar cluster curve, the difference is the upward flexibility demand. When the planned power generation curve is higher than the wind-solar cluster curve, the difference is the downward flexibility demand. Figure 2 As shown in FIG, the wind-solar cluster curve is the output curve of the mth scenario of the ith cluster of a cascade power station, and the power generation plan is the day-ahead plan provided by the power grid.

[0086]

[0087] Where: and They respectively increase and decrease the flexibility requirement of the system at time t for the mth scenario of cluster i.

[0088] (3) Combined with supply capacity, obtain flexibility supply and demand relationship and flexibility evaluation indicators.

[0089] In this step, the flexibility supply and demand relationship obtained includes the flexibility supply of hydropower units and the flexibility supply of pumped storage. Specifically, the flexibility supply of hydropower units is expressed as:

[0090]

[0091] Where: τ is the time scale; Increase flexibility supply capacity for hydropower plants; Hydropower stations reduce their flexibility supply capacity; is the ramp rate of the nth hydropower station; is the down-ramp rate of the nth hydropower station; It is the maximum output of conventional units; is the minimum output of a conventional unit. Under different time scales, the adjustable range of the unit is also different. Figure 3 As shown in the figure, within 15 minutes, the adjustable range of the flexibility of the hydropower unit is proportional to the climbing rate. After a period of time, the unit reaches the output limit, and the flexibility can no longer be adjusted upward.

[0092] The flexibility supply of pumped hydroelectric energy storage (PHES) is expressed as:

[0093]

[0094] Because there is one pumped storage for each of the two power stations, corresponding to the wind and solar cluster i, the pumped storage is also represented by i, and the i-th pumped storage is assumed to provide flexibility for the i-th cluster by default. The pumped storage provides upward flexibility for cluster i at time t, The pumped storage unit provides downward flexibility for cluster i at time t, is the climbing capacity of pumped storage unit i, are the upper and lower limits of the output of pumped storage unit i at time t respectively.

[0095]

[0096] Where: is the power of pumped storage power generation, and the flow of the upper reservoir And the upper reservoir head H UR related; is the pumping power of pumped storage, and the flow rate of the lower reservoir and the lower reservoir head H LR Related; η g is the power generation efficiency of pumped storage; η m Pumping efficiency for pumped storage; Upper reservoir water level; is the water level of the lower reservoir; upward flexibility provided for pumped hydro; Provides downward flexibility for pumped storage; ρ is the density of water; g is the acceleration due to gravity.

[0097] To achieve system balance, the flexible supply capacity must be greater than the demand at all times:

[0098]

[0099] Where: P s,n,t+1 , P s,n,t are the outputs of hydropower station n at time t+1 and t respectively; N is the total number of hydropower stations; δ i is the difference between the planned output and the actual output of wind-solar cluster i; I is the total number of wind-solar clusters.

[0100] In addition, the flexibility evaluation indicators in this step include the probability of insufficient flexibility upward adjustment, the probability of insufficient flexibility downward adjustment, the expectation of insufficient flexibility upward adjustment and the expectation of insufficient flexibility downward adjustment.

[0101] (4) Construct the expected and probabilistic model of inflexibility deficiency. The specific components of the model are as follows:

[0102] (4.1) Probability of insufficient flexibility increase:

[0103] Flexibility increases the probability that supply capacity will not be able to meet demand in period t.

[0104]

[0105] Where: The probability of insufficient supply capacity for cluster i in period t is adjusted upward flexibly; is a set of scenarios where the flexible upward adjustment of supply capacity is insufficient in cluster i at time t; The flexibility increase supply capacity provided by the flexibility resources to cluster i in period t.

[0106] (4.2) Probability of insufficient flexibility adjustment:

[0107] Flexibility reduces the probability that supply capacity will not be able to meet demand in period t.

[0108]

[0109] Where: is the probability of insufficient supply capacity for cluster i in period t; A set of scenarios for cluster i to flexibly adjust its supply capacity in time period t; The flexibility of the flexible resource provided to cluster i in time period t is reduced to provide capacity.

[0110] (4.3) The increase in flexibility is less than expected:

[0111] The expectation of the difference between the increased flexibility demand and the increased supply capacity due to insufficient adjustment capacity during period t.

[0112]

[0113] In the formula is the flexibility increase of cluster i that is less than expected at time period t, MW.

[0114] (4.4) Flexibility reduction is less than expected:

[0115] The expectation of the difference between the increased flexibility demand and the increased supply capacity due to insufficient adjustment capacity during period t.

[0116]

[0117] In the formula The flexibility of cluster i at time t is adjusted downward less than expected, MW.

[0118] Furthermore, in order to minimize wind and solar power abandonment, minimize the impact of intermittent renewable energy on the stable and safe operation of the system, ensure economy, and reduce operating costs, this embodiment uses the minimum sum of the expected insufficiency of flexibility of each cluster and the minimum sum of the insufficiency probability of flexibility as the objective function:

[0119]

[0120] In this embodiment, the constraints on the flexibility evaluation index include flexibility adjustment capability, water balance constraint, initial and final water level constraint, reservoir water level constraint, power generation flow constraint, outflow flow constraint, and hydropower station output constraint. Among them:

[0121] 1.Flexibility and adjustment capability:

[0122]

[0123] is the upward flexibility supply capacity provided by hydropower and PHES for cluster i at time period t, MW; The flexibility that pumped storage provides to cluster i during period t is The flexibility increase capability provided by the nth hydropower station to cluster i in period t.

[0124]

[0125] In the formula The flexibility to increase the capacity provided to the nth hydropower station during period t; The flexibility reduction capacity provided for the nth hydropower station in period t, MW.

[0126] 2. Water balance constraints:

[0127]

[0128] Where: V n,t+1 、V n,t are the storage capacity of hydropower station n at time t+1 and t, respectively, 3 ;QI n,t With QU n,t are the inflow and outflow of hydropower station n in period t, m 3 / s; Δt is the number of hours in period t; τ n-1 is the water flow delay time from reservoir n-1 to reservoir n; QE n,t , QD n,t , QS n,t are the interval inflow, power generation flow and abandoned water flow of hydropower station n in period t, respectively. 3 / s.

[0129] 3. Initial and final water level constraints:

[0130]

[0131] Where: Z n,1 , Z n,T+1 are the reservoir water levels at the beginning and end of the dispatching period of hydropower station n, m; are the initial and final water levels of the dispatching period given by hydropower station n, m.

[0132] 4. Reservoir water level constraints:

[0133]

[0134] Where: Z n,t , are the water level, lower water level limit and upper water level limit of hydropower station n in period t, m respectively.

[0135] 5. Power generation flow constraints:

[0136]

[0137] Where: QD n,t , are the power generation flow and maximum power generation flow of hydropower station n in period t, m 3 / s.

[0138] 6. Outbound flow constraints:

[0139]

[0140] Where: QU n,t , are the minimum outflow, outflow and maximum outflow of hydropower station n in period t, respectively. 3 / s.

[0141] 7. Hydropower station output constraints:

[0142]

[0143] Where: P n,t , They are the output, minimum output and maximum output of hydropower station n in period t, MW.

[0144] (5) Set a correction factor based on the probability of insufficient flexibility, and redistribute and evaluate the amount of wind and solar power curtailment.

[0145] Assume d k d1 is the area with the largest area of ​​insufficient flexibility adjustment capacity, and d2 is the area with the smallest area of ​​insufficient flexibility adjustment capacity. k The probability of insufficient flexibility is corrected to 1, and the correction coefficient is set to X (x is just a coefficient. The overall purpose of the following formula is to make the size of the area with insufficient flexibility adjustment ability correspond to the probability size. The t below the probability represents the time period, so it can be used directly).

[0146]

[0147] D=d1+d2+…+d k

[0148] d k >…>d2>d1

[0149] d k >d>d1

[0150] Where: D is the sum of the areas with insufficient flexibility adjustment capacity, d is the area between d kAny region between d and d1. k The probability of insufficient downward flexibility in the area between d1 is:

[0151]

[0152] At this time, the allowable amount of wind and solar power abandonment will be allocated according to the corrected probability.

[0153]

[0154] Where: W is the amount of wind and solar power that can be abandoned; W t ′ is the amount of wind and solar power abandoned at time t.

[0155] (6) Considering the regulating effect of pumped-storage power stations, the comprehensive evaluation index of system flexibility under different proportions of renewable energy power generation is obtained.

[0156] Specifically, allocating the amount of wind and solar power curtailment based on the revised downward inflexibility probability can better improve the flexibility problem caused by insufficient ramping. However, if the amount of wind and solar power curtailment is to be further reduced, pumped storage needs to be considered:

[0157]

[0158] Providing downward flexibility supply for pumped storage can further reduce the amount of wind and solar power curtailment, which can produce better economic benefits in scenarios with a high proportion of new energy access. After allocating the wind and solar power curtailment, flexibility assessment is conducted again to obtain flexibility assessment indicators that consider the use of pumped storage to coordinate the consumption of new energy. The specific process is as follows Figure 4 shown.

[0159] The flexibility demand is quantified through Matlab programming, and the quantified results are input into the flexibility assessment model. Pumped storage is then added to the flexibility assessment model to construct a short-term scheduling model considering pumped storage, and the target is solved.

[0160] Simulation test

[0161] Take the renewable energy system consisting of three wind and solar power station clusters and four cascade hydropower stations in a certain area of ​​Hunan as an example. Since the flexibility in the flood season can basically meet its needs and the research significance is not great, a typical day in the dry season is selected for simulation calculation. The actual output of a typical day is used to construct the probability distribution function of the wind and solar power station cluster, 15 minutes is used as the time scale, and all the parameters input to the model are actual parameters. Table 1 and Supplementary Table 1 are the basic data of each power station. In order to verify the method of the above embodiment, a wind-solar penetration rate of 50% is set for simulation analysis, assuming that the wind-solar ratio in the wind-solar cluster is the optimal ratio.

[0162] Table 1 Basic data of power station

[0163]

[0164] Supplementary Table 1 Pumped Storage Power Station Parameters

[0165]

[0166] 1. Lower the flexibility supply and demand analysis.

[0167] The wind-solar cluster output curve is generated by the above wind-solar output scene generation method, such as Figure 5 shown.

[0168] According to the actual day-ahead power generation plan, the power generation curve is drawn to obtain the flexibility upward and downward demand, and then the downward flexibility supply capacity is obtained to obtain the downward flexibility supply and demand relationship as follows: Figure 6 The analysis shows that the downward adjustment flexibility of each cluster at different times is in short supply to varying degrees, indicating that a 50% wind power penetration rate puts a lot of pressure on the system and requires more means to provide sufficient downward adjustment flexibility. Therefore, the flexibility adjustment means are analyzed below.

[0169] 2. Analysis of downward flexibility adjustment measures.

[0170] According to the downward flexibility index given in Table 2, it can be seen that when the wind-solar penetration rate is 50%, the pumped storage cost is consistent with the case of 10% wind and solar power abandonment. Under the wind and solar power abandonment operation, the probability and expectation of insufficient downward flexibility are reduced by 4.28% and 93.6MW respectively. If the index is to be further reduced, more wind and solar power abandonment will be required, which will increase excessive costs. At this time, adding pumped storage for consideration, it can be seen that the probability and expectation of insufficient flexibility are reduced by 14.67% and 456.8MW respectively, which is more than 4 times lower than the case of only considering wind and solar power abandonment. It can be seen that in the case of 50% wind and solar power penetration, it is more appropriate to use pumped storage to improve downward flexibility.

[0171] Table 2 Flexibility indicators for 50% wind power penetration

[0172]

[0173] In order to further analyze the methods applicable to lower and higher wind-solar penetration rates, this embodiment introduces wind-solar penetration rates of 30% and 70% for comparison, and Table 3 shows the downward flexibility indicators for different wind-solar penetration rates. Table 4 shows the incremental flexibility provided by pumped storage at different wind-solar penetration rates and 10% wind and solar abandonment under the same cost scenario. It can be seen that when the wind-solar penetration rate is higher than 30%, the downward flexibility increment and growth rate are much greater than the parameters when 10% wind and solar abandonment occurs. It can be seen that under high wind-solar penetration rates, it is more suitable to use pumped storage to adjust the downward flexibility. When the wind-solar penetration rate is 30%, the downward flexibility of using 10% wind and solar abandonment increases by 1.4%. At the same cost, the use of pumped storage increases the downward flexibility by 1.2%, which is lower than the downward flexibility adjustment benefit brought by 10% wind and solar abandonment. Therefore, when the wind-solar penetration rate is 30%, it is more appropriate to use the means of abandoning wind and solar.

[0174] Table 3 Flexibility index for different wind and solar penetration rates

[0175]

[0176] Table 4: Flexibility increment under the same cost

[0177]

[0178] pass Figure 7 The distribution and change trend of the expected and probability of insufficient flexibility at different wind power penetration rates show that the higher the wind and solar penetration rate, the greater the slope of the expected inflexibility, which is close to a quadratic function, and the slope of the probability of insufficient flexibility does not change much, increasing linearly, and overall, the changes in both are very large. It can be seen that the higher the wind and solar penetration rate, the greater the probability and expectation of insufficient flexibility, and the growth rate is extremely fast.

[0179] To sum up, when the wind power penetration rate is lower than 30%, it is more appropriate to use wind and solar power abandonment to improve the flexibility of downward regulation. When it is higher than 30%, a large amount of wind and solar power abandonment will be generated. Therefore, it is obviously not enough to only use wind and solar power abandonment to adjust the flexibility. Therefore, pumped storage can be used to provide downward flexibility to achieve the best economic regulation.

[0180] The following conclusions can be drawn from the corresponding simulation test results:

[0181] 1) The simulation analysis reveals that as the acceptable wind curtailment ratio increases, the problem of insufficient downward flexibility faced by the system is gradually alleviated. This shows that the lack of downward flexibility of the system can be effectively compensated by the reasonable application of wind and solar curtailment strategies.

[0182] 2) When the wind power penetration rate is maintained below 30%, the lack of flexibility is relatively mild, and its expected value and probability of occurrence are low and grow slowly, which is still within the controllable range of the system. However, once the wind and solar penetration rate exceeds the 30% threshold, the expectation and probability of insufficient flexibility will rise sharply, resulting in a serious lack of flexibility, which in turn poses a major threat to the safe and stable operation of the system.

[0183] 3) According to the level of wind and solar penetration, it can be divided into two stages: low penetration (less than 30%) and high penetration (more than 30%). In the low penetration stage, it is more appropriate to use wind and solar abandonment to improve system flexibility; in the high penetration stage, it is more appropriate to enhance system flexibility through pumped storage technology.

[0184] The present invention focuses on the system-level downward flexibility assessment and its needs, and demonstrates the intrinsic connection between downward flexibility and economy. The proposed new energy consumption flexibility assessment method considering the regulating role of pumped storage power stations analyzes the downward flexibility improvement method under different wind and solar penetration rates more comprehensively and deeply than other methods. It not only incorporates the phenomenon of wind and solar abandonment into the consideration of flexibility assessment, but also innovatively introduces the regulating role of pumped storage power stations, and constructs a flexibility assessment system that comprehensively considers the characteristics of new energy power generation and the synergistic effect of pumped storage power stations. This method can more accurately assess the flexibility needs of the power system, optimize the allocation of power resources, reduce energy waste, and improve the economy and reliability of the power system. It provides a strong reference for engineering practice to select the most appropriate downward flexibility improvement plan in different application scenarios. Through this method, more effective decision-making support can be provided to power system operators to promote the efficient use of new energy and the sustainable development of the power system.

[0185] In order to make it easier for ordinary technicians in the field to understand the improvements of the present invention over the prior art, some drawings and descriptions of the present invention have been simplified, and the above-mentioned embodiments are preferred implementation schemes of the present invention. In addition, the present invention can also be implemented in other ways. Any obvious replacement without departing from the concept of the present technical solution is within the protection scope of the present invention.

Claims

1. A method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations, characterized in that: The following steps are involved: (1) Generate output scenarios with different probabilities; (2) Determine the flexibility requirements for each scenario based on the day-ahead output plan; (3) Combined with supply capacity, obtain flexibility supply and demand relationship and flexibility evaluation indicators; (4) Constructing the expectation and probability model of inflexibility deficiency; (5) Set a correction factor based on the probability of insufficient flexibility, and redistribute and evaluate the amount of wind and solar power curtailment; (6) Considering the regulating effect of pumped-storage power stations, the comprehensive evaluation index of system flexibility under different proportions of renewable energy power generation is obtained.

2. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 1 is characterized in that: In step (1), kernel density estimation and coupla function are used to generate output scenarios with different probabilities. The method includes the following steps: (1.1) Take n samples of the random variable X: x1, x2, x3, …, xn; (1.2) The wind and solar power output data are processed using the kernel density method to obtain the probability distribution function of each time period: Where: h is the window width; is the output of the wind turbine at the nth hour on the i-th day; is the photovoltaic power output at the nth hour on the i-th day; K(·) is the kernel density function; (1.3) The binary Frank-Copula function is used to model the wind and solar power output in each period to obtain its joint probability distribution function: i＝1，2，…，24 Where: F n (x i ,y i ) is the wind-solar joint distribution function in a fixed period; C(·) is the binary Frank-Copula function; u i 、v i are the distribution functions of wind power and photovoltaic units respectively; (1.4) The obtained joint distribution function is used to sample data from all fixed time periods, and the wind turbine and photovoltaic output of each time period is obtained through inverse transformation, and finally a typical daily curve is generated that takes into account the correlation and randomness of wind and photovoltaic power.

3. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 1 is characterized in that: In step (2), the flexibility requirement F i，m，t It is defined as the difference between the mth scenario and the planned output of the wind-solar cluster i at time t. When the planned power generation curve is lower than the wind-solar cluster curve, the difference is the upward flexibility demand. When the planned power generation curve is higher than the wind-solar cluster curve, the difference is the downward flexibility demand. It is expressed as follows: Where: and They respectively increase and decrease the flexibility requirement of the system at time t for the mth scenario of cluster i.

4. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 1 is characterized in that: In step (3), the flexibility supply and demand relationship obtained includes the flexibility supply of hydropower units and the flexibility supply of pumped storage units; the flexibility supply of the hydropower units is expressed as: Where: τ is the time scale; Increase flexibility supply capacity for hydropower plants; Hydropower stations reduce their flexibility supply capacity; is the ramp rate of the nth hydropower station; is the down-ramp rate of the nth hydropower station; It is the maximum output of conventional units; It is the minimum output of conventional units. Under different time scales, the adjustable range of the units is different. The pumped storage flexibility supply is expressed as: Where: The pumped storage provides upward flexibility for cluster i at time t, The pumped storage unit provides downward flexibility for cluster i at time t, is the climbing capacity of pumped storage unit i, are the upper and lower limits of the output of pumped storage unit i at time t respectively.

5. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 1 is characterized in that: In step (3), the flexibility evaluation index includes the probability of insufficient flexibility upward adjustment, the probability of insufficient flexibility downward adjustment, the expectation of insufficient flexibility upward adjustment and the expectation of insufficient flexibility downward adjustment.

6. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 5 is characterized in that: The expected and probabilistic model of inflexibility deficiency constructed in step (4) includes: Probability of insufficient flexibility increase: Where: The probability of insufficient supply capacity for cluster i in period t is adjusted upward flexibly; is a set of scenarios where the flexible upward adjustment of supply capacity is insufficient in cluster i at time t; The flexibility increase supply capacity provided by the flexibility resource to cluster i in time period t; Probability of insufficient flexibility reduction: Where: is the probability of insufficient supply capacity for cluster i in period t; A set of scenarios for cluster i to flexibly adjust its supply capacity in time period t; The flexibility of the flexible resource provided to cluster i in time period t is adjusted downward; Flexibility increase falls short of expectations: In the formula is the flexibility increase of cluster i at time t that is less than the expectation, MW; Flexibility downgraded below expectations: In the formula The flexibility of cluster i at time t is adjusted downward less than expected, MW.

7. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 6 is characterized in that: The objective function is to minimize the sum of the expected inflexibility deficiency of each cluster and the sum of the probability of inflexibility deficiency:

8. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 7 is characterized in that: The constraints on the flexibility evaluation index include flexibility adjustment capability, water balance constraint, initial and final water level constraint, reservoir water level constraint, power generation flow constraint, outflow flow constraint, and hydropower station output constraint.

9. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 1 is characterized in that: In step (5), let d k d1 is the area with the largest area of ​​insufficient flexibility adjustment capacity, and d2 is the area with the smallest area of ​​insufficient flexibility adjustment capacity. k Lower the probability of insufficient flexibility to 1 and set the correction factor to X: D=d1+d2+…+d k d k >…>d2>d1 d k >d>d1 Where: D is the sum of the areas with insufficient flexibility adjustment capacity, d is the area between d k Any region between d1 and d2, in d k The probability of insufficient downward flexibility in the area between d1 is: At this time, the allowed amount of wind and solar power abandonment is allocated according to the corrected probability: Where: W is the amount of wind and solar power that can be abandoned; W t ′ is the amount of wind and solar power abandoned at time t.

10. The method for evaluating the flexibility of new energy consumption considering the regulation effect of pumped storage power stations according to claim 9 is characterized in that: In step (6), the regulation effect of the pumped storage power station is considered as follows: in, Provide downward flexibility for pumped storage.

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