Cascade hydropower trans-provincial power transmission quantity pricing method and system in response to peak regulation demand of receiving-end power grid

Abstract

The invention discloses a pricing method and system for cascade hydropower trans-provincial power transmission quantity responding to peak regulation requirements of a receiving-end power grid, and belongs to the field of hydroelectric generation. The method comprises the following steps: dividing peak, flat and valley time periods of electricity price of a receiving end province, and drawing up a feasible time-of-use electricity price scheme set; establishing a cascade hydropower multi-province power generation model; and finally, inputting the time-of-use electricity price scheme into a cascade hydropower multi-province power generation model, calculating a 24-hour outgoing output curve of cascade hydropower, calculating two evaluation indexes of the power purchase cost and the peak regulation effect of a receiving-end power grid, optimizing the time-of-use electricity price scheme through a non-dominated sorting algorithm, setting index weights, and defining a preference function, and selecting the scheme with the minimum preference function value as the optimal time-sharing pricing scheme. Under the condition that the maximum power generation income is met, response to the peak regulation requirement of the receiving-end power grid is effectively promoted, self-generated power and electric quantity balance of the sending end and the receiving end at the hour level is achieved, the power purchase cost of the receiving-end power grid is controllable, and the win-win situation of the power plant and the receiving-end power grid is achieved.

Description

Technical Field

[0001] The invention belongs to the field of hydropower generation, and relates to a pricing method and system for cascade hydropower inter-provincial power transmission in response to the peak-shaving demand of a receiving-end power grid. Background Art

[0002] Hydropower is the clean power source with the largest annual electricity generation in my country, mainly concentrated in the southwest region and the Three Gorges Basin, while my country's power load centers are mainly concentrated in the eastern and southeastern coastal provinces. Hydropower resources and load centers show a significant inverse distribution feature.

[0003] In the traditional inter-provincial power transmission model, the power transmission and receiving parties sign a long-term power transmission agreement on an annual basis, agreeing on the monthly power transmission volume and power transmission price. According to the power transmission agreement, part of the power generated by hydropower stations in the southwest region is transmitted to the receiving provinces, while the other part remains in the province. When power is transmitted, the 24-hour transmission process is usually very smooth, and the power transmission output curve is expressed as a horizontal straight line or a segmented horizontal straight line, and the electricity price is fixed in each period.

[0004] In recent years, with the rapid growth of new energy power stations such as wind power and photovoltaic power in my country, the output of new energy has strong volatility, resulting in a rapid increase in the peak-shaving demand of the receiving power grid. In view of the excellent regulation performance of hydropower, the receiving power grid urgently needs external hydropower to change the power transmission mode and flexibly adjust its 24-hour external transmission output curve every day to respond to the peak-shaving demand of the receiving power grid in real time. At the same time, the pilot of the power spot market in the sending provinces in the southwest region has been launched, and the sending hydropower can participate in the power spot transaction in the province. In the spot market, when the peak-shaving demand of the power grid is strong, the electricity price will increase significantly. The hydropower station can obtain higher power generation income by generating more electricity at this time, which means that responding to the peak-shaving demand of the receiving power grid with a fixed electricity price at this time will bring huge economic losses, which violates the original intention of the enterprise's power production. Therefore, the power generation strategy of the sending-end hydropower and the peak-shaving demand of the receiving-end power grid have produced a real contradiction. So far, there is no good technical solution. How to formulate a new price according to the actual power supply and demand characteristics is the breakthrough idea given by the present invention. Summary of the invention

[0005] The present invention provides a pricing method and system for cascade hydropower interprovincial power transmission that responds to the peak-shaving demand of the receiving power grid. It is a new pricing method and its supporting system, which innovates the pricing model of traditional power transmission. According to the peak-shaving demand of the receiving power grid, the power generation characteristics of cascade hydropower and other engineering conditions, the present invention adopts a time-of-use electricity price to express the electricity price scheme, and provides a method for determining this time-of-use electricity price scheme. The pricing scheme provided can effectively promote the response of cascade hydropower to the peak-shaving demand of the receiving power grid under the condition of maximizing the power generation revenue of cascade hydropower in multiple provinces, and achieve the balance of self-generated electricity at the hourly level between the power sending end and the receiving end, and the power purchase cost of the receiving power grid is controllable, so as to achieve a win-win situation for the hydropower station and the receiving power grid. The pricing method provided by the present invention is simple and easy to implement, and the application cases show that it can significantly improve the balance of power supply and demand. The present invention can provide a technical reference for the external transmission of power to adapt to the transformation of power production mode.

[0006] Technical solution of the present invention:

[0007] On the one hand, the present invention provides a pricing method for the inter-provincial transmission of cascade hydropower in response to the peak-shaving demand of the receiving power grid. The pricing method includes: first, dividing the peak, flat and valley periods of electricity prices in the receiving provinces, and formulating a feasible set of time-of-use electricity price schemes; then establishing a multi-province power generation model for cascade hydropower; finally, inputting the time-of-use electricity price scheme into the multi-province power generation model for cascade hydropower, calculating the 24-hour transmission output curve of cascade hydropower, calculating two evaluation indicators, the power purchase cost and peak-shaving effect of the receiving power grid, using the 24-hour transmission output curve, optimizing the time-of-use electricity price scheme through a non-dominated sorting algorithm, setting indicator weights and defining a preference function, and selecting the scheme with the smallest preference function value as the optimal time-of-use pricing scheme. The pricing method specifically includes the following steps:

[0008] Step 1: Formulate a feasible set of time-of-use electricity price plans.

[0009] First, the peak, flat and valley periods of electricity prices are divided according to the actual load demand of the receiving provinces; then, the range of values ​​of the tiered electricity prices and the values ​​to be used are determined based on actual engineering experience; finally, the Cartesian product is used to generate alternative time-of-use electricity price schemes and obtain a set of time-of-use electricity price schemes. Specifically:

[0010] Step 1.1: Divide the peak, flat and valley periods of electricity prices in the receiving provinces based on the triangular fuzzy membership function.

[0011] Considering 24 hours a day as 24 time periods, the time period vector is recorded as T = {1, ..., t, ..., 24}, and the corresponding load value of the receiving province is L = {l1, ..., l t , ..., l 24The daily average value sequence of the 24-hour load curve in a typical year in the receiving province is collected, and the triangular fuzzy membership functions of the peak, flat and valley periods are constructed respectively. The parameters are selected as the maximum, minimum and average values ​​of the daily average value sequence of the 24-hour load curve in the receiving province. The three membership function values ​​of each period are calculated, and the period type corresponding to the maximum value of the three membership function values ​​is the period type of the period.

[0012] Step 1.2: Determine the electricity price to be selected in the receiving province.

[0013] First, based on actual engineering experience, the upper and lower limits of electricity prices during peak, flat and valley periods in the receiving provinces are determined respectively, and the electricity price ranges during peak, flat and valley periods are obtained.

[0014] Then, each electricity price interval is discretized with the same step size, and the discrete points are used as the discrete values ​​of the electricity price to be adopted. The number of peak, flat and valley electricity prices to be adopted is N respectively. 峰 、N 平 、N 谷 .

[0015] Step 1.3: Generate a set of time-of-use electricity price plans.

[0016] Step 1.3.1: Generate a three-dimensional Cartesian product based on the discrete values ​​of peak, flat and valley electricity prices obtained in step 1.2. Each element of the three-dimensional Cartesian product is an array containing the peak, flat and valley electricity prices. The total number of elements of the three-dimensional Cartesian product N = N 峰 ·N 平 ·N 谷

[0017] Step 1.3.2: Expand the ternary electricity price in each element of the three-dimensional Cartesian product to 24 hours according to the peak, flat and valley time periods divided in step 1.1 to obtain the corresponding 24-hour time-of-use electricity price plan. Then, N elements correspond to N time-of-use electricity price plans to form a time-of-use electricity price plan set.

[0018] Step 2: Construct a multi-province generation model of cascade hydropower.

[0019] The multi-province power generation model of cascade hydropower is used to simulate the power transmission behavior of cascade hydropower under a given time-of-use electricity price scheme, wherein the multiple provinces include the province where the cascade hydropower is located (referred to as "the province") and the province where the cascade hydropower receives electricity through inter-provincial power transmission (referred to as "the receiving province"). When cascade hydropower participates in multi-province power transmission, the primary goal is power generation revenue. At the same time, it is necessary to meet physical requirements including the ratio of power in the province to power transmitted, hydraulic relations, and operating restrictions of high-voltage DC transmission lines. Specifically, the following steps are included:

[0020] Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces.

[0021] The objective function is constructed with the goal of maximizing the comprehensive benefits of cascade hydropower transmission within the province and to the receiving provinces, as shown in equations (1)-(2):

[0022]

[0023] Where: E is the comprehensive benefit of cascade hydropower transmission in the province and the receiving province; is the electricity price of the province in period t; The agreed time-of-use electricity price between the cascade hydropower and the receiving province in period t is the electricity price that needs to be finally determined; is the power output of hydropower station i in the province during period t; is the output of hydropower station i at period t; peak , plain , valley They are the time-of-use electricity prices for the peak, flat and valley periods to be determined respectively; k t valley They are 0 and 1 variables corresponding to the peak, flat and valley periods. When it is 1, other integer variables are 0. When it is 1, other integer variables are 0. When it is in the valley period k t valley When it takes 1, other integer variables take 0; Δt is the time period length, i.e. 1 hour; T is the total number of time periods in a year.

[0024] Step 2.2: Construct power constraints for multi-province power transmission.

[0025] Step 2.2.1: Construct the power constraints for multi-province power transmission.

[0026] In order to ensure that the sum of the power transmission in the province and the power transmission outside the cascade hydropower is equal to the total power generation of the cascade hydropower, the constraint condition is constructed as shown in formula (3):

[0027]

[0028] Where: N i，t is the output of hydropower station i in period t.

[0029] Step 2.2.2: Construct power distribution ratio constraints.

[0030] According to the current power transmission requirements, the ratio of the total power transmission in the province to the total power transmission should be a certain value each month. Therefore, the constraint on the ratio of power transmission in the province to that in other provinces is established as shown in formula (4):

[0031]

[0032] Where: M mis the time period set of the mth month; k m It is the ratio of the power output of the province to that of other provinces in the mth month, and is a constant determined before power transmission.

[0033] Step 2.3: Construct hydraulic constraints.

[0034] Step 2.3.1: Construct water balance constraints, as shown in equations (5) and (6):

[0035]

[0036] Q i，t =G i，t +S i，t (6)

[0037] Where: V i，t I is the initial storage capacity of hydropower station i in the tth period; i，t , Q i，t , G i，t , S i，t are the inflow, outflow, power generation and abandoned water flow of hydropower station i in period t respectively; U i is the set of upstream power stations of hydropower station i, and the leading power station is an empty set; Q u，t is the power generation flow of the upstream hydropower station u in the tth period; d u，i Δt is the water flow delay from the upstream hydropower station u to the hydropower station i; s The number of seconds for each period.

[0038] Step 2.3.2: Construct the traffic boundary constraint, as shown in equations (7) and (8):

[0039]

[0040] Where: and are the upper and lower limits of the outflow of hydropower station i in period t, respectively; and are the upper and lower limits of the power generation flow of hydropower station i respectively.

[0041] Step 2.3.3: Construct the storage capacity boundary constraint, as shown in formula (9):

[0042] V i min ≤V i，t ≤V i max (9)

[0043] Where: V i max and V i min are the upper and lower limits of the storage capacity of hydropower station i respectively.

[0044] Step 2.3.4: Describe the power generation function of the hydropower station, as shown in formula (10):

[0045] Q i，t =η i，t N i，t (10)

[0046] Where: η i，t is the water consumption rate of hydropower station i in period t.

[0047] Step 2.4: Construct the operation constraints of the HVDC interconnection line.

[0048] Step 2.4.1: To ensure that the amount of electricity transmitted does not exceed the upper and lower limits of the transmission capacity of the transmission channel, construct the upper and lower limit constraints of the channel capacity, as shown in formula (11):

[0049]

[0050] Where: is the output transmitted through the kth high-voltage DC interconnection line in the tth period; are the upper and lower output constraints of the kth HVDC interconnection line.

[0051] Step 2.4.2: To ensure that the power adjustment amplitude between adjacent time periods does not exceed the maximum adjustment range allowed by the high-voltage DC interconnection line, a power adjustment amplitude constraint is constructed, as shown in equations (12) to (14):

[0052]

[0053] Where: P k，t is the transmission power of the high-voltage DC tie line k in the tth period; ΔP k down Adjust the power upper limit upward and downward for the high-voltage DC tie line k respectively; They are 0-1 variables representing whether the high-voltage DC tie line k is adjusted upward or downward in the tth period, and adjustment is 1, and no adjustment is 0. Equations (12) and (13) represent the amplitude constraints of the upward and downward adjustments of the high-voltage DC tie line between two adjacent periods, and equation (14) represents the unidirectional adjustment of power.

[0054] Step 2.4.3: To ensure that the transmission power of the high-voltage DC interconnection line cannot be reversely adjusted between adjacent time periods, a reverse adjustment restriction constraint between adjacent time periods is constructed, such as equations (15) and (16):

[0055]

[0056] Step 2.4.4: To ensure that the transmission power of the high-voltage DC interconnection line will not be adjusted frequently within a day, a constraint on the number of times the transmission line is adjusted is constructed, such as equations (17) and (18):

[0057]

[0058] Where: and are the maximum upward and downward times of the HVDC tie line k in one day; D d is the time period set of the dth day; Equations (17) and (18) ensure that the transmission power cannot be adjusted frequently within a day, thus ensuring the operational reliability of the high-voltage DC interconnection line.

[0059] Step 3: Optimize the time-of-use electricity price plan.

[0060] Step 3.1: Obtain the effects of different time-of-use electricity price plans.

[0061] All time-of-use electricity price schemes generated in step 1 are used as input conditions, and the cascade hydropower multi-province power generation model constructed in step 2 is used for optimization calculation to obtain the 24-hour transmission output curve of cascade hydropower under different time-of-use electricity price schemes. The power purchase cost and peak-shaving effect of the receiving power grid are calculated according to the power generation in each period corresponding to the 24-hour transmission output curve. The calculation formula of the power purchase cost C is as shown in formula (19), and the calculation evaluation index of the peak-shaving effect is selected from the peak-to-valley difference, variance, average distance, maximum value and load rate of the residual load of the receiving power grid.

[0062]

[0063] Step 3.2: Obtain the optimal time-of-use electricity price scheme family.

[0064] Taking the power purchase cost and peak load regulation effect of the receiving power grid under different time-of-use electricity price schemes as evaluation indicators, the Pareto frontier scheme under these two evaluation indicators is found based on the non-dominated sorting algorithm, and the corresponding time-of-use electricity price schemes under the Pareto frontier are combined into the optimal time-of-use electricity price scheme family. Specifically:

[0065] Step 3.2.1: Combine the power purchase cost and peak load regulation effect of the receiving power grid under each time-of-use electricity price scheme in the time-of-use electricity price scheme set into N sets of scheme data sets Among them, C r is the electricity purchase cost of the receiving power grid under the time-of-use electricity price scheme r, V r It is the peak regulation effect of the receiving power grid under the time-of-use electricity price scheme r.

[0066] Step 3.2.2: Determine the dominance relationship: For any two time-of-use electricity price schemes a and b, if the two inequalities If both are strictly established, then the time-of-use electricity price plan a is said to dominate the time-of-use electricity price plan b.

[0067] Step 3.2.3: Traverse all time-of-use electricity price schemes, determine the dominance relationship in pairs, mark the time-of-use electricity price schemes that are not dominated by other schemes as the Pareto frontier Γ of the first layer, iteratively screen the schemes in Γ, and remove the dominated time-of-use electricity price schemes in Γ after each iteration until all time-of-use electricity price schemes are screened, and the remaining time-of-use electricity price schemes in Γ are combined into the optimal time-of-use electricity price scheme family.

[0068] Step 3.3: Determine the final time-of-use electricity price plan.

[0069] According to the economic conditions and peak load demand of the receiving provinces, a balanced evaluation model is established to determine the final time-of-use electricity price plan, which includes the following steps:

[0070] Step 3.3.1: Normalize the two evaluation index data of power purchase cost and peak load regulation effect to ensure the comparability between the indicators, as shown in formula (20):

[0071]

[0072] Where: y j , y′ j , They are the normalized value, current value, minimum value, and maximum value of the j evaluation index respectively.

[0073] Step 3.3.2: Define the preference function ω j Represents the importance weight of the j-th evaluation indicator, which is determined according to the economic conditions and peak-shaving demand of the receiving province.

[0074] Step 3.3.3: For each time-of-use electricity price scheme in the optimal time-of-use electricity price scheme family, calculate its preference function value, and select the time-of-use electricity price scheme with the smallest preference function value as the final time-of-use electricity price scheme.

[0075] The present invention also provides a pricing system for cascade hydropower interprovincial power transmission in response to the peak-shaving demand of the receiving-end power grid, which is used to call computer resources to implement the above pricing method. The pricing system includes 4 modules:

[0076] Module 1: Time-of-use electricity price scheme set determination module.

[0077] This module takes the actual load demand of the receiving province and the upper and lower limits of electricity prices during peak, flat and valley periods as input, divides the electricity prices of the receiving province into peak, flat and valley periods, calculates and generates time-of-use electricity price plans, forms a set of time-of-use electricity price plans, and outputs them.

[0078] Module 2: Construction and calculation module of cascade hydropower multi-province power generation model, which includes two sub-modules:

[0079] Module 2.1 is a module for constructing a cascade hydropower multi-province power generation model. It uses the allocation ratio of the cascade hydropower generation in the province and that transmitted, the initial and final storage capacity of the power station, the water consumption rate of the power station and the capacity of the transmission channel, the adjustment amplitude, the upper limit of the number of adjustments, and the provincial electricity price as parameters, and calls a mature mathematical optimization modeling tool to construct the cascade hydropower multi-province power generation model described in step 2.

[0080] Module 2.2 is a calculation module for the cascade hydropower multi-province power generation model. It is based on the cascade hydropower multi-province power generation model provided by module 2.1, and provides an input interface for time-of-use electricity price schemes. After obtaining the input time-of-use electricity price scheme, it automatically calculates the cascade hydropower multi-province power generation model; after the calculation is completed, it outputs the 24-hour transmission output curve information calculated for the given time-of-use electricity price scheme.

[0081] Module 3: Optimal time-of-use electricity price family determination module.

[0082] This module is used to execute steps 3.1 and 3.2 in the pricing method. First, each time-of-use electricity price scheme in the set of time-of-use electricity price schemes output by module 1 is obtained and input into module 2.2 as input data; then, the power purchase cost and peak-shaving effect of the receiving power grid are calculated according to the results returned by module 2.2; finally, according to the power purchase cost and peak-shaving effect information of the receiving power grid under all schemes, step 3.2 is executed to determine the optimal time-of-use electricity price scheme family and output it.

[0083] Module 4: Final pricing module.

[0084] This module takes the output of module 3 as input, executes step 3.3, determines the final time-of-use electricity price plan, and outputs it.

[0085] Beneficial effects of the present invention

[0086] The present invention aims to solve the problem that the current pricing scheme for electricity transmission is not compatible with the current large-scale grid connection of new energy, the electricity spot market and other industrial changes, and provides a new time-sharing pricing method and a supporting system. The present invention can calculate a reasonable time-sharing electricity price scheme based on engineering conditions such as the peak-shaving demand of the receiving power grid and the characteristics of cascade hydropower generation. The pricing scheme provided can effectively promote the response of cascade hydropower to the peak-shaving demand of the receiving power grid under the condition of maximizing the power generation revenue of cascade hydropower in multiple provinces, achieve the balance of spontaneous power generation at the hourly level between the transmitting and receiving ends, and the power purchase cost of the receiving power grid is controllable, achieving a win-win situation for the hydropower station and the receiving power grid. The present invention can provide a technical reference for the transmission of electricity to adapt to the transformation of power production methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1It is a graph of variance changes as cost increases;

[0088] Figure 2 It is the change diagram of each peak regulation effect evaluation index with cost increase, where (a) is the peak-to-valley difference of residual load in province G, (b) is the average distance of residual load in province G, (c) is the maximum value of residual load in province G, and (d) is the residual load rate in province G;

[0089] Figure 3 This is a diagram of the pricing system architecture provided by the present invention. DETAILED DESCRIPTION

[0090] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0091] The present invention is implemented below with the L River Basin (hereinafter referred to as "L River Basin") in the Y Province as the engineering background. This embodiment is implemented with the cascade hydropower consisting of two large hydropower stations A and B located in the L River Basin (hereinafter referred to as "A Hydropower Station" and "B Hydropower Station", which together constitute the L River Basin cascade hydropower) as the implementation object, and the power station parameters adopt the actual data of the A and B hydropower stations.

[0092] According to the current framework agreement, Hydropower Station A sends electricity to Province G for consumption through High Voltage DC Interconnection Line A, and Hydropower Station B sends electricity through High Voltage DC Interconnection Line B in a "grid-to-grid" manner. The power transmission limit of High Voltage DC Interconnection Line A and High Voltage DC Interconnection Line B is 5000MW. Since the spot market in Province Y has just entered trial operation and there is no full-year spot data, the Nordic spot market data is used, and corresponding adjustments are made according to the load characteristics of Province Y. The monthly ratio of intra-provincial transmission volume to inter-provincial transmission volume is converted according to the actual historical data of Province Y. This embodiment takes the actual data of fixed electricity prices for the transmission of framework agreement electricity from Province Y to Province G in a certain year as an example to implement the method of the present invention.

[0093] On one hand, this embodiment provides a pricing method for cascade hydropower inter-provincial transmission volume in response to the peak load demand of the receiving power grid. The implementation steps of the pricing method are as follows:

[0094] Step 1: Formulate a feasible set of time-of-use electricity price plans.

[0095] Step 1.1: Divide the receiving provinces into peak, flat and valley time periods based on the triangular fuzzy membership function.

[0096] Considering 24 hours a day as 24 time periods, the time period vector is recorded as T = {1, ..., t, ..., 24}, and the corresponding load value of the receiving province is L = {l1, ..., l t , ..., l 24The daily average value sequence of the 24-hour load curve of the receiving province in a typical year is collected, and the triangular fuzzy membership functions of the peak, flat and valley periods are constructed respectively. The parameters are selected as the maximum, minimum and average values ​​of the daily average value sequence of the 24-hour load curve of the receiving province:

[0097] Construct the valley period membership function, as shown in formula (21);

[0098]

[0099] Construct the membership function of the normal period, as shown in formula (22);

[0100]

[0101] Construct the peak period membership function, as shown in formula (23);

[0102]

[0103] In formulas (21) to (23), l t is the actual load data, l min is the minimum load value, l max is the maximum load value, l avg is the average value of the load, μ valley (l t ), μ plain (l t ), μ peak (l t ) are the membership functions for valley, flat and peak time periods respectively.

[0104] Calculate the three membership function values ​​of each time period. The time period type corresponding to the maximum value of the three membership function values ​​is the time period type of the time period. After calculation, the peak time periods in this embodiment are time periods 10-12 and 15-21, the normal time periods are time periods 9, 13-14 and 22-24, and the remaining time periods are valley time periods.

[0105] Step 1.2: Determine the electricity price to be selected in the receiving province.

[0106] First, based on actual engineering experience, the upper and lower limits of electricity prices during peak, flat and valley periods in the receiving provinces are determined respectively, and the electricity price ranges during peak, flat and valley periods are obtained.

[0107] Then, the same step size is used to discretize each electricity price interval, and the discrete points are used as discrete values ​​of the electricity price to be adopted. The number of peak, flat and valley electricity prices to be adopted is N respectively. 峰 、N 平 、N 谷 .

[0108] Step 1.3: Generate a set of time-of-use electricity price plans.

[0109] Step 1.3.1: Generate a three-dimensional Cartesian product based on the discrete values ​​of peak, flat and valley electricity prices obtained in step 1.2. Each element of the three-dimensional Cartesian product is an array containing the peak, flat and valley electricity prices. The total number of elements of the three-dimensional Cartesian product N = N 峰 ·N 平 ·N 谷

[0110] Step 1.3.2: Expand the ternary electricity price in each element of the three-dimensional Cartesian product to 24 hours according to the peak, flat and valley periods divided in step 1.1, and obtain the corresponding 24-hour time-of-use electricity price plan, then N The elements correspond to N The time-of-use electricity price plans constitute a time-of-use electricity price plan set.

[0111] Step 2: Construct a multi-province generation model of cascade hydropower.

[0112] Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces.

[0113] The objective function is constructed with the goal of maximizing the comprehensive benefits of cascade hydropower transmission within the province and to the receiving provinces, as shown in equations (1)-(2).

[0114] Step 2.2: Construct power constraints for multi-province power transmission.

[0115] Step 2.2.1: Construct the power constraints for multi-province power transmission.

[0116] In order to ensure that the sum of the power transmission of cascade hydropower in the province and the power transmission outside is equal to the total power generation of cascade hydropower, the constraint conditions are constructed as shown in formula (3).

[0117] Step 2.2.2: Construct power distribution ratio constraints.

[0118] According to the current power transmission requirements, the ratio of the total power transmission in the province to the total power transmission outside the province should be a certain value each month. Therefore, the constraint on the ratio of power transmission in the province to that outside the province is established as shown in formula (4).

[0119] Step 2.3: Construct hydraulic constraints.

[0120] Step 2.3.1: Construct water balance constraints, as shown in equations (5) and (6).

[0121] Step 2.3.2: Construct the flow boundary constraints, as shown in equations (7) and (8).

[0122] Step 2.3.3: Construct the storage capacity boundary constraint, as shown in formula (9).

[0123] Step 2.3.4: Describe the power generation function of the hydropower station, as shown in equation (10).

[0124] Step 2.4: Construct the operation constraints of the HVDC interconnection line.

[0125] Step 2.4.1: To ensure that the amount of power transmitted does not exceed the upper and lower limits of the transmission capacity of the transmission channel, construct the upper and lower limit constraints of the channel capacity, as shown in formula (11).

[0126] Step 2.4.2: To ensure that the power adjustment amplitude between adjacent time periods does not exceed the maximum adjustment range allowed by the high-voltage DC interconnection line, a power adjustment amplitude constraint is constructed, as shown in equations (12) to (14).

[0127] Step 2.4.3: To ensure that the transmission power of the HVDC interconnection line cannot be reversely adjusted between adjacent time periods, a reverse adjustment restriction constraint between adjacent time periods is constructed, such as equations (15) and (16).

[0128] Step 2.4.4: To ensure that the transmission power of the HVDC interconnection line will not be adjusted frequently within a day, a constraint on the number of adjustments of the transmission line is constructed, such as equations (17) and (18).

[0129] Step 3: Optimize the time-of-use electricity price plan.

[0130] Step 3.1: Obtain the effects of different time-of-use electricity price plans.

[0131] All the time-of-use electricity price schemes generated in step 1 are used as input conditions, and the cascade hydropower multi-province power generation model constructed in step 2 is used for optimization calculation to obtain the 24-hour transmission output curve of the cascade hydropower under different time-of-use electricity price schemes. The power purchase cost and peak-shaving effect of the receiving power grid are calculated according to the power generation in each period corresponding to the 24-hour transmission output curve. Among them, the calculation formula of the power purchase cost C is as shown in formula (19), and the calculation evaluation index of the peak-to-valley difference, variance, average distance, maximum value and load rate of the residual load of the receiving power grid are selected. The calculation formulas are as follows:

[0132] Residual load peak-to-valley difference:

[0133]

[0134] Where: F1 is the peak-to-valley difference of the residual load of the receiving power grid; T is the total number of dispatching periods, which is 1 day in this section; I is the total number of cascade hydropower stations participating in the dispatch; D t is the load of the receiving power grid during period t; L t is the residual load of the receiving power grid during period t.

[0135] Residual load variance:

[0136]

[0137] Where: F2 is the residual load variance of the receiving power grid.

[0138] Residual load average distance:

[0139]

[0140] Where: F3 is the average distance of residual load of the receiving power grid.

[0141] Maximum residual load:

[0142]

[0143] Where: F4 is the maximum value of the residual load of the receiving power grid.

[0144] Residual load rate:

[0145]

[0146] Where: F5 is the maximum value of the residual load of the receiving power grid.

[0147] The smaller the peak-to-valley difference of the residual load, the smaller the peak-shaving capacity demand of the residual load; the smaller the variance and mean distance of the residual load, both indicate that the residual load sequence is more stable and the output fluctuation regulation demand of other units is smaller; the smaller the maximum value of the residual load, the smaller the demand of the residual load for the peak capacity of other units; the greater the load rate of the residual load, the smaller the degree of its change. In short, the smaller the peak-to-valley difference, variance, mean distance, and maximum value of the residual load, and the greater the residual load rate, the better the peak-shaving effect.

[0148] In this embodiment, the residual load variance is used as the peak load regulation effect evaluation index, and the residual load variance and the receiving-end power grid cost under each time-of-use electricity price scheme are calculated according to formula (26) and formula (19).

[0149] Step 3.2: Obtain the optimal time-of-use electricity price scheme family.

[0150] Step 3.2.1: Combine the power purchase cost and peak load regulation effect of the receiving power grid under each time-of-use electricity price scheme in the time-of-use electricity price scheme set into N sets of scheme data sets Among them, C r is the electricity purchase cost of the receiving power grid under the time-of-use electricity price scheme r, V r It is the peak regulation effect of the receiving power grid under the time-of-use electricity price scheme r.

[0151] Step 3.2.2: Determine the dominance relationship: For any two time-of-use electricity price schemes a and b, if the two inequalities If both are strictly established, then the time-of-use electricity price plan a is said to dominate the time-of-use electricity price plan b.

[0152] Step 3.2.3: Traverse all time-of-use electricity price schemes, determine the dominance relationship in pairs, mark the time-of-use electricity price schemes that are not dominated by other schemes as the Pareto frontier Γ of the first layer, iteratively screen the schemes in Γ, remove the dominated time-of-use electricity price schemes in Γ after each iteration, until all time-of-use electricity price schemes are screened, and the remaining time-of-use electricity price schemes in Γ form the optimal time-of-use electricity price scheme family. In this embodiment, after screening, a total of 21 time-of-use electricity price schemes remain to form the optimal time-of-use electricity price scheme family.

[0153] Step 3.3: Determine the final time-of-use electricity price plan.

[0154] Step 3.3.1: Normalize the two evaluation index data of power purchase cost and peak load regulation effect to ensure the comparability between the evaluation indexes, as shown in formula (20).

[0155] Step 3.3.2: Define the preference function In this embodiment, the weights of the power purchase cost and the remaining load variance index are both set to 0.5.

[0156] Step 3.3.3: Calculate the value of the preference function for the 21 time-of-use electricity price schemes in the optimal time-of-use electricity price scheme family, and then select the time-of-use electricity price scheme with the smallest preference function value as the final time-of-use electricity price scheme. After calculation, the optimal time-of-use electricity price scheme in this embodiment is 800 yuan in the peak period, 500 yuan in the normal period, and 150 yuan in the valley period, where the peak period is period 10-12, 15-21, the normal period is period 9, period 13-14 and period 22-24, and the rest of the periods are valley periods.

[0157] This embodiment also provides a pricing system for cascade hydropower interprovincial power transmission in response to the peak load demand of the receiving power grid, which is used to call computer resources to implement the above pricing method, such as Figure 3 As shown, the pricing system includes 4 modules:

[0158] Module 1: Time-of-use electricity price scheme set determination module.

[0159] This module takes the actual load demand of the receiving province and the upper and lower limits of the electricity price during peak, flat and valley periods as input, runs the triangular fuzzy membership function and Cartesian product calculation described in step 1 of the pricing method, calculates and generates a time-of-use electricity price plan, forms a set of time-of-use electricity price plans, and outputs them.

[0160] Module 2: Construction and calculation module of cascade hydropower multi-province power generation model, which includes two sub-modules:

[0161] Module 2.1 is a module for constructing a cascade hydropower multi-province power generation model. It uses information such as the proportion of cascade hydropower generation in the province and transmitted power, the initial and final storage capacity of the power station, the water consumption rate of the power station and the capacity of the transmission channel, and the adjustment amplitude as parameters, and calls mature mathematical optimization modeling tools to construct the cascade hydropower multi-province power generation model described in step 2.

[0162] Module 2.2 is a calculation module for the cascade hydropower multi-province power generation model. It is based on the cascade hydropower multi-province power generation model provided by module 2.1, and provides an input interface for time-of-use electricity price schemes. After obtaining the input time-of-use electricity price scheme, it automatically calculates the cascade hydropower multi-province power generation model; after the calculation is completed, it outputs the 24-hour transmission output curve information calculated for the given time-of-use electricity price scheme.

[0163] Module 3: Optimal time-of-use electricity price family determination module.

[0164] This module is used to execute steps 3.1 and 3.2 in the pricing method. First, each time-of-use electricity price scheme in the set of time-of-use electricity price schemes output by module 1 is obtained and input into module 2.2 as input data; then, the power purchase cost and peak-shaving effect of the receiving power grid are calculated according to the results returned by module 2.2; finally, according to the power purchase cost and peak-shaving effect information of the receiving power grid under all schemes, step 3.2 is executed to determine the optimal time-of-use electricity price scheme family and output it.

[0165] Module 4: Final pricing module.

[0166] This module takes the output of module 3 as input, executes step 3.3, determines the final time-of-use electricity price plan, and outputs it.

[0167] Implementation results analysis:

[0168] 1) Analysis of power grid cost and peak load regulation effect;

[0169] In order to better evaluate the relationship between peak-shaving performance and economic benefits and provide a quantitative reference for the negotiation of electricity price plans between the power transmission and receiving ends, variance is selected as the peak-shaving effect evaluation index, and the indicator CVD is introduced to measure the degree of variance change caused by cost increase, as shown in formula (30). The specific meaning is the change in variance caused by unit cost change.

[0170]

[0171] Where: ΔV is the deviation of the variance between adjacent plans, and ΔC is the deviation of the total cost between adjacent plans.

[0172] According to the size of CVD, the relationship curve between cost and peak regulation effect is divided into high sensitivity area, balanced area and low sensitivity area. The average CVD of each area is 234MW. 2 / 10,000 yuan, 58MW 2 / 10,000 yuan and 12MW 2 / Ten thousand yuan. Figure 1 As shown in the figure, in the high-sensitivity area, as the cost of the receiving power grid increases, the variance decreases faster. In the balanced area, as the cost increases, the variance decreases slower than in the high-sensitivity area. In the low-sensitivity area, as the cost increases, the variance decreases more slowly. This also reflects that as the peak-shaving demand of the receiving power grid increases, the higher the peak-shaving demand, the greater the cost. Figure 2 It can be seen that similar effects are also achieved under other peak-shaving indicators. As the cost increases, the peak-to-valley difference, average distance, and maximum value of the residual load of the receiving power grid all decrease, and the residual load rate increases. As the cost increases, the CVD changes smaller and smaller. That is to say, as the peak-shaving demand continues to increase, it will cost more to achieve the same peak-shaving effect. The above conclusions provide a quantitative reference for the negotiated electricity price schemes of the sending and receiving power grids. Therefore, in order to help the sending and receiving provinces balance the cost and peak-shaving demand and select the only optimal time-of-use electricity price scheme, the present invention adopts the method of setting indicator weights, which is determined according to the economic conditions of the receiving provinces and the degree of peak-shaving demand. In this embodiment, the weights of the two indicators are set to 0.5, and the only optimal time-of-use electricity price scheme is selected from the optimal time-of-use electricity price scheme family, which is 800 yuan for peak time, 500 yuan for normal time, and 150 yuan for valley time.

[0173] 2) Effectiveness analysis;

[0174] To verify the effectiveness of the present invention, the final time-of-use electricity price scheme determined in this embodiment is compared with the fixed electricity price scheme in the traditional framework agreement, and the peak load regulation results of the two schemes are calculated. The descriptions of the two schemes are as follows:

[0175] Time-of-use electricity price plan: The electricity within the framework agreement is sold according to the final time-of-use electricity price plan determined in this embodiment.

[0176] Fixed electricity price plan: The electricity within the framework agreement is sold at a fixed price, and the fixed electricity price adopts the actual electricity price data of the framework agreement in the same year as this embodiment.

[0177] As shown in Table 1, the original load in the table is the actual data of the original load in the receiving province in that year. Under the two models, the various peak-shaving effect evaluation indicators throughout the year are statistically analyzed. It can be seen that the peak-shaving indicators of the time-of-use electricity price scheme are improved compared with the fixed electricity price scheme. In terms of reducing the peak-to-valley difference of the residual load, the peak-to-valley difference of the residual load of the time-of-use electricity price scheme is reduced by 7.63% compared with the fixed electricity price scheme. In terms of improving the stability of the residual load, the variance of the residual load is reduced by 18.18%, and the average distance of the residual load is reduced by 10.46%. In terms of reducing the maximum value of the residual load, the maximum value of the residual load is reduced by 1.08%. In terms of improving the degree of change of the residual load, the residual load rate is increased by 1.19%. In terms of electricity cost, the cost of the receiving-end power grid increased by 11.96%. It can be seen that the effect of increasing the external transmission income of the sending-end hydropower station is achieved. Although the cost of the receiving-end power grid increases, the effect of peak-shaving demand is met under the premise of controllable cost, and finally the balance of interests between the sending-end power station and the receiving-end power grid is achieved. It can be seen that the present invention can achieve price coordination of the electricity in the framework agreement between the sender and the receiver and meet the peak load demand of the receiving power grid, thereby achieving a win-win effect for both the sender and the receiver.

[0178] Table 1: Statistical indicators of peak load regulation effects of various schemes

[0179]

[0180] In summary, the present invention can provide a method for price coordination between senders and receivers and formulation of cascade hydropower transmission plans in the cascade hydropower transmission market in response to the peak-shaving demand of the receiving power grid. The provided method can bring better peak-shaving effects than traditional models.

Claims

1. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid, characterized in that: The pricing method includes: firstly, dividing the peak, flat and valley periods of electricity prices in the receiving provinces, and formulating a feasible set of time-of-use electricity price schemes; then establishing a multi-province power generation model of cascade hydropower; finally, inputting the time-of-use electricity price scheme into the multi-province power generation model of cascade hydropower, calculating the 24-hour transmission output curve of cascade hydropower, calculating two evaluation indicators of the receiving power grid's power purchase cost and peak regulation effect from the 24-hour transmission output curve, optimizing the time-of-use electricity price scheme through a non-dominated sorting algorithm, setting indicator weights and defining a preference function, and selecting the scheme with the smallest preference function value as the optimal time-of-use pricing scheme.

2. According to claim 1, a pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid, characterized in that: The pricing method specifically includes the following steps: Step 1: Formulate a feasible set of time-of-use electricity price plans; Step 1.1: Divide the peak, flat and valley periods of electricity prices in the receiving provinces based on the triangular fuzzy membership function; Consider a 24-hour day as 24 time periods, and the time period vector is recorded as , the corresponding load value of the receiving province is ; The daily average value sequence of the 24-hour load curve in the receiving province in a typical year is collected, and the triangular fuzzy membership functions of the peak, flat and valley periods are constructed respectively. The three membership function values ​​of each period are calculated, and the period type corresponding to the maximum value is the period type of the period. Step 1.2: Determine the electricity price to be selected in the receiving province; First, based on actual engineering experience, the upper and lower limits of the peak, flat and valley electricity prices in the receiving provinces are determined, and the peak, flat and valley electricity price ranges are obtained; Then, each electricity price interval is discretized with the same step size, and the discrete points are used as the discrete values ​​of the electricity price to be adopted. The number of peak, flat and valley electricity prices to be adopted are , , ; Step 1.3: Generate a set of time-of-use electricity price plans; Step 1.3.1: Generate a three-dimensional Cartesian product based on the discrete values ​​of the electricity price obtained in step 1.

2. Each element of the three-dimensional Cartesian product is an array containing the peak, flat and valley electricity prices. The total number of elements is ; Step 1.3.2: Expand the ternary electricity price in each element of the three-dimensional Cartesian product to 24 hours according to the peak, flat and valley periods divided in step 1.1, and obtain the corresponding 24-hour time-of-use electricity price plan. The time-of-use electricity price schemes constitute a set of time-of-use electricity price schemes; Step 2: Construct a multi-province generation model of cascade hydropower; Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces; The objective function is constructed with the goal of maximizing the comprehensive benefits of cascade hydropower transmission in the province and to the receiving provinces: （1） （2） Where: The comprehensive benefits of cascade hydropower in transmitting electricity in the province and in the receiving provinces; For the The electricity price in the province during the time period; For the The time-of-use electricity price agreed upon by the cascade hydropower and the receiving provinces for the "West-to-East Power Transmission" agreement is the electricity price that needs to be finally determined; For hydropower station In the The province's contribution during the period; For hydropower station In the The output of the time period; , , They are the time-of-use electricity prices for the peak, flat and valley periods to be determined respectively; , , They are 0 and 1 variables corresponding to the peak, flat and valley periods. When it is 1, other integer variables are 0. When it is 1, other integer variables are 0. When it takes 1, other integer variables take 0; is the duration of the session, i.e. 1 hour; is the total number of time periods throughout the year; Step 2.2: Construct power constraints for multi-province power transmission; Step 2.2.1: Construct the power constraints for multi-province power transmission; In order to ensure that the sum of the power transmission of cascade hydropower in the province and the power transmission outside is equal to the total power generation of cascade hydropower, the constraint conditions are constructed: （3） Where: For hydropower station In the Output during the time period; Step 2.2.2: Construct power distribution ratio constraints; Establish constraints on the ratio of electricity delivered to the province and to other provinces: （4） Where: For the Monthly time period collection; For the The monthly ratio of electricity generated in the province to electricity transmitted to other provinces is a constant determined before transmission; Step 2.3: Construct hydraulic constraints; Step 2.3.1: Construct water balance constraints: （5） （6） Where: For hydropower station In the The initial storage capacity of the time period; , , , Hydropower Station In the Inflow, outflow, power generation and abandoned water flows during the time period; For hydropower station The set of upstream power stations, and the leading power station is an empty set; For upstream hydropower station In the The power generation flow during the period; For upstream hydropower station To the hydroelectric power station When the water flow is stagnant; is the number of seconds for each period; Step 2.3.2: Construct flow boundary constraints: （7） （8） Where: and Hydropower Station In the The upper and lower limits of the outbound flow in the time period; and Hydropower Station The upper and lower limits of power generation flow; Step 2.3.3: Construct storage capacity boundary constraints: （9） Where: and Hydropower Station The upper and lower limits of storage capacity; Step 2.3.4: Describe the power generation function of the hydropower station: （10） Where: For hydropower station In the Water consumption rate during the period; Step 2.4: Construct the operation constraints of the HVDC interconnection line; Step 2.4.1: To ensure that the amount of power transmitted does not exceed the upper and lower limits of the transmission capacity of the transmission channel, construct the upper and lower limit constraints of the channel capacity: （11） Where: For the Period through The output of high-voltage DC interconnection lines; , For the The upper and lower limits of the output of the high-voltage DC interconnection lines; Step 2.4.2: To ensure that the power adjustment amplitude between adjacent time periods does not exceed the maximum adjustment range allowed by the high-voltage DC interconnection line, construct a power adjustment amplitude constraint: （12） （13） （14） Where: High voltage DC interconnection line No. The transmission power of the time period; , High voltage DC interconnection line Adjust the power limit upward or downward; , Represents high voltage DC interconnection lines In the A 0-1 variable indicating whether the time period is adjusted upward or downward, if adjusted, it is 1, and if not adjusted, it is 0; Equations (12) and (13) represent the amplitude constraints of the upward and downward adjustments between two adjacent time periods of the high-voltage DC interconnection line, and Equation (14) represents the unidirectional adjustment of power; Step 2.4.3: To ensure that the transmission power of the HVDC interconnection line cannot be reversely adjusted between adjacent time periods, a reverse adjustment restriction constraint is constructed for adjacent time periods: （15） （16） Step 2.4.4: To ensure that the transmission power of the high-voltage DC interconnection line is not adjusted frequently within a day, a constraint on the number of times the transmission line is adjusted is constructed: （17） （18） Where: and High voltage DC interconnection line The maximum number of up- and down-adjustments in a day; For the A collection of time periods of the day; Step 3: Optimize the time-of-use electricity price scheme; Step 3.1: Obtain the effects of different time-of-use electricity price plans; The time-of-use electricity price scheme generated in step 1 is used as an input condition, and the cascade hydropower multi-province power generation model constructed in step 2 is used for optimization calculation to obtain the 24-hour transmission output curve of the cascade hydropower under different time-of-use electricity price schemes. According to the power generation in each period corresponding to the 24-hour transmission output curve, the power purchase cost and peak regulation effect of the receiving power grid are calculated; Step 3.2: Obtain the optimal time-of-use electricity price scheme family; Taking the power purchase cost and peak load regulation effect of the receiving power grid under different time-of-use electricity price schemes as evaluation indicators, the Pareto frontier schemes under these two evaluation indicators are found based on the non-dominated sorting algorithm, and the corresponding time-of-use electricity price schemes under the Pareto frontier are combined into an optimal time-of-use electricity price scheme family; Step 3.3: Determine the final time-of-use electricity price plan; Step 3.3.1: Normalize the two evaluation index data of power purchase cost and peak load regulation effect; Step 3.3.2: Define the preference function , Representative The normalized value of the evaluation index is Representative The importance weight of each evaluation indicator is determined according to the economic conditions and peak load demand of the receiving province; Step 3.3.3: For each time-of-use electricity price scheme in the optimal time-of-use electricity price scheme family, calculate its preference function value, and select the time-of-use electricity price scheme with the smallest preference function value as the final time-of-use electricity price scheme.

3. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid according to claim 2, characterized in that: In the step 1.1, the parameters in the membership function are selected as the maximum value, minimum value and average value of the daily average value sequence of the 24-hour load curve of the receiving province.

4. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid according to claim 2, characterized in that: In step 3.1, the calculation formula of the electricity purchase cost C is as follows: （19）。 5. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid according to claim 2, characterized in that: In the step 3.1, the calculation evaluation index of the peak regulation effect is selected from the peak-to-valley difference, variance, average distance, maximum value and load rate of the residual load of the receiving-end power grid.

6. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid according to claim 2, characterized in that: The step 3.2 is specifically as follows: Step 3.2.1: Combine the power purchase cost and peak load regulation effect of the receiving power grid under each time-of-use power price scheme in the time-of-use power price scheme set Group Schema Dataset in, Time-of-use electricity pricing scheme The power purchase cost of the receiving power grid is Time-of-use electricity pricing scheme The peak load regulation effect of the downstream receiving power grid; Step 3.2.2: Determine the dominance relationship: For any two time-of-use electricity price plans and time-of-use electricity pricing scheme , if two inequalities If all are strictly established, it is called a time-of-use electricity price scheme Control time-of-use electricity price plan ; Step 3.2.3: Traverse all time-of-use electricity price schemes, determine the dominance relationship in pairs, and mark the time-of-use electricity price scheme that is not dominated by other schemes as the Pareto frontier of the first layer , iterative screening Medium solution, remove after each iteration The time-of-use electricity price schemes that have been controlled in the The remaining time-of-use electricity price schemes finally constitute the optimal time-of-use electricity price scheme family.

7. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak load demand of the receiving power grid according to claim 2, characterized in that: In step 3.3.1, the two evaluation index data of power purchase cost and peak load regulation effect are normalized by the following formula: （20） Where: , , They are The current value, minimum value, and maximum value of the evaluation index after normalization.

8. A pricing system for cascade hydropower interprovincial transmission volume in response to the peak-shaving demand of the receiving power grid, used to call computer resources to implement the pricing method described in any one of claims 1 to 7, characterized in that: The pricing system includes 4 modules: Module 1: Time-of-use electricity price scheme set determination module; This module takes the actual load demand of the receiving province and the upper and lower limits of the electricity price during the peak, flat and valley periods as input, divides the electricity price of the receiving province into peak, flat and valley periods, calculates and generates the time-of-use electricity price plan, forms a set of time-of-use electricity price plans, and outputs them; Module 2: Construction and calculation module of cascade hydropower multi-province power generation model, which includes two sub-modules: Module 2.1 is a module for constructing a cascade hydropower multi-province power generation model. It uses the proportion of cascade hydropower generation in the province and the external transmission generation, the initial and final storage capacity of the power station, the water consumption rate of the power station and the external transmission channel capacity, the adjustment amplitude, the upper limit of the number of adjustments, and the provincial electricity price as parameters, and calls a mature mathematical optimization modeling tool to construct the cascade hydropower multi-province power generation model described in step 2; Module 2.2 is a calculation module for the cascade hydropower multi-province power generation model. Based on the cascade hydropower multi-province power generation model provided by module 2.1, it provides an input interface for the time-of-use electricity price scheme. After obtaining the input time-of-use electricity price scheme, it automatically calculates the cascade hydropower multi-province power generation model. After the calculation is completed, it outputs the 24-hour transmission output curve information under the given time-of-use electricity price scheme. Module 3: Optimal time-of-use electricity price family determination module; This module is used to execute steps 3.1 and 3.2 in the pricing method; first, each time-of-use electricity price scheme in the set of time-of-use electricity price schemes output by module 1 is obtained and input into module 2.2 as input data; then, the electricity purchase cost and peak-shaving effect of the receiving power grid are calculated according to the result returned by module 2.2; finally, according to the electricity purchase cost and peak-shaving effect information of the receiving power grid under all time-of-use electricity price schemes, step 3.2 is executed to determine the optimal time-of-use electricity price scheme family and output it; Module 4: Final pricing module; This module takes the output of module 3 as input, executes step 3.3, determines the final time-of-use electricity price plan, and outputs it.

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