A pricing method and system for cascade hydropower interprovincial transmission capacity in response to peak-shaving demand of receiving power grid

Abstract

The present invention discloses a pricing method and system for cascade hydropower interprovincial power transmission that responds to the peak-shaving demand of the receiving power grid, and belongs to the field of hydropower generation. First, the peak, flat and valley periods of electricity prices in the receiving provinces are divided, and a feasible set of time-of-use electricity price schemes is formulated; then a cascade hydropower multi-province power generation model is established; finally, the time-of-use electricity price scheme is input into the cascade hydropower multi-province power generation model, and after calculating the 24-hour external transmission output curve of the cascade hydropower, two evaluation indicators, namely the power purchase cost and the peak-shaving effect of the receiving power grid, are calculated. The time-of-use electricity price scheme is optimized through a non-dominated sorting algorithm, and the indicator weights are set and a preference function is defined. The scheme with the smallest preference function value is selected as the optimal time-of-use pricing scheme. Under the condition of meeting the maximum power generation income, the present invention effectively promotes its response to the peak-shaving demand of the receiving power grid, realizes the balance of spontaneous power generation between the sending end and the receiving end at the hourly level, and the power purchase cost of the receiving power grid is controllable, thereby achieving a win-win situation for the power plant and the receiving power grid.

Description

Technical Field

[0001] The present invention belongs to the field of hydropower generation, and relates to a pricing method and system for cascade hydropower interprovincial transmission volume that responds to the peak regulation demand of a receiving power grid. Background Art

[0002] Under the traditional interprovincial power transmission model, the power transmission and receiving parties sign long-term power transmission agreements on an annual basis, stipulating monthly power transmission volumes and prices. Hydropower stations in southwestern China transmit a portion of their electricity to the receiving provinces according to these agreements, while the remainder remains within their own provinces. When power is transmitted, the 24-hour transmission process is typically very smooth, with the transmission output curve showing a horizontal line or segmented horizontal lines, and the electricity price remains fixed for each time period.

[0003] In recent years, with the rapid growth of renewable energy power stations such as wind and photovoltaic power in my country, the output of renewable energy has become highly volatile, leading to a rapid increase in peak-shaving demand on receiving power grids. Given the excellent regulation performance of hydropower, receiving power grids urgently need external hydropower to change their transmission model and flexibly adjust their 24-hour daily transmission output curve to respond in real time to the peak-shaving demand of the receiving power grid. Simultaneously, pilot programs for electricity spot markets have been launched in sending provinces in the southwest region, allowing sending hydropower to participate in spot trading within their province. In the spot market, electricity prices rise significantly when peak-shaving demand is strong. Hydropower stations can generate more power during these times to generate higher revenue. However, responding to peak-shaving demand from receiving power grids with a fixed electricity price at these times would result in significant economic losses, contradicting the original intention of power generation. Therefore, a real contradiction has arisen between the generation strategy of sending hydropower and the peak-shaving demand of receiving power grids. To date, no effective technical solution has been found. The solution proposed in this paper is to establish a new price based on the actual characteristics of power supply and demand. Summary of the Invention

[0004] 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. The present invention adopts a time-of-use electricity price to express the electricity price scheme based on engineering conditions such as the peak-shaving demand of the receiving power grid and the power generation characteristics of cascade hydropower, and provides a method for determining this time-of-use electricity price scheme. The pricing scheme provided can effectively promote cascade hydropower to respond to the peak-shaving demand of the receiving power grid while meeting the maximum power generation benefits of cascade hydropower in multiple provinces, achieve the balance of self-generated electricity at the hourly level between the sending 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 pricing method provided by the present invention is simple and easy to implement, and application cases have shown that it can significantly improve the balance of power supply and demand. The present invention can provide a technical reference for the adaptation of the transmitted power to the transformation of power production methods.

[0005] Technical solution of the present invention:

[0006] 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-provincial power generation model for cascade hydropower; finally, inputting the time-of-use electricity price scheme into the multi-provincial power generation model for cascade hydropower, calculating the 24-hour transmission output curve of cascade hydropower, and calculating the two evaluation indicators of the power purchase cost and peak-shaving effect of the receiving power grid from the 24-hour transmission output curve, optimizing the time-of-use electricity price scheme through a non-dominated sorting algorithm, setting the indicator weights and defining the 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:

[0007] Step 1: Develop a set of feasible time-of-use electricity price plans.

[0008] First, the peak, flat, and valley periods of electricity prices are divided according to the actual load demand of the receiving provinces; then, based on actual engineering experience, the range of values for the tiered electricity prices and the values to be used are determined; finally, a Cartesian product is used to generate alternative time-of-use electricity price schemes, resulting in a set of time-of-use electricity price schemes. Specifically:

[0009] Step 1.1: Divide the peak, flat and valley periods of electricity prices in the receiving provinces based on the triangular fuzzy membership function.

[0010] Considering 24 hours a day as 24 periods, the 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 of a typical year in the receiving province is collected, and triangular fuzzy membership functions are constructed for peak, flat, and valley periods 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. The three membership function values are calculated for each period, and the period type corresponding to the maximum value among the three membership function values is the period type of that period.

[0011] Step 1.2: Determine the electricity price to be selected in the receiving province.

[0012] 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.

[0013] 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 、 、 .

[0014] Step 1.3: Generate a set of time-of-use electricity price plans.

[0015] 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 is .

[0016] 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 corresponding elements are The time-of-use electricity price plans constitute a time-of-use electricity price plan set.

[0017] Step 2: Construct a multi-province cascade hydropower generation model.

[0018] The multi-province 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, where the multiple provinces include the province where the cascade hydropower is located (referred to as the "province") and the provinces to which the cascade hydropower transmits electricity across provinces (referred to as the "receiving provinces"). When cascade hydropower participates in multi-province power transmission, power generation revenue is the primary goal. At the same time, physical requirements such as the ratio of power in the province to power transmitted, hydraulic relations, and operating restrictions of the high-voltage direct current transmission line must be met. Specifically, the following steps are included:

[0019] Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces.

[0020] 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) and (2):

[0021] (1)

[0022] (2)

[0023] Where: The comprehensive benefits of cascade hydropower in transmitting electricity within the province and in receiving provinces; For the Provincial electricity prices during the time period; For the The time-of-use electricity price agreed upon between the cascade hydropower project and the receiving province is the price that needs to be finalized; For hydropower stations In the The province's contribution during the period; For hydropower stations In the The output of the time period; 、 、 The time-of-use electricity prices for peak, flat and valley periods are 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; The total number of time periods throughout the year.

[0024] Step 2.2: Construct power constraints for multi-provincial 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 within the province and the power transmission outside the province equals the total power generation of the cascade hydropower, the constraint conditions are constructed as shown in formula (3):

[0027] (3)

[0028] Where: For hydropower stations In the Output during the period.

[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 outwards should be a certain value each month. Therefore, the ratio constraint of the power transmission in the province to the power transmission outwards is established as shown in formula (4):

[0031] (4)

[0032] Where: For the Monthly time period collection; For the The monthly ratio of electricity generated in the province to that transmitted to other provinces is a constant determined before electricity is transmitted.

[0033] Step 2.3: Construct hydraulic constraints.

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

[0035] (5)

[0036] (6)

[0037] Where: For hydropower stations In 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 stations The set of upstream power stations, and the leading power station is an empty set; For upstream hydropower station In the Power generation flow during the period; For upstream hydropower station To the hydropower station When the water flow is stagnant; The number of seconds for each period.

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

[0039] (7)

[0040] (8)

[0041] Where: and Hydropower Station In the The upper and lower limits of outbound flow in the time period; and Hydropower Station The upper and lower limits of power generation flow.

[0042] Step 2.3.3: Construct the storage capacity boundary constraint, as shown in formula (9):

[0043] (9)

[0044] Where: and Hydropower Station The upper and lower limits of storage capacity.

[0045] Step 2.3.4: Describe the power generation function of the hydropower station, as shown in Equation (10):

[0046] (10)

[0047] Where: For hydropower stations In the Water consumption rate during the period.

[0048] Step 2.4: Construct HVDC interconnection line operation constraints.

[0049] 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):

[0050] (11)

[0051] Where: For the Period through the The output of the HVDC interconnection line; 、 For the The upper and lower output limits of the HVDC interconnection lines are set.

[0052] 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 HVDC interconnection line, construct a power adjustment amplitude constraint, as shown in Equations (12) to (14):

[0053] (12)

[0054] (13)

[0055] (14)

[0056] Where: High-voltage DC interconnection line No. Transmission power during the time period; 、 High-voltage DC interconnection lines Adjust the power limit up or down; 、 Represents high voltage DC interconnection lines In the A 0-1 variable indicating whether the time period is adjusted upward or downward, with adjustment equal to 1 and no adjustment equal to 0. Equations (12) and (13) represent the amplitude constraints for upward and downward adjustments of the HVDC tie line between two adjacent time periods, and Equation (14) represents the unidirectional adjustment of power.

[0057] 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 for adjacent time periods is constructed, as shown in Equations (15) and (16):

[0058] (15)

[0059] (16)

[0060] Step 2.4.4: To ensure that the transmission power of the HVDC interconnection line is not frequently adjusted within a day, a constraint on the number of transmission line adjustments is constructed, as shown in Equations (17) and (18):

[0061] (17)

[0062] (18)

[0063] Where: and High-voltage DC interconnection lines The maximum number of upward and downward adjustments in a day; For the The time period of the day is a set; Equations (17) and (18) ensure that the transmission power cannot be adjusted frequently within a day, thus ensuring the operational reliability of the HVDC interconnection line.

[0064] Step 3: Optimize the time-of-use electricity price plan.

[0065] Step 3.1: Obtain the effects of different time-of-use electricity price plans.

[0066] 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 the cascade hydropower under different time-of-use electricity price schemes. The power purchase cost and peak regulation effect of the receiving power grid are calculated based on the power generation in each period corresponding to the 24-hour transmission output curve. The calculation formula is as shown in formula (19). 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.

[0067] (19)

[0068] Step 3.2: Obtain the optimal time-of-use electricity price plan family.

[0069] Taking the electricity 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 an optimal time-of-use electricity price scheme family. Specifically:

[0070] 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 Group scenario dataset in, Time-of-use electricity pricing scheme The electricity purchase cost of the receiving power grid is Time-of-use electricity pricing scheme The peak regulation effect of the downstream receiving power grid.

[0071] Step 3.2.2: Determine the dominance relationship: For any two time-of-use electricity price plans and time-of-use electricity pricing schemes , if two inequalities If both are strictly established, it is called a time-of-use electricity price scheme Control time-of-use electricity price plan .

[0072] 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 first layer of Pareto frontier , iterative screening Medium solution, remove after each iteration The time-of-use electricity price plan that has been dominated in the The final remaining time-of-use electricity price schemes constitute the optimal time-of-use electricity price scheme family.

[0073] Step 3.3: Determine the final time-of-use electricity price plan.

[0074] Based on 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. The specific steps include the following:

[0075] Step 3.3.1: Normalize the two evaluation index data of electricity purchase cost and peak load regulation effect to ensure comparability between the indicators, as shown in formula (20):

[0076] (20)

[0077] Where: 、 、 、 They are Normalized value, current value, minimum value, and maximum value of the evaluation index.

[0078] Step 3.3.2: Define the preference function , Representative The importance weight of each evaluation indicator is determined according to the economic conditions and peak-shaving demand of the receiving province.

[0079] 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.

[0080] The present invention also provides a pricing system for cascade hydropower interprovincial transmission volume that responds to the peak-shaving demand of the receiving power grid, which is used to call computer resources to implement the above-mentioned pricing method. The pricing system includes four modules:

[0081] Module 1: Time-of-use electricity price scheme set determination module.

[0082] 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.

[0083] Module 2: Cascade hydropower multi-province power generation model construction and calculation module, which includes two sub-modules:

[0084] Module 2.1 is a module for constructing a multi-provincial power generation model for cascade hydropower. It uses the distribution 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 electricity price of the province as parameters, and calls a mature mathematical optimization modeling tool to construct the multi-provincial power generation model for cascade hydropower described in step 2.

[0085] Module 2.2 is the 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 time-of-use electricity price schemes. After receiving 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.

[0086] Module 3: Optimal time-of-use electricity price family determination module.

[0087] This module is used to execute steps 3.1 and 3.2 of 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 fed into module 2.2 as input data. Then, the receiving grid's electricity purchase cost and peak-shaving effect are calculated based on the results returned by module 2.2. Finally, based on the receiving grid's electricity purchase cost and peak-shaving effect information under all schemes, step 3.2 is executed to determine the optimal time-of-use electricity price scheme family and output it.

[0088] Module 4: Final pricing module.

[0089] 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.

[0090] Beneficial effects of the present invention

[0091] The present invention addresses the problem that the current pricing scheme for electricity transmission is not compatible with current industrial changes such as large-scale grid connection of new energy and electricity spot market, and provides a new time-of-use pricing method and its supporting system. The present invention can calculate a reasonable time-of-use electricity price scheme based on engineering conditions such as the peak-shaving demand of the receiving power grid and the power generation characteristics of cascade hydropower. The pricing scheme provided can effectively promote its response to the peak-shaving demand of the receiving power grid while meeting the maximum power generation benefits of cascade hydropower in multiple provinces, achieve the balance of self-generated electricity at the hourly level between the transmitting and receiving ends, and control the power purchase cost of the receiving power grid, achieving a win-win situation for the hydropower station and the receiving power grid. The present invention can provide a technical reference for the adaptation of the transmitted electricity to the transformation of the power production mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Figure 1 It is a graph of variance changes as cost increases;

[0093] Figure 2 This is a graph showing the changes in various peak regulation effect evaluation indicators with increasing costs, where (a) is the peak-to-valley difference of the residual load in Province G, (b) is the average distance of the residual load in Province G, (c) is the maximum residual load in Province G, and (d) is the residual load rate in Province G;

[0094] Figure 3 This is a diagram of the pricing system architecture provided by the present invention. DETAILED DESCRIPTION

[0095] The present invention will be further described below with reference to the accompanying drawings and examples.

[0096] The following implementation of the present invention is based on the L River Basin within Province Y (hereinafter referred to as the "L River Basin"). This example is based on a cascade hydropower project consisting of two large hydropower stations, A and B, located in the L River Basin (hereinafter referred to as "Hydropower Station A" and "Hydropower Station B," respectively; together, they constitute the L River Basin cascade hydropower project). The plant parameters are based on actual data from the A and B hydropower stations.

[0097] According to the current framework agreement, Hydropower Station A transmits electricity to Province G for consumption through HVDC Interconnection Line A, and Hydropower Station B transmits electricity through HVDC Interconnection Line B in a "grid-to-grid" manner. The power transmission limit of HVDC Interconnection Line A and HVDC 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 based on the load characteristics of Province Y. The monthly ratio of intra-provincial power transmission to inter-provincial power transmission is converted according to the actual historical data of Province Y. This embodiment uses the actual data of fixed electricity prices for the power transmitted from Province Y to Province G under the framework agreement in a certain year as an example to implement the method of the present invention.

[0098] On one hand, this embodiment provides a pricing method for cascade hydropower interprovincial transmission volume that responds to the peak-shaving demand of the receiving power grid. The implementation steps of the pricing method are as follows:

[0099] Step 1: Develop a set of feasible time-of-use electricity price plans.

[0100] Step 1.1: Divide the receiving provinces into peak, flat and valley time periods based on the triangular fuzzy membership function.

[0101] Considering 24 hours a day as 24 periods, the 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 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:

[0102] Construct the valley period membership function as shown in formula (21);

[0103] (twenty one)

[0104] Construct the membership function of the normal period, as shown in formula (22);

[0105] (twenty two)

[0106] Construct the peak period membership function as shown in formula (23);

[0107] (twenty three)

[0108] In formulas (21) to (23), is the actual load data, is the minimum load value, is the maximum load value, is the average value of the load, 、 、 are the membership functions for valley, flat and peak periods respectively.

[0109] Calculate the three membership function values for each time period. The time period type corresponding to the maximum value among the three membership function values is the time period type of the time period. After calculation, in this embodiment, the peak time periods are time periods 10-12 and 15-21, the flat time periods are time periods 9, time periods 13-14 and time periods 22-24, and the remaining time periods are valley time periods.

[0110] Step 1.2: Determine the electricity price to be selected in the receiving province.

[0111] 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.

[0112] Then, the same step size is used to discretize each electricity price interval, 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 respectively 、 、 .

[0113] Step 1.3: Generate a set of time-of-use electricity price plans.

[0114] 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 is .

[0115] 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 corresponding elements are The time-of-use electricity price plans constitute a time-of-use electricity price plan set.

[0116] Step 2: Construct a multi-province cascade hydropower generation model.

[0117] Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces.

[0118] 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) and (2).

[0119] Step 2.2: Construct power constraints for multi-provincial power transmission.

[0120] Step 2.2.1: Construct the power constraints for multi-province power transmission.

[0121] In order to ensure that the sum of the power transmitted by cascade hydropower in the province and the power transmitted to other provinces equals the total power generation of cascade hydropower, the constraint conditions are constructed as shown in formula (3).

[0122] Step 2.2.2: Construct power distribution ratio constraints.

[0123] According to the current power transmission requirements, the ratio of the total power transmission in the province to the total power transmission out of the province should be a certain value each month. Therefore, the ratio constraint of the power transmission in the province to the power transmission out of the province is established as shown in formula (4).

[0124] Step 2.3: Construct hydraulic constraints.

[0125] Step 2.3.1: Construct water balance constraints, as shown in Equations (5) and (6).

[0126] Step 2.3.2: Construct the flow boundary constraint, as shown in Equation (7)-Equation (8).

[0127] Step 2.3.3: Construct the storage capacity boundary constraint as shown in Equation (9).

[0128] Step 2.3.4: Describe the power generation function of the hydropower station, as shown in Equation (10).

[0129] Step 2.4: Construct HVDC interconnection line operation constraints.

[0130] 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).

[0131] 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 HVDC interconnection line, construct a power adjustment amplitude constraint, as shown in Equations (12) to (14).

[0132] Step 2.4.3: To ensure that the transmission power of the HVDC interconnection line cannot be reversely adjusted between adjacent time periods, construct the reverse adjustment restriction constraints between adjacent time periods, as shown in Equations (15) and (16).

[0133] Step 2.4.4: To ensure that the transmission power of the HVDC interconnection line is not frequently adjusted within a day, a constraint on the number of adjustments to the transmission line is constructed, as shown in Equations (17) and (18).

[0134] Step 3: Optimize the time-of-use electricity price plan.

[0135] Step 3.1: Obtain the effects of different time-of-use electricity price plans.

[0136] 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 curves 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 based on 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. The calculation formulas are as shown in formulas (24) to (29):

[0137] Residual load peak-to-valley difference:

[0138] (twenty four)

[0139] (25)

[0140] Where: The peak-to-valley difference of the residual load of the receiving power grid; is the total number of cascade hydropower stations participating in the dispatch; for The receiving end power grid load during the time period; for The residual load of the receiving power grid during the period.

[0141] Residual load variance:

[0142] (26)

[0143] Where: is the residual load variance of the receiving power grid.

[0144] Residual load average distance:

[0145] (27)

[0146] Where: is the average residual load distance of the receiving power grid.

[0147] Maximum residual load:

[0148] (28)

[0149] Where: is the maximum value of the residual load of the receiving power grid.

[0150] Residual load rate:

[0151] (29)

[0152] Where: is the maximum value of the residual load of the receiving power grid.

[0153] The smaller the residual load peak-to-valley difference, the smaller the residual load's peak-shaving capacity requirement. Smaller residual load variance and mean distance indicate a more stable residual load sequence, minimizing the need to regulate output fluctuations from other units. A smaller residual load maximum value indicates a smaller residual load demand on the peak capacity of other units. A larger residual load ratio indicates less variability. In short, smaller residual load peak-to-valley difference, variance, mean distance, and maximum value, as well as a larger residual load ratio, indicate better peak-shaving effectiveness.

[0154] In this embodiment, the residual load variance is used as the peak regulation effect evaluation index, and the residual load variance and the receiving grid cost under each time-of-use electricity price scheme are calculated according to formula (26) and formula (19).

[0155] Step 3.2: Obtain the optimal time-of-use electricity price plan family.

[0156] 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 Group scenario dataset in, Time-of-use electricity pricing scheme The electricity purchase cost of the receiving power grid is Time-of-use electricity pricing scheme The peak regulation effect of the downstream receiving power grid.

[0157] Step 3.2.2: Determine the dominance relationship: For any two time-of-use electricity price plans and time-of-use electricity pricing schemes , if two inequalities If both are strictly established, it is called a time-of-use electricity price scheme Control time-of-use electricity price plan .

[0158] 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 first layer of Pareto frontier , iterative screening Medium solution, remove after each iteration The time-of-use electricity price plan that has been dominated in the The remaining time-of-use electricity price schemes finally 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.

[0159] Step 3.3: Determine the final time-of-use electricity price plan.

[0160] Step 3.3.1: Normalize the data of the two evaluation indicators, electricity purchase cost and peak regulation effect, to ensure the comparability between the evaluation indicators, as shown in formula (20).

[0161] Step 3.3.2: Define the preference function ,In this embodiment, the weights of the electricity purchase cost and the ,remaining load variance index are both set to 0.5.

[0162] Step 3.3.3: Calculate the preference function values for the 21 time-of-use pricing schemes in the optimal time-of-use pricing scheme family, and then select the time-of-use pricing scheme with the smallest preference function value as the final time-of-use pricing scheme. The calculation shows that the optimal time-of-use pricing scheme in this embodiment is 800 yuan for peak hours, 500 yuan for off-peak hours, and 150 yuan for off-peak hours. The peak hours are periods 10-12 and 15-21, the off-peak hours are periods 9, 13-14, and 22-24, and the remaining periods are off-peak hours.

[0163] This embodiment also provides a pricing system for cascade hydropower interprovincial transmission volume that responds to the peak-shaving 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:

[0164] Module 1: Time-of-use electricity price scheme set determination module.

[0165] 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, 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.

[0166] Module 2: Cascade hydropower multi-province power generation model construction and calculation module, which includes two sub-modules:

[0167] Module 2.1 is a module for constructing a multi-provincial power generation model for cascade hydropower. It uses information such as the distribution ratio of the cascade hydropower generation in the province and the external transmission, the initial and final storage capacity of the power station, the water consumption rate of the power station, the capacity of the external transmission channel, and the adjustment amplitude as parameters, and calls a mature mathematical optimization modeling tool to construct the multi-provincial power generation model for cascade hydropower described in step 2.

[0168] Module 2.2 is the 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 time-of-use electricity price schemes. After receiving 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.

[0169] Module 3: Optimal time-of-use electricity price family determination module.

[0170] This module is used to execute steps 3.1 and 3.2 of 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 fed into module 2.2 as input data. Then, the receiving grid's electricity purchase cost and peak-shaving effect are calculated based on the results returned by module 2.2. Finally, based on the receiving grid's electricity purchase cost and peak-shaving effect information under all schemes, step 3.2 is executed to determine the optimal time-of-use electricity price scheme family and output it.

[0171] Module 4: Final pricing module.

[0172] 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.

[0173] Implementation results analysis:

[0174] 1) Analysis of grid costs and peak load regulation effects;

[0175] 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 for the power grids at the transmitting and receiving ends, variance is selected as the evaluation index of peak-shaving effect, 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.

[0176] (30)

[0177] Where: is the deviation of the variance between adjacent solutions, is the deviation of total costs between adjacent plans.

[0178] 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, the variance decreases slower as the cost increases. 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. In addition, as the cost increases, the CVD changes become smaller and smaller. In other words, as the peak-shaving demand continues to increase, it costs 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 costs and peak-shaving demands and select the only optimal time-of-use electricity price scheme, the present invention adopts the method of setting indicator weights, which are 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 period, 500 yuan for flat period, and 150 yuan for valley period.

[0179] 2) Validity analysis;

[0180] 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-shaving results of the two schemes are calculated. The two schemes are described as follows:

[0181] Time-of-use electricity price plan: The electricity within the framework agreement is sold at the final time-of-use electricity price plan determined in this embodiment.

[0182] Fixed electricity price plan: The electricity volume 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.

[0183] As shown in Table 1, the raw load in the table represents the actual raw load data for the receiving province in that year. Under both models, annual peak-shaving performance evaluation indicators were calculated and found to improve across all peak-shaving indicators under the TOU pricing scheme compared to the fixed-price scheme. In terms of reducing the peak-to-valley difference in residual load, the TOU pricing scheme reduced it by 7.63% compared to the fixed-price scheme. In terms of improving residual load stability, the residual load variance decreased by 18.18% and the residual load average distance decreased by 10.46%. In terms of reducing the maximum residual load, the maximum residual load decreased by 1.08%. In terms of improving the variability of residual load, the residual load rate increased by 1.19%. The receiving grid's electricity costs increased by 11.96%. This indicates that the sending hydropower station achieved increased revenue from outbound transmission. While the receiving grid experienced increased costs, peak-shaving requirements were met within manageable costs, ultimately achieving a balance of interests between the sending and receiving power stations. 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-shaving demand of the receiving power grid, achieving a win-win effect for both the sender and the receiver.

[0184] Table 1: Statistical indicators of peak load regulation effects of various schemes

[0185]

[0186] In summary, the present invention can provide a method for price coordination between the sender and the receiver 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-shaving demand of the receiving power grid, characterized by: The pricing methods include: Step 1: Develop a feasible TOU electricity price plan, including: Divide the electricity price peak, flat and valley periods in the receiving provinces and generate a set of time-of-use electricity price plans; Step 2: Construct a multi-province cascade hydropower generation model, including: Step 2.1: Construct an objective function to maximize the benefits of cascade hydropower participation in multiple provinces, including: 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: （1） （2） Where: The comprehensive benefits of cascade hydropower in transmitting electricity within the province and in receiving provinces; For the Provincial electricity prices during the time period; For the Time-of-use electricity prices agreed between cascade hydropower and receiving provinces; For hydropower stations In the The province's contribution during the period; For hydropower stations In the The output of the time period; 、 、 The time-of-use electricity prices for peak, flat and valley periods are 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 in a year; Step 2.2: Construct power constraints for multi-provincial power transmission; Step 2.3: Construct hydraulic constraints; Step 2.4: Construct HVDC interconnection line operation constraints; Step 3: Optimize the time-of-use electricity price plan, including: Step 3.1: Obtain the effects of different time-of-use electricity price plans, including: Taking the TOU electricity price scheme generated in step 1 as input, the multi-provincial cascade hydropower 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 TOU electricity price schemes. Based on 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 plan family, including: 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, a non-dominated sorting algorithm is used to find the Pareto frontier scheme under these two evaluation indicators. 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 TOU electricity price plan, including: Determine the two evaluation index data of electricity purchase cost and peak regulation effect, set the index weights and define the preference function; 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.

2. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak-shaving demand of the receiving power grid according to claim 1, characterized in that: The pricing method specifically includes the following steps: Step 1: Formulate a feasible set of time-of-use electricity price plans, including: Step 1.1: Divide the peak, flat and valley periods of electricity prices in the receiving provinces based on the triangular fuzzy membership function, including: Considering 24 hours a day as 24 periods, the period vector is recorded as , the corresponding load value of the receiving province is Collect the daily average value sequence of the 24-hour load curve of the receiving province in a typical year, construct the triangular fuzzy membership function for the peak, flat and valley periods respectively, calculate the three membership function values for each period, and the period type corresponding to the maximum value among the three membership function values is the period type of the period; Step 1.2: Determine the electricity price to be selected for the receiving province, including: First, based on actual project experience, the upper and lower limits of electricity prices during peak, flat and valley periods in the receiving provinces are determined, and the price ranges for peak, flat and valley periods 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 TOU price plan set, including: 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 plans constitute a time-of-use electricity price plan set; Step 2.2: Constructing power constraints for multi-provincial power transmission, including: Step 2.2.1: Construct the power constraints for multi-province power transmission: In order to ensure that the sum of the power transmitted within the province and the power transmitted outside the province equals the total power generation of the cascade hydropower, the following constraints are constructed: （3） Where: For hydropower stations In the Output during the time period; Step 2.2.2: Construct power distribution ratio constraints, including: Establish constraints on the ratio of electricity volume within the province to that transmitted to other provinces: （4） Where: For the Monthly time period collection; For the The monthly ratio of electricity generated in the province to that transmitted to other provinces is a constant determined before electricity is transmitted; Step 2.3: Constructing hydraulic constraints, including: Step 2.3.1: Construct water balance constraints: （5） （6） Where: For hydropower stations In 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 stations The set of upstream power stations, and the leading power station is an empty set; For upstream hydropower station In the Power generation flow during the period; For upstream hydropower station To the hydropower station When the water flow is stagnant; 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 outbound flow in the time period; and Hydropower Station 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 stations In the Water consumption rate during the time period; The step 2.4: establishing the HVDC tie line operation constraints includes: Step 2.4.1: To ensure that the amount of power transmitted does not exceed the upper and lower limits of the transmission channel's transmission capacity, establish upper and lower limit constraints on the channel's capacity: （11） Where: For the Period through the The output of the HVDC interconnection line; 、 For the The upper and lower output limits of the HVDC 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 HVDC interconnection line, construct a power adjustment amplitude constraint: （12） （13） （14） Where: High-voltage DC interconnection line No. Transmission power during the time period; 、 High-voltage DC interconnection lines Adjust the power limit up or down; 、 Represents high voltage DC interconnection lines In the A 0-1 variable indicating whether the time period is adjusted upward or downward, with adjustment equal to 1 and no adjustment equal to 0. Equations (12) and (13) represent the amplitude constraints for upward and downward adjustments of the HVDC tie line between two adjacent time periods, 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 constraint is constructed for adjacent time periods: （15） （16） Step 2.4.4: To ensure that the transmission power of the HVDC interconnection line is not frequently adjusted within a day, set up a constraint on the number of transmission line adjustments: （17） （18） Where: and High-voltage DC interconnection lines The maximum number of upward and downward adjustments in a day; For the A collection of time periods for the day; Step 3.3: Determine the final time-of-use electricity price plan, including: Step 3.3.1: Normalize the two evaluation index data of electricity 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-shaving 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-shaving demand of the receiving power grid according to claim 2, characterized in that: In step 3.1, the electricity purchase cost The calculation formula is as follows: （19）。 5. The pricing method for cascade hydropower interprovincial transmission volume in response to the peak-shaving demand of the receiving power grid according to claim 2 is 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 of the residual load of the receiving-end power grid, the residual load variance, the residual load average distance and the residual load maximum value.

6. A pricing method for cascade hydropower interprovincial transmission volume in response to the peak-shaving demand of the receiving power grid according to claim 5, 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 electricity price scheme in the time-of-use electricity price scheme set Group scenario dataset in, Time-of-use electricity pricing scheme The electricity purchase cost of the receiving power grid is Time-of-use electricity pricing scheme Peak 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 schemes , if two inequalities If both 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 first layer of Pareto frontier , iterative screening Medium solution, remove after each iteration The time-of-use electricity price plan that has been dominated in the The final remaining time-of-use electricity price schemes 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-shaving demand of the receiving power grid according to claim 2, characterized in that: In step 3.3.1, the two evaluation index data of electricity purchase cost and peak load regulation effect are normalized by the following formula: （20） Where: 、 、 、 They are Normalized value, current value, minimum value, and maximum value of the evaluation index.

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 according to 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 peak, flat and valley periods as input, divides the electricity price of the receiving province into peak, flat and valley periods, calculates and generates a time-of-use electricity price plan, forms a set of time-of-use electricity price plans, and outputs them; Module 2: Cascade hydropower multi-province power generation model construction and calculation module, which includes two sub-modules: Module 2.1 is a module for constructing a multi-provincial cascade hydropower generation model. This module uses the proportion of cascade hydropower generation in the province and transmitted power generation, the initial and final storage capacity of the power station, the water consumption rate of the power station and the transmission channel capacity, the adjustment amplitude, the upper limit of the number of adjustments, and the provincial electricity price as parameters. It uses mature mathematical optimization modeling tools to construct the multi-provincial cascade hydropower generation model described in step 2. Module 2.2 is the calculation module for the cascade hydropower multi-province generation model. Based on the cascade hydropower multi-province generation model provided by module 2.1, it provides an external time-of-use electricity price scheme input interface. After receiving the input time-of-use electricity price scheme, it automatically calculates the cascade hydropower multi-province 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 of the pricing method. First, it obtains each time-of-use electricity price scheme from the set of time-of-use electricity price schemes output by module 1 and inputs it into module 2.2 as input data. Then, based on the results returned by module 2.2, it calculates the electricity purchase cost and peak-shaving effect of the receiving power grid. Finally, based on the electricity purchase cost and peak-shaving effect information of the receiving power grid under all time-of-use electricity price schemes, it executes step 3.2 to determine the optimal time-of-use electricity price scheme family and outputs 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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