A step-by-step connection adaptive time-of-use electricity price daily joint scheduling method and system

Abstract

The application provides a kind of step connection within-day joint scheduling method and system suitable for time-of-use electricity price, collects the hourly natural inflow process of cascade hydropower stations in dry season, and time-of-use electricity price data of cascade hydropower stations;Adopt normalization method to convert the hourly natural inflow process of cascade hydropower stations in dry season and time-of-use electricity price data of cascade hydropower stations into dimensionless curves respectively, and calculate the matching degree between them to screen different flow scenarios;With the maximum power generation benefit of each hydropower station in cascade within dry season as the optimization objective, considering the influence of cascade connection on the minimum discharge constraint of hydropower station, a within-day joint scheduling model of cascade hydropower stations is established;Using NSGA-Ⅱ multi-objective intelligent optimization algorithm, different flow scenarios are solved to obtain a multi-objective scheduling solution set;By comparing the power generation benefits of multi-objective scheduling solution and simulation scheduling, a power generation benefit allocation scheme between cascades is proposed.

Description

Technical Field

[0001] This invention relates to the field of reservoir group power generation dispatching, and in particular to an intraday joint dispatching method and system adapted to time-of-use pricing under cascade connection. Background Technology

[0002] The minimum discharge flow rate takes into account various needs such as ecological flow in the river section, water intake in the downstream channel, power generation by the hydropower station, and navigation, and is one of the important indicators constraining the scheduling and operation of hydropower stations. When operating with a single reservoir, in order to ensure that there are no sections of the river downstream of the dam that experience reduced water flow, the hydropower station must control the discharge according to the minimum discharge flow rate at all times. The large-scale integration of wind and solar new energy into the grid has placed higher demands on the scheduling flexibility of hydropower stations. The daily electricity price changes significantly over time, and instantaneous control of discharge according to the minimum discharge flow rate is not conducive to the power generation scheduling and operation of hydropower stations.

[0003] In the development pattern of cascade hydropower stations, upstream and downstream hydropower stations form a cascade connection to fully utilize river hydropower resources. Under the cascade connection, there is often no dewatering section between upstream and downstream hydropower stations. When the water depth, river width, and other conditions of the cascade reservoir section basically meet the requirements of water ecology, water ecology, and other water supply, the minimum downstream discharge flow is changed from instantaneous control to daily average control. This can increase the daily peak-shaving performance of hydropower stations on the one hand, and increase the cascade power generation benefits by combining the daily time-of-use electricity price distribution characteristics on the other hand. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of the prior art by providing a method and system for intraday joint dispatching adapted to time-of-use pricing under cascade connection, thus providing technical support for joint dispatching of cascade hydropower stations adapted to time-of-use pricing scenarios.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides an intraday joint dispatching method adapted to time-of-use pricing under tiered grid connection, comprising: S1. Collect hourly natural inflow data of cascade hydropower stations during the dry season and time-of-use electricity price data of cascade hydropower stations; S2. Using the normalization method, the hourly natural inflow process of the cascade hydropower station during the dry season and the time-of-use electricity price of the cascade hydropower station are converted into dimensionless curves, and the matching degree between the two is calculated to screen different flow scenarios. S3. Taking the maximization of daily power generation efficiency of each cascade hydropower station during the dry season as the optimization objective, and considering the impact of cascade connection on the minimum downstream flow constraint of hydropower stations, a joint scheduling model for cascade hydropower stations during the day is constructed. S4. The NSGA-II multi-objective intelligent optimization algorithm is used to solve different traffic scenarios and obtain a multi-objective scheduling solution set. S5. Compare the power generation benefits of the multi-objective scheduling solution with those of the simulated scheduling, and propose a power generation benefit allocation scheme between cascades.

[0006] Furthermore, S1 specifically refers to: ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly natural inflow; Indicates the first Hydropower station The dry season of the year day Hourly electricity price; This indicates the total number of years to be calculated; Indicates the total number of days in the dry season; This indicates the total number of reservoirs.

[0007] Furthermore, in S2, the hourly natural inflow process of the cascade hydropower stations during the dry season and the time-of-use electricity price of the cascade hydropower stations are converted into dimensionless curves using a normalization method, specifically as follows: ; ; ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly normalized natural inflow; Indicates the first Hydropower station The dry season of the year day Electricity price normalized to hourly rate; In step S2, the matching degree between the normalized dimensionless curve of the hourly natural inflow of the cascade hydropower stations during the dry season and the dimensionless curve of the time-of-use electricity price of the cascade hydropower stations is calculated, specifically as follows: ; in, Represents the normalized i-th Hydropower station The dry season of the year The matching degree between daily inflow and time-of-use electricity price is expressed as Euclidean distance; In S2, different flow scenarios are selected: the corresponding inflow flow scenario is selected according to the principle of maximizing or minimizing the matching degree between the daily inflow process of each hydropower station and the time-of-use electricity price.

[0008] Furthermore, in S3, with the optimization objective of maximizing the daily power generation efficiency of each cascade hydropower station during the dry season, a joint daily dispatch model for the cascade hydropower stations is constructed, specifically as follows: S301. Objective Function Construction: Taking the maximization of daily power generation efficiency of each hydropower station during the dry season as the optimization objective, the calculation is as follows: ; in, Indicates the first Hydropower station The dry season of the year Daily power generation benefits; Indicates the first Hydropower station The dry season of the year day Hourly effort; This indicates a long calculation period for hydropower station dispatching; S302. Constraint Settings: These include hydropower station water balance constraints, output limit constraints, water level boundary constraints, downstream flow constraints, initial and final water level constraints during the scheduling period, and flow evolution constraints, calculated as follows: ; ; ; ; ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly outbound flow; Indicates the first Hydropower station The dry season of the year day Hourly storage capacity; Indicates the first Hydropower station The dry season of the year day Minimum output per hour; Indicates the first Hydropower station The dry season of the year day Maximum output per hour; Indicates the first Hydropower station The dry season of the year day Hourly water level; Indicates the first Hydropower station The dry season of the year day Hourly lowest water level; Indicates the first Hydropower station The dry season of the year day Highest water level in hours; Indicates the first Hydropower station The dry season of the year day Minimum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year day Maximum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year Initial water level during daily scheduling; Indicates the first Hydropower station The dry season of the year Daily water level at the end of the dispatch period; Indicates the first Hydropower station The dry season of the year day Inflow within hourly intervals; In S3, the impact of cascade connection on the minimum downstream flow constraint of the hydropower station is considered, specifically as follows: S303. When the water level of the downstream hydropower station is lower than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled by instantaneous discharge, that is: ; in, Indicates the first The hydropower station during the dry season Minimum instantaneous discharge flow rate per day; Indicates the first The water level at which the hydropower station connects with the upstream hydropower station; S304. When the water level of the downstream hydropower station is higher than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled according to the average daily water volume, that is: ; in, Indicates the first Hydropower station Minimum daily discharge volume.

[0009] Furthermore, S4 specifically includes: S401. Taking the hourly outflow from the cascade hydropower stations as the decision variable, the calculation expression is as follows: ; S402. Set the parameter values ​​for the NSGA-II multi-objective intelligent optimization algorithm, including: number of iterations. Population size Cross coefficient Coefficient of variation parameter; S403. Taking maximizing the power generation efficiency of each hydropower station during the dry season as the optimization objective, multi-objective optimization is performed on different selected flow scenarios to obtain a multi-objective scheduling solution set, which is calculated as follows: ; in, Indicates the first Population number Hydropower station The dry season of the year day Hourly outbound flow.

[0010] Furthermore, S5 specifically includes: S501. Using a simulated dispatching method, calculate the power generation benefits of each hydropower station under simulated dispatching of cascade hydropower stations, specifically: ; in, Indicates the first Hydropower station The dry season of the year The daily simulated power generation efficiency is calculated using the following formula: ; in, Indicates the first Hydropower station The dry season of the year Daily simulated power output scheduling; S502. Select the solution that maximizes the sum of the power generation benefits of the cascade hydropower stations in the multi-objective scheduling solution. Specifically: ; ; in, In the multi-objective scheduling solution set, the first... Population number Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first cascade hydropower station The dry season of the year The solution set number corresponding to the maximum daily power generation benefit; S503. Using a weighted allocation method, the solution that maximizes the sum of the power generation benefits of cascade hydropower stations in the multi-objective scheduling solution is redistributed, specifically as follows: ; in, The solution set that maximizes the benefits of cascade power generation is represented by the first... Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first Hydropower station distribution of power generation benefits; Indicates the first The weighting of power generation benefits for hydropower stations.

[0011] Furthermore, a daytime joint dispatching system adapted to time-of-use pricing under tiered connection includes: at least one processor, and a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by the processor to implement the intraday joint scheduling method for time-of-use pricing under tiered connection.

[0012] The beneficial effects of this invention are as follows: it calculates the daily power generation benefits of cascade hydropower stations by considering the water level connection relationship of cascade hydropower stations and the time-of-use electricity price within the day, and provides technical support for increasing the power generation benefits of cascade hydropower stations through the redistribution of power generation benefits; and it breaks through the technical bottleneck of joint dispatching based on time-of-use electricity price under cascade connection. Attached Figure Description

[0013] Figure 1 This is a flowchart of an intraday joint dispatching method adapted to time-of-use pricing under tiered connection according to the present invention; Figure 2 A schematic diagram of the multi-objective optimization solution set for the power generation benefits of cascade hydropower stations; Figure 3 A schematic diagram comparing the multi-objective optimization solution set and simulated scheduling of the power generation benefits of cascade hydropower stations. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0015] Please see Figure 1 Taking a group of reservoirs in a certain river basin as an implementation case, a method for intraday joint dispatching adapted to time-of-use pricing under cascade connection is proposed, including: S1. Collect hourly natural inflow data of cascade hydropower stations during the dry season and time-of-use electricity price data of cascade hydropower stations; S2. Using the normalization method, the hourly natural inflow process of the cascade hydropower station during the dry season and the time-of-use electricity price of the cascade hydropower station are converted into dimensionless curves, and the matching degree between the two is calculated to screen different flow scenarios. S3. Taking the maximization of daily power generation efficiency of each cascade hydropower station during the dry season as the optimization objective, and considering the impact of cascade connection on the minimum downstream flow constraint of hydropower stations, a joint scheduling model for cascade hydropower stations during the day is constructed. S4. The NSGA-II multi-objective intelligent optimization algorithm is used to solve different traffic scenarios and obtain a multi-objective scheduling solution set. S5. Compare the power generation benefits of the multi-objective scheduling solution with those of the simulated scheduling, and propose a power generation benefit allocation scheme between cascades.

[0016] In S1, the hourly natural inflow process of the cascade hydropower stations during the dry season and the time-of-use electricity price data of the cascade hydropower stations are specifically defined as follows: ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly natural inflow; Indicates the first Hydropower station The dry season of the year day Hourly electricity price; This indicates the total number of years to be calculated; Indicates the total number of days in the dry season; Indicates the total number of reservoirs; In S2, the hourly natural inflow process of the cascade hydropower stations during the dry season and the time-of-use electricity price of the cascade hydropower stations are converted into dimensionless curves using a normalization method, specifically: ; ; ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly normalized natural inflow; Indicates the first Hydropower station The dry season of the year day Electricity price normalized to hourly rate; In step S2, the matching degree between the normalized dimensionless curve of the hourly natural inflow of the cascade hydropower stations during the dry season and the dimensionless curve of the time-of-use electricity price of the cascade hydropower stations is calculated, as follows: ; in, Represents the normalized i-th Hydropower station The dry season of the year The matching degree between daily inflow and time-of-use electricity price is expressed as Euclidean distance; In S2, different flow scenarios can be selected according to the principles of maximizing or minimizing the matching degree between the daily inflow process of each hydropower station and the time-of-use electricity price. In S3, with the optimization objective of maximizing the daily power generation efficiency of each cascade hydropower station during the dry season, a joint daily dispatch model for the cascade hydropower stations is constructed as follows: S301. Objective Function Construction: The optimization objective is to maximize the daily power generation efficiency of each hydropower station in the cascade hydropower station during the dry season. The calculation formula is as follows: ; in, Indicates the first Hydropower station The dry season of the year Daily power generation benefits; Indicates the first Hydropower station The dry season of the year day Hourly effort; This indicates a long calculation period for hydropower station dispatching; S302. Constraint settings, including hydropower station water balance constraints, output limit constraints, water level boundary constraints, downstream flow constraints, initial and final water level constraints during the scheduling period, and flow evolution constraints. The calculation formula is as follows: ; ; ; ; ; ; in, Indicates the first Hydropower station The dry season of the year day Hourly outbound flow; Indicates the first Hydropower station The dry season of the year day Hourly storage capacity; Indicates the first Hydropower station The dry season of the year day Minimum output per hour; Indicates the first Hydropower station The dry season of the year day Maximum output per hour; Indicates the first Hydropower station The dry season of the year day Hourly water level; Indicates the first Hydropower station The dry season of the year day Hourly lowest water level; Indicates the first Hydropower station The dry season of the year day Highest water level in hours; Indicates the first Hydropower station The dry season of the year day Minimum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year day Maximum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year Initial water level during daily scheduling; Indicates the first Hydropower station The dry season of the year Daily water level at the end of the dispatch period; Indicates the first Hydropower station The dry season of the year day Inflow within hourly intervals; In S3, the impact of cascade connection on the minimum downstream flow constraint of the hydropower station is considered, as follows: S303. When the water level of the downstream hydropower station is lower than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled by instantaneous discharge, that is: ; in, Indicates the first The hydropower station during the dry season Minimum instantaneous discharge flow rate per day; Indicates the first The water level at which the hydropower station connects with the upstream hydropower station; S304. When the water level of the downstream hydropower station is higher than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled according to the average daily water volume, that is: ; in, Indicates the first Hydropower station Minimum daily discharge volume; Furthermore, in step S4, the NSGA-II multi-objective intelligent optimization algorithm is used to solve different traffic scenarios and obtain a multi-objective scheduling solution set, as follows: S401. Taking the hourly outflow from the reservoir of the cascade hydropower station as the decision variable, the calculation expression is as follows: ; S402. Set the parameter values ​​for the NSGA-II multi-objective intelligent optimization algorithm, including: number of iterations. Population size Cross coefficient Coefficient of variation Parameters; S403. Taking the maximization of power generation efficiency during the dry season of each hydropower station as the optimization objective, multi-objective optimization is performed on different selected flow scenarios to obtain a multi-objective scheduling solution set. The calculation expression is as follows: ; in, Indicates the first Population number Hydropower station The dry season of the year day Hourly outbound flow; Specifically, S5 is: S501. Using a simulated scheduling method, calculate the power generation benefits of each hydropower station under simulated scheduling of cascade hydropower stations, as detailed below: ; in, Indicates the first Hydropower station The dry season of the year The daily simulated power generation efficiency is calculated using the following formula: ; in, Indicates the first Hydropower station The dry season of the year Daily simulated power output scheduling; S502. Select the solution that maximizes the sum of the power generation benefits of the cascade hydropower stations in the multi-objective scheduling solution. Specifically: ; ; in, In the multi-objective scheduling solution set, the first... Population number Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first cascade hydropower station The dry season of the year The solution set number corresponding to the maximum daily power generation benefit; S503. Using a weighted allocation method, the solution that maximizes the sum of the power generation benefits of cascade hydropower stations in the multi-objective scheduling solution is redistributed, as follows: ; in, The solution set that maximizes the benefits of cascade power generation is represented by the first... Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first Hydropower station distribution of power generation benefits; Indicates the first The weighting of power generation benefits for hydropower stations.

[0017] The multi-objective optimization solution set of the power generation benefits of cascade hydropower stations is as follows: Figure 2 As shown.

[0018] A Comparison of Multi-Objective Optimization Solution Set and Simulation Scheduling of Power Generation Benefits of Cascade Hydropower Stations Figure 3 As shown.

[0019] according to Figure 2 and Figure 3 It can be seen that under simulated dispatch, the daily power generation benefits of hydropower stations 1 and 2 are RMB 2.9225 million and RMB 973,300, respectively; under multi-objective dispatch, the daily power generation benefits of hydropower stations 1 and 2 are RMB 2.9565-2.9627 million and RMB 995,200-997,100, respectively. Compared with simulated dispatch, multi-objective dispatch can increase the daily power generation benefits by up to RMB 62,600. If the installed capacity ratio of hydropower stations 1 and 2 is 5.35:1, then hydropower station 1 can be further allocated RMB 52,800 in power generation benefits, and hydropower station 2 can be further allocated RMB 9,800 in power generation benefits.

[0020] The embodiments described above are merely illustrative of implementation methods of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be defined by the appended claims.

Claims

1. A method for intraday joint dispatching adapted to time-of-use pricing under tiered grid connection, characterized in that, include: S1. Collect hourly natural inflow data of cascade hydropower stations during the dry season and time-of-use electricity price data of cascade hydropower stations; S2. Using the normalization method, the hourly natural inflow process of the cascade hydropower station during the dry season and the time-of-use electricity price of the cascade hydropower station are converted into dimensionless curves, and the matching degree between the two is calculated to screen different flow scenarios. S3. Taking the maximization of daily power generation efficiency of each cascade hydropower station during the dry season as the optimization objective, and considering the impact of cascade connection on the minimum downstream flow constraint of hydropower stations, a joint scheduling model for cascade hydropower stations during the day is constructed. S4. The NSGA-II multi-objective intelligent optimization algorithm is used to solve different traffic scenarios and obtain a multi-objective scheduling solution set. S5. Compare the power generation benefits of the multi-objective scheduling solution with those of the simulated scheduling, and propose a power generation benefit allocation scheme between cascades.

2. The intraday joint dispatching method for time-of-use pricing under tiered connection as described in claim 1, characterized in that, Specifically, S1 is: ； ； in, Indicates the first Hydropower station The dry season of the year day Hourly natural inflow; Indicates the first Hydropower station The dry season of the year day Hourly electricity price; This indicates the total number of years to be calculated; Indicates the total number of days in the dry season; This indicates the total number of reservoirs.

3. The intraday joint dispatching method for time-of-use pricing under cascade connection as described in claim 2, characterized in that: In S2, the hourly natural inflow process of the cascade hydropower stations during the dry season and the time-of-use electricity price of the cascade hydropower stations are converted into dimensionless curves using a normalization method, specifically: ； ； ； ； in, Indicates the first Hydropower station The dry season of the year day Hourly normalized natural inflow; Indicates the first Hydropower station The dry season of the year day Electricity price normalized to hourly rate; In step S2, the matching degree between the normalized dimensionless curve of the hourly natural inflow of the cascade hydropower stations during the dry season and the dimensionless curve of the time-of-use electricity price of the cascade hydropower stations is calculated, specifically as follows: ； in, Represents the normalized i-th Hydropower station The dry season of the year The matching degree between daily inflow and time-of-use electricity price is expressed as Euclidean distance; In S2, different flow scenarios are selected: the corresponding inflow flow scenario is selected according to the principle of maximizing or minimizing the matching degree between the daily inflow process of each hydropower station and the time-of-use electricity price.

4. The intraday joint dispatching method for time-of-use pricing under tiered connection as described in claim 3, characterized in that: In S3, with the optimization objective of maximizing the daily power generation efficiency of each cascade hydropower station during the dry season, a joint daily dispatch model for the cascade hydropower stations is constructed, specifically as follows: S301. Objective Function Construction: Taking the maximization of daily power generation efficiency of each hydropower station during the dry season as the optimization objective, the calculation is as follows: ； in, Indicates the first Hydropower station The dry season of the year Daily power generation benefits; Indicates the first Hydropower station The dry season of the year day Hourly effort; This indicates a long calculation period for hydropower station dispatching; S302. Constraint Settings: These include hydropower station water balance constraints, output limit constraints, water level boundary constraints, downstream flow constraints, initial and final water level constraints during the scheduling period, and flow evolution constraints, calculated as follows: ； ； ； ； ； ； in, Indicates the first Hydropower station The dry season of the year day Hourly outbound flow; Indicates the first Hydropower station The dry season of the year day Hourly storage capacity; Indicates the first Hydropower station The dry season of the year day Minimum output per hour; Indicates the first Hydropower station The dry season of the year day Maximum output per hour; Indicates the first Hydropower station The dry season of the year day Hourly water level; Indicates the first Hydropower station The dry season of the year day Hourly lowest water level; Indicates the first Hydropower station The dry season of the year day Highest water level in hours; Indicates the first Hydropower station The dry season of the year day Minimum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year day Maximum outbound flow rate per hour; Indicates the first Hydropower station The dry season of the year Initial water level during daily scheduling; Indicates the first Hydropower station The dry season of the year Daily water level at the end of the dispatch period; Indicates the first Hydropower station The dry season of the year day Inflow within hourly intervals; In S3, the impact of cascade connection on the minimum downstream flow constraint of the hydropower station is considered, specifically as follows: S303. When the water level of the downstream hydropower station is lower than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled by instantaneous discharge, that is: ； in, Indicates the first The hydropower station during the dry season Minimum instantaneous discharge flow rate per day; Indicates the first The water level at which the hydropower station connects with the upstream hydropower station; S304. When the water level of the downstream hydropower station is higher than the connecting water level, the minimum discharge flow of the upstream hydropower station shall be controlled according to the average daily water volume, that is: ； in, Indicates the first Hydropower station Minimum daily discharge volume.

5. The intraday joint dispatching method for time-of-use pricing under tiered connection as described in claim 4, characterized in that, Specifically, S4 is: S401. Taking the hourly outflow from the cascade hydropower stations as the decision variable, the calculation expression is as follows: ； S402. Set the parameter values ​​for the NSGA-II multi-objective intelligent optimization algorithm, including: number of iterations. Population size Cross coefficient Coefficient of variation parameter; S403. Taking maximizing the power generation efficiency of each hydropower station during the dry season as the optimization objective, multi-objective optimization is performed on different selected flow scenarios to obtain a multi-objective scheduling solution set, which is calculated as follows: ； in, Indicates the first Population number Hydropower station The dry season of the year day Hourly outbound flow.

6. The intraday joint dispatching method for time-of-use pricing under tiered connection as described in claim 5, characterized in that, Specifically, S5 is: S501. Using a simulated dispatching method, calculate the power generation benefits of each hydropower station under simulated dispatching of cascade hydropower stations, specifically: ； in, Indicates the first Hydropower station The dry season of the year The daily simulated power generation efficiency is calculated using the following formula: ； in, Indicates the first Hydropower station The dry season of the year Daily simulated power output scheduling; S502. Select the solution that maximizes the sum of the power generation benefits of the cascade hydropower stations in the multi-objective scheduling solution. Specifically: ； ； in, In the multi-objective scheduling solution set, the first... Population number Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first cascade hydropower station The dry season of the year The solution set number corresponding to the maximum daily power generation benefit; S503. Using a weighted allocation method, the solution that maximizes the sum of the power generation benefits of cascade hydropower stations in the multi-objective scheduling solution is redistributed, specifically as follows: ； in, The solution set that maximizes the benefits of cascade power generation is represented by the first... Hydropower station The dry season of the year Daily simulated dispatch power generation benefits; Indicates the first Hydropower station distribution of power generation benefits; Indicates the first The weighting of power generation benefits for hydropower stations.

7. A daytime joint dispatching system adapted to time-of-use pricing under tiered connection, characterized in that, include: At least one processor, and a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by the processor to implement the intraday joint scheduling method for time-of-use pricing under cascade connection as described in any one of claims 1 to 6.

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