A method, device and medium for improving dry season hydroelectric regulation power

Abstract

The application discloses a method, equipment and medium for improving dry season water and electricity regulation power, and comprises the following specific steps: constructing a dry season regulation power potential tapping model, obtaining water balance, reservoir water level, reservoir discharge flow, water power matching between cascade hydropower stations, power station output and section power transmission as constraint conditions; selecting maximization of total water, wind, light and clean energy generation in a year and maximization of dry season output in a year as a target function, and optimizing the dry season regulation power potential tapping model; using a POA algorithm to solve the optimized potential tapping model to obtain optimal output of the dry season water and electricity regulation power. By selecting maximization of total water, wind, light and clean energy generation in a year and maximization of dry season output in a year as a target function, a medium and long term collaborative optimization model is constructed. In the model construction process, the constraint conditions are considered, the regulation power of the water and electricity can be improved through the coordinated operation of the cascade reservoirs, so that the potential of the water and electricity regulation wind and light is tapped, and the power demand is met.

Description

Technical Field

[0001] This invention relates to the field of hydropower regulation technology, specifically to a method, device, and medium for increasing the hydropower regulation capacity during the dry season. Background Technology

[0002] In the operation of integrated hydropower, wind, and solar energy systems, the regulation capacity of hydropower plays a crucial role. This is mainly because hydropower stations have unparalleled advantages in regulation within such integrated systems. With the rapid development and widespread application of new energy technologies, research on integrated hydropower, wind, and solar energy systems has attracted increasing attention. Among these research topics, optimizing the regulation capacity of hydropower and improving the system's operational efficiency has become a key issue. The core idea is to fully leverage the complementarity between various energy sources, adjusting hydropower operation strategies to mitigate wind and solar power output, and ultimately maximizing energy utilization efficiency.

[0003] Optimizing the regulation capacity of hydropower can improve the overall efficiency of integrated hydro, wind, and solar energy systems, compensating for the limitations of single energy sources like wind or solar power in terms of power generation capacity. More specifically, the regulation capacity of hydropower can be used to provide necessary electricity when wind or solar power generation is insufficient, and to store excess electricity for later use when there is a surplus.

[0004] Hydropower output is lower during the dry season due to the influence of water inflow, while wind and solar power output is higher during the dry season for hydropower. This results in limited hydropower regulation capacity for wind and solar power during the dry season. To fully utilize the regulating role of reservoir power stations with regulation capabilities and improve the utilization rate of cascade water resources, coordinated and optimized scheduling of cascade hydropower stations is crucial. During the dry season, hydropower output is lower due to the influence of water inflow. At this time, the joint scheduling of cascade reservoirs should be fully utilized, especially the Pubugou Reservoir with regulation capacity. Through reasonable regulation, the output during the dry season can be increased, so that the monthly output difference between hydropower, wind power, and photovoltaic power is smaller, and the portion that can withstand the base load in the power grid can be maximized. At the beginning of the flood season, priority should be given to impounding water in reservoirs with weak regulation capacity, followed by reservoirs with regulation capacity, to increase the generating head of the power station group, thereby increasing the hydropower output used to regulate wind and solar power and increasing the absorption of wind and solar power. After the flood season, reservoirs with regulation capacity should be given priority to increase power production to replenish the downstream cascade reservoirs. This can significantly improve the regulation capacity of cascade power stations during the dry season and help stabilize the fluctuations in wind and solar power. Therefore, a method is needed to increase the amount of hydropower regulated during the dry season to meet the above requirements. Summary of the Invention

[0005] The technical problem this invention aims to solve is that the hydropower regulation capacity for wind and solar power is limited during the dry season, failing to meet electricity demand. The objective is to provide a method, equipment, and medium to improve the hydropower regulation capacity during the dry season. By selecting the maximum annual total clean energy generation from hydropower, wind power, and solar power, and the maximum annual dry season output as objective functions, a medium- to long-term collaborative optimization model is constructed. During model construction, the following constraints are considered: water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output, cross-sectional transmission constraints, and non-negative constraints. This allows for the coordinated operation of cascade reservoirs to improve the hydropower regulation capacity, thereby unlocking the potential of hydropower for wind and solar power regulation.

[0006] This invention is achieved through the following technical solution:

[0007] The first aspect of this invention provides a method for increasing the amount of hydropower regulation during the dry season, comprising the following specific steps:

[0008] Construct a potential model for regulating electricity volume during the dry season;

[0009] Using water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output and cross-sectional power transmission as constraints, and selecting the maximum annual total power generation of clean energy from hydropower, wind power and solar power and the maximum annual dry season output as objective functions, the potential tapping model for dry season regulation power is optimized.

[0010] The POA algorithm was used to solve the optimized potential tapping model to obtain the optimal output of hydropower regulation during the dry season.

[0011] This invention constructs a medium- to long-term collaborative optimization model by selecting the maximum annual total power generation from clean energy sources such as hydropower, wind power, and solar power, and the maximum dry season output within the year as objective functions. In the process of model construction, the following constraints are considered: water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output, cross-sectional transmission constraints, and non-negative condition constraints. It can improve the regulation capacity of hydropower through the coordinated operation of cascade reservoirs, thereby tapping the potential of hydropower to regulate wind and solar power and meeting the power demand.

[0012] Furthermore, the constraints include water balance constraints, reservoir water level constraints, reservoir discharge flow constraints, power plant output constraints, and cross-sectional transmission constraints, all of which are non-negative constraints.

[0013] Furthermore, the water balance constraint includes:

[0014] Obtain the water discharge and power generation flow of the i-th hydropower station in time period t, and determine the discharge flow of the i-th hydropower station in time period t;

[0015] Obtain the initial reservoir storage and inflow of the i-th hydropower station in time period t. Combine this with the outflow of the i-th hydropower station in time period t to determine the final reservoir storage of the i-th hydropower station in time period t.

[0016] Furthermore, the reservoir water level constraint includes:

[0017] Obtain the minimum and maximum allowable water levels and the flood control limit water level of the i-th hydropower station at time t, and determine the water level of the i-th hydropower station at time t.

[0018] Furthermore, the reservoir discharge flow constraints and the hydraulic constraints between the cascade hydropower stations include:

[0019] Obtain the minimum discharge flow that should be guaranteed for the i-th hydropower station in time period t, the maximum allowable discharge flow, and the ecological flow of the i-th hydropower station in time period t. Determine the reservoir discharge flow of the i-th hydropower station in time period t and the discharge flow of the (i-1)-th hydropower station at time t.

[0020] Obtain the average inflow between the (i-1)th and ith hydropower stations at time t to determine the hydraulic conditions between the cascade hydropower stations.

[0021] Furthermore, the power plant output constraints and cross-sectional transmission constraints include:

[0022] Obtain the minimum and maximum allowable output of the i-th power station of the j-th power station during the t-th time period, and determine the power station output;

[0023] Obtain the set of transmission sections, the transmission section number, the transmission limit of section d, and the number of power stations of type j within section d. Combine this with the power station output to determine the transmission capacity of the transmission section.

[0024] Furthermore, the objective function construction step includes maximizing the annual power generation of clean energy sources such as hydropower, wind power, and solar power, and maximizing the output during the dry season within the year;

[0025] The steps for maximizing the total clean energy power generation from hydropower, wind power, and solar power within the year include:

[0026]

[0027] In the formula, i represents the power station variable; j = w, s, and h represent the wind farm, photovoltaic power station, and hydropower station, respectively; n j t represents the total number of power plants of type j; t represents the time period variable; T represents the total number of time periods calculated within the year; E represents the annual power generation of clean energy; N represents the total number of power plants of type j. j,it N represents the power output of the i-th power station of the j-th type of power station during the t-th time period; h,it Q represents the power output of the i-th hydropower station during time period t; i,t For the i-th hydropower station in the t-th time period; H i,tLet be the generating head of the i-th hydropower station in the t-th time period; k is the conversion factor; Δt is the number of hours in the t-th time period within the year;

[0028] The steps for maximizing dry season output during the year include:

[0029]

[0030] In the formula, NP represents the dry season output of clean energy.

[0031] Furthermore, the step of solving the optimized potential tapping model using the POA algorithm includes:

[0032] S1 uses the equal flow rate method to determine the initial water level of each reservoir.

[0033] S2 optimizes the hydropower stations sequentially according to the hydraulic connection order of the cascade hydropower stations.

[0034] S3 traverses the power output process of wind power and hydropower at all times;

[0035] S4. Repeat steps S2 and S3 until the target requirement is met.

[0036] A second aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for increasing the amount of hydropower regulation during the dry season.

[0037] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for increasing the amount of hydropower regulation during the dry season.

[0038] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0039] A medium- to long-term collaborative optimization model is constructed by selecting the maximum annual power generation from clean energy sources (hydropower, wind power, and solar power) and the maximum power output during the dry season as objective functions. During model construction, the following constraints are considered: water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output, cross-sectional transmission constraints, and non-negative constraints. This model demonstrates how coordinated operation of cascade reservoirs can improve the regulation capacity of hydropower, thereby unlocking the potential of hydropower to regulate wind and solar power. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0041] Figure 1 This is a flowchart of a method for increasing hydropower regulation power during the dry season, as described in an embodiment of the present invention.

[0042] Figure 2 This is a schematic diagram of the reservoir capacity-water level relationship curves of the three stations, Pubugou, Shenxigou, and Zhentouba, in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the flow-tailwater level relationship curves of the three stations, Waterfall Gully, Deep Creek Gully, and Pillow Dam, in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the overall calculation results for tapping and improving the scenic potential of Waterfall Gully, Deep Creek Gully, Pillow Dam and surrounding areas in an embodiment of the present invention;

[0045] Figure 5 This is a schematic diagram of the calculation results for improving the power sources of Waterfall Gully, Deep Creek Gully, Pillow Dam and surrounding scenery in an embodiment of the present invention;

[0046] Figure 6 This is a schematic diagram of the total power output process before the optimization of Waterfall Gully, Deep Creek Gully, Pillow Dam and surrounding scenery in an embodiment of the present invention;

[0047] Figure 7 This is a diagram showing the power output process of different power sources before the optimization of Waterfall Gully, Deep Creek Gully, Pillow Dam and surrounding scenery in an embodiment of the present invention;

[0048] Figure 8 This is a comparison chart of the monthly hydropower output process and the total power generation of hydropower, wind power, and solar power in the actual operation and after optimization in the embodiments of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0050] Example 1

[0051] like Figure 1 As shown, the first aspect of this embodiment provides a method for increasing the amount of hydropower regulation during the dry season, including the following specific steps:

[0052] A potential model for regulating power generation during the dry season is constructed, and water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output and cross-sectional power transmission are obtained as constraints.

[0053] The model for tapping the potential of dry season power regulation is optimized by selecting the total annual power generation of clean energy from hydropower, wind power, and solar power as the objective functions and the maximum power output during the dry season.

[0054] The POA algorithm was used to solve the optimized potential tapping model to obtain the optimal output of hydropower regulation during the dry season.

[0055] This embodiment constructs a medium- to long-term collaborative optimization model by selecting the maximum annual power generation from clean energy sources (hydropower, wind power, and solar power) and the maximum dry season output as objective functions. During model construction, the following constraints are considered: water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output, cross-sectional transmission constraints, and non-negative constraints. This model can improve the regulation capacity of hydropower through coordinated operation of cascade reservoirs, thereby unlocking the potential of hydropower to regulate wind and solar power and meeting electricity demand.

[0056] In some possible embodiments, the constraints include water balance constraints, reservoir water level constraints, reservoir discharge constraints, power plant output constraints, and cross-sectional transmission constraints. All constraints are non-negative, specifically including:

[0057] (1) Water balance constraint:

[0058]

[0059] In the formula, V i,t V i,t+1 R represents the initial and final water storage of the i-th reservoir during time period t, respectively. i,t Let Q be the inflow rate of the i-th reservoir during the t-th time period. ri,t The discharge flow of the i-th reservoir during time period t is S. i,t Let Q be the discharge flow rate of the i-th reservoir during the t-th time period. i,t Let be the power generation flow of the i-th reservoir during the t-th time period;

[0060] (2) Reservoir water level constraints: Limit the water level of each reservoir to ensure that the water level fluctuates within the allowable range, including flood control water level constraints during the flood season;

[0061]

[0062] In the formula, Z i,t Let be the water level of the i-th reservoir at time t; These are the minimum and maximum water levels allowed for the i-th reservoir at time t, respectively. Let be the flood control limit water level of the i-th reservoir at time t;

[0063] (3) Reservoir discharge constraints, including ecological water demand constraints;

[0064]

[0065] In the formula, These represent the minimum discharge flow and the maximum allowable discharge flow that the i-th hydropower station should guarantee during the t-th time period, respectively. Let be the ecological flow of the i-th hydropower station in time period t;

[0066] (4) Hydraulic matching constraints between cascade power stations:

[0067] R i,t =Q ri-1,t +I i,t

[0068] In the formula, Q ri-1,t Let I be the discharge flow rate of the (i-1)th hydropower station at time t; i,t Let be the average inflow between the (i-1)th hydropower station and the ith hydropower station at time t;

[0069] (5) Power plant output constraints:

[0070]

[0071] In the formula, These represent the minimum and maximum allowable output of the i-th power station of the j-th power station during the t-th time period;

[0072] (6) Transmission section constraints: Assuming there are D transmission sections in total, the following constraints must be satisfied for any section d:

[0073]

[0074] In the formula: D is the set of transmission sections; d is the transmission section number; N d The transmission limit of section d; n jd The number of power stations of type j within cross section d;

[0075] (7) Nonnegativity constraint

[0076] All of the above variables are non-negative.

[0077] In some possible embodiments, the steps for maximizing the total clean energy generation from hydro, wind, and solar power within a year include:

[0078]

[0079] In the formula, i represents the power station variable; j = w, s, and h represent the wind farm, photovoltaic power station, and hydropower station, respectively; n j t represents the total number of power plants of type j; t represents the time period variable; T represents the total number of time periods calculated within the year; E represents the annual clean energy power generation; m t N represents the unit capacity during time period t; j,it N represents the power output of the i-th power station of the j-th type of power station during the t-th time period; h,it Q represents the power output of the i-th hydropower station during time period t; i,t For the i-th hydropower station in the t-th time period; H i,t Let be the generating head of the i-th hydropower station in the t-th time period; k is the conversion factor; Δt is the number of hours in the t-th time period within the year;

[0080] The calculation steps for maximizing dry season output during the year include:

[0081]

[0082] In the formula, NP represents the dry season output of clean energy.

[0083] In some possible embodiments, the steps of solving the optimized potential tapping model using the POA algorithm include:

[0084] S1 uses the equal flow rate method to determine the initial water level of each reservoir.

[0085] S2 optimizes the hydropower stations sequentially according to the hydraulic connection order of the cascade hydropower stations.

[0086] S3 traverses the power output process of wind power and hydropower at all times;

[0087] S4. Repeat steps S2 and S3 until the target requirement is met.

[0088] The second aspect of this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a method for increasing the amount of hydropower regulation during the dry season.

[0089] The third aspect of this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for increasing the amount of hydropower regulation during the dry season.

[0090] Example 2

[0091] Using an established model and corresponding algorithm for improving the regulation capacity of hydropower during the dry season, this paper presents a case study on the medium- and long-term regulation capacity of the Pubugou, Shenxigou, and Zhentouba hydropower stations and surrounding wind and solar power facilities. In the calculations, except for the Pubugou hydropower station which possesses annual regulation capacity, the other hydropower stations have relatively weak regulation capabilities and can even be classified as run-of-river hydropower stations. Therefore, when conducting research on improving the regulation capacity during the dry season at a medium- and long-term scale, the Shenxigou and Zhentouba hydropower stations are considered uniformly according to the characteristics of run-of-river hydropower stations.

[0092] Basic Information

[0093] A study was conducted on tapping the potential of the three hydropower stations (Bupugou, Shenxigou, and Zhentouba) and their surrounding landscape to increase power generation during the dry season. The relevant basic parameters of the cascade hydropower stations are shown in Table 1. Figure 2 and Figure 3 As shown in Tables 2 and 3, the basic parameters and power output process of wind and solar power are shown in Table 2 and Table 3.

[0094] Table 1 Basic parameters of the three stations: Pubugou, Shenxigou, and Zhentouba

[0095] power station Waterfall Valley Deep Creek Pillow Dam Installed capacity / 10,000 kW 360.00 66.00 72.00 Dead water level / m 790 655 618 Normal water level / m 850 660 624 Flood control water level 836.2 / 841 none none Design head / m 154.60 34.61 33.00 <![CDATA[Dead storage capacity / 100 million m 3 > 11.17 0.28 0.29 <![CDATA[Regulation capacity / 100 million m 3 > 38.94 0.08 0.12 <![CDATA[Storage capacity below normal pool level / 100 million m 3 > 50.11 0.36 0.41 Output coefficient 8.29 8.38 8.34 Flood control task have none none <![CDATA[Maximum discharge flow m 3 / s]]> 2772.00 2619.00 2697.00 <![CDATA[Minimum discharge flow m 3 / s]]> 327 327 327 Flow time (min) 0 20 25 Head loss m 5.00 2.00 2.00 Adjustment performance Incomplete annual adjustment Daily Adjustment Daily Adjustment

[0096] Table 2 Basic parameters of wind and solar power around Pubugou

[0097] power supply Scale (10,000 kW) wind power 35 Photovoltaics 126

[0098] Table 3 Annual Output of Wind Power and Solar Power

[0099] month Wind power / 10,000 kW Photovoltaics / 10,000 kW June 4.41 14.57 July 2.59 12.28 August 3.67 14.60 September 3.87 14.90 October 6.44 12.74 November 7.04 17.50 December 4.84 18.65 January 6.8 19.12 February 6.72 18.69 March 8.9 19.86 April 7.18 18.16 May 5.14 15.23

[0100] Calculation results:

[0101] The power outputs of the three stations (Bupugou, Shenxigou, and Zhentouba) and the surrounding wind and solar power were incorporated into the established model, and the results are shown in Tables 4 and 5. Figure 4 and Figure 5 As shown, the calculation results for the Waterfall Gully, which serves as a regulating reservoir, are listed separately.

[0102] Table 4. Calculation results of potential tapping for the Pubugou Hydropower Station

[0103]

[0104] Table 5. Calculation Results of Potential Enhancement for Waterfall Gully, Deep Creek Gully, Pillow Dam and Surrounding Scenery

[0105]

[0106] Results analysis:

[0107] Before optimization

[0108] To verify the validity and applicability of the calculation results of the power regulation mining model for the Bupugou, Shenxigou, Zhentouba, and surrounding wind and solar power, this embodiment uses the operating data of the Bupugou, Shenxigou, Zhentouba, and surrounding wind and solar power in selected typical years (as shown in Tables 6 and 7). Figure 6 , Figure 7 The results of the optimization calculations (shown in the figure) are compared with those of the mining model based on increasing hydropower regulation during the dry season constructed in this embodiment. This analysis demonstrates the effectiveness and applicability of the model in practical application scenarios and provides valuable reference for future research and practice.

[0109] Table 6. Actual Operation Process of Pubugou Hydropower Station

[0110]

[0111] Table 7. Actual Operation Process of Waterfall Gully, Deep Creek Gully, Pillow Dam and Surrounding Scenery

[0112]

[0113] Comparative analysis

[0114] The actual operating results and the optimized results were compared and analyzed, and the results are as follows:

[0115] (1) The monthly output of the Pubugou, Shengou, and Zhengou hydropower stations showed little change before and after optimization during the flood season. This is because the Pubugou hydropower station also has flood control responsibilities during the flood season, and is limited by the flood control water level, leaving limited room for adjustment. However, after optimization during the dry season, the regulation capacity of the Pubugou reservoir was fully tapped, from Figure 8 It can be seen that after the optimization of the dry season, the monthly power output of the three stations of Pubugou, Shenxigou, and Zhentouba has significantly reduced the fluctuations compared with the actual operation. The average monthly power output during the dry season has increased by 430,000 kW, and the potential tapping effect during the dry season is obvious.

[0116] (2) In the analysis of the total amount of hydropower, wind power and photovoltaic power generation, the actual total power generation of hydropower, wind power and photovoltaic power generation was 2172040 million kWh. After optimization by the power generation adjustment and enhancement model, the total power generation of hydropower, wind power and photovoltaic power generation increased to 2240259 million kWh, and the annual power generation increased by 68219 million kWh, which is 3.1% growth compared with the initial power generation.

[0117] In summary, the analysis shows that the potential tapping model based on increasing the regulation of hydropower during the dry season can improve the regulation capacity of wind and solar power by increasing hydropower generation during the dry season.

[0118] This embodiment addresses the issue of insufficient hydropower output during the dry season in the Pubugou, Shenxigou, and Zhentouba sections of the Dadu River basin. It explores a potential-tapping model based on increasing the regulating power output during the dry season, aiming to maximize the hydropower regulation capacity, absorb wind and solar power, and mitigate their fluctuations. By optimizing the power generation potential of the cascade reservoirs, the hydropower output is increased, thereby better regulating wind and solar power fluctuations and improving the utilization rate of transmission channels. The main conclusions are as follows:

[0119] (1) First, the model construction is described, including maximizing clean energy power generation and minimizing power output as objective functions, while considering constraints such as water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output, cross-sectional transmission constraints, and non-negativity constraints. Based on this, the successive optimization algorithm (POA) is selected to solve the model.

[0120] (2) A case study was conducted using the three hydropower stations (Bupugou, Shenxigou, and Zhentouba) and their surrounding wind and solar power in the Dadu River basin as examples. By comparing actual operating data and optimized calculation results, the effectiveness and applicability of the model in practical application scenarios were verified. In the optimized results, the total power generation increased by 3.1%, and the monthly output of hydropower, wind power, and solar power during the dry season remained stable at approximately 2.08 million kW, fully demonstrating the rationality and scientific nature of the proposed model based on improving the potential of hydropower regulation during the dry season.

[0121] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for increasing the amount of hydropower regulation during the dry season, characterized in that, The specific steps include the following: Construct a potential model for regulating electricity volume during the dry season; Using water balance, reservoir water level, reservoir discharge flow, hydraulic matching between cascade power stations, power station output and cross-sectional power transmission as constraints, and selecting the maximum annual total power generation of clean energy from hydropower, wind power and solar power and the maximum annual dry season output as objective functions, the potential tapping model for dry season regulation power is optimized. The steps for maximizing the total clean energy power generation from hydropower, wind power, and solar power within the year include: ； In the formula, i is the power station variable; j=w, s, and h are wind farm, photovoltaic power station, and hydropower station, respectively; For the first Total number of power stations of this type; For time period variables; To calculate the total number of time periods within the year; Annual electricity generation from clean energy sources; The unit capacity during time period t; For the first Class 1 power station The first power station Efforts during a specific time period; For the first The first hydropower station Power generation output during a given period; For the first The first hydropower station Time period; For the first The first hydropower station Hydropower head during the specified time period; These are conversion factors; The first in the year The number of hours in the time period; The steps for maximizing dry season output during the year include: ； In the formula, Contribute to clean energy during the dry season; The POA algorithm was used to solve the optimized potential tapping model to obtain the optimal output of hydropower regulation during the dry season.

2. The method for increasing hydropower regulation capacity during the dry season according to claim 1, characterized in that, The constraints include water balance constraints, reservoir water level constraints, reservoir discharge flow constraints, power plant output constraints, and cross-sectional power transmission constraints, all of which are non-negative constraints.

3. The method for increasing hydropower regulation capacity during the dry season according to claim 2, characterized in that, The water balance constraints include: Obtain the water discharge and power generation flow of the i-th hydropower station in time period t, and determine the discharge flow of the i-th hydropower station in time period t; Obtain the initial reservoir storage and inflow of the i-th hydropower station in time period t. Combine this with the outflow of the i-th hydropower station in time period t to determine the final reservoir storage of the i-th hydropower station in time period t.

4. The method for increasing hydropower regulation capacity during the dry season according to claim 2, characterized in that, The reservoir water level constraints include: Obtain the minimum and maximum allowable water levels and the flood control limit water level of the i-th hydropower station at time t, and determine the water level of the i-th hydropower station at time t.

5. The method for increasing hydropower regulation capacity during the dry season according to claim 2, characterized in that, The reservoir discharge constraints and the hydraulic constraints between cascade hydropower stations include: Obtain the minimum discharge flow that should be guaranteed for the i-th hydropower station in time period t, the maximum allowable discharge flow, and the ecological flow of the i-th hydropower station in time period t. Determine the reservoir discharge flow of the i-th hydropower station in time period t and the discharge flow of the (i-1)-th hydropower station at time t. Obtain the average inflow between the (i-1)th and ith hydropower stations at time t, and determine the hydraulics between the cascade hydropower stations.

6. The method for increasing hydropower regulation capacity during the dry season according to claim 2, characterized in that, The power plant output constraints and cross-sectional transmission constraints include: Obtain the minimum and maximum allowable output of the i-th power station of the j-th power station during the t-th time period, and determine the power station output; Obtain the set of transmission sections, the transmission section number, the transmission limit of section d, and the number of power stations of type j within section d. Combine this with the power station output to determine the transmission capacity of the transmission section.

7. The method for increasing hydropower regulation capacity during the dry season according to claim 1, characterized in that, The steps for solving the optimized potential tapping model using the POA algorithm include: S1 uses the equal flow rate method to determine the initial water level of each reservoir. S2 optimizes the hydropower stations sequentially according to the hydraulic connection order of the cascade hydropower stations. S3 traverses the power output process of wind power and hydropower at all times; S4 repeats steps S2 and S3 until the target requires stopping.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for increasing hydropower regulation power during the dry season as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for increasing hydropower regulation capacity during the dry season as described in any one of claims 1 to 7.

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