Optimization method of water-air-solar complementary power generation and ice prevention considering water storage

Abstract

The application discloses a water, wind and light complementary power generation and ice jam prevention scheduling optimization method considering water storage energy, wherein the water storage energy is a reversible unit or a water pumping large pump, and the method comprises the following steps: constructing a long-term model of double-target optimization scheduling of a cascade reservoir with the smallest water supply gap and the largest power generation, and a short-term model of double-target optimization scheduling of a water, wind, light and storage system with the smallest power supply and demand gap and the smallest abandoned wind and light rate; taking non-flood period ten-day scale runoff as the long-term model input, and solving by using a multi-objective algorithm to obtain ten-day scale water level, reservoir capacity, flow and power process of the cascade reservoir; taking the beginning and end reservoir capacities of the first ten-day period of the long-term model as boundaries, and taking hourly scale runoff, photovoltaic and wind power as the short-term model input, and solving by using a multi-objective algorithm to obtain the hourly scale process of the cascade reservoir and the reversible unit or the water pumping large pump; feeding back the short-term end reservoir capacity to the long-term model, rolling updating the remaining period model input, and iteratively calculating the long-term and short-term coupling to gradually complete the non-flood period optimization scheduling scheme.

Description

Technical Field

[0001] This invention relates to the field of cascade reservoir optimization scheduling technology, and in particular to an optimization method for water-wind-solar hybrid power generation and ice prevention scheduling that considers water storage. Background Technology

[0002] Reservoir ice control scheduling refers to the process of regulating the winter flow of nearby regulating reservoirs upstream of frozen river sections to improve water flow conditions and thus control ice conditions and ice disasters. During the ice-floe period, the reservoir releases a large flow to meet the requirements of high flow and high ice cover for river freezing, and to free up necessary ice control storage capacity to impound water from upstream power generation. During the river freezing period, the reservoir releases water within the flow range required for ice control operation, while avoiding drastic fluctuations in the release flow to maintain the stability of the river ice cover. During the thawing period, the reservoir release flow is appropriately reduced to maintain a stable or slow decline in the river level, achieving a "gentle thawing".

[0003] For example, the upper reaches of the Yellow River undertake comprehensive water resource utilization tasks such as flood control, ice jam control, water supply, power generation, ecological restoration, and sediment transport. To date, more than 20 hydropower projects have been built in this section, forming a cascade reservoir system represented by Longyangxia (with multi-year regulation capacity) and Liujiaxia (with annual regulation capacity). The ice jam control period for the Ningxia-Inner Mongolia section of the upper Yellow River is from November to March of the following year. On average over many years, ice floes typically begin to form in late November, freeze over in early December, and thaw in mid-to-late March of the following year, with a freezing period of about 120 days and a frozen river length of up to 1000 km. For a long time, relevant departments have explored a joint operation mode for the Longyangxia and Liujiaxia reservoirs (hereinafter referred to as "Long-Liu reservoirs"), using the Lanzhou section as the ice jam control flow control section to ensure the safety of the Ningxia-Inner Mongolia section during the ice jam period. According to ice jam prevention requirements, the Liujiaxia Reservoir needs to increase its discharge flow in late November each year to ensure that the Lanzhou section meets the minimum flow limit (greater than 650 m³ / s) in order to achieve high-flow river freezing, while reserving a certain amount of ice jam prevention capacity (1-1.5 billion m³). 3This is to accommodate the increased water release from the Longyangxia Reservoir due to the limited outflow from the Liujiaxia Reservoir and to meet the winter power load demand of the Northwest Power Grid. Through controlled release from the Liujiaxia Reservoir, the minimum monthly flow at the Lanzhou section (December, January, February, March) should be controlled at 500, 400, 500, and 450 m³ / s respectively, and the maximum flow should be controlled at 700, 700, 700, and 600 m³ / s respectively. To balance the power shortage in the Northwest Power Grid, the Longyangxia Reservoir increases its water release during this period, driving increased power generation from the cascade hydropower stations between the Longyangxia and Liujiaxia reservoirs. The water level of the Liujiaxia Reservoir gradually rises as it receives the increased water release from the Longyangxia Reservoir. This ice-fighting scheduling method, which reserves ice-fighting capacity at Liujiaxia Dam and constrains the outflow from Liujiaxia, ensures the safety of ice flooding in the Ningxia-Inner Mongolia section. However, by lowering the water level in front of Liujiaxia Dam and the head for power generation during the ice-fighting period, it inevitably leads to reduced power generation efficiency and increased water consumption, thus impairing the hydropower benefits of Liujiaxia. How to coordinate the relationship between the water dispatching and power dispatching departments, and balance the dual benefits of ice-fighting safety (i.e., not exceeding the outflow constraint of Liujiaxia Dam) and hydropower (i.e., achieving increased power generation benefits of the Long-Liu cascade without reserving or reserving ice-fighting capacity at Liujiaxia Dam during the ice-fighting period), has long been a major challenge for both departments.

[0004] On the other hand, to achieve the "dual carbon" goal, my country is actively promoting the construction of a new power system based on wind and solar power. Under the new circumstances and requirements, the installed capacity and generation share of wind and solar power in the power structure have increased significantly. However, wind and solar power output is random, intermittent, and fluctuating, and large-scale grid connection will put considerable pressure on the safe and stable operation of the power system. Hydropower has excellent peak-shaving capabilities; bundling hydropower with wind and solar power output for transmission can effectively increase the absorption of new energy and reduce wind and solar curtailment. At the same time, the country is also vigorously developing various types of energy storage to alleviate the short-term and long-term balancing pressure caused by the mismatch between new energy output and power load demand, providing strong support for the large-scale grid connection and efficient utilization of new energy.

[0005] The main characteristics of existing technologies are as follows: First, in terms of scheduling objectives, most technologies consider the combination of cascade reservoirs and ice prevention safety objectives during ice-prone period scheduling, with few technologies focusing on new energy consumption objectives. Second, in terms of time scale, hydro-wind-solar hybrid power generation and ice prevention scheduling have different research scales. Ice prevention scheduling usually considers long-term scales, with a research span generally from the ice-prone period (November to March of the following year) or a year, and a time step generally in ten days or months. Most hydro-wind-solar hybrid technologies focus on short-term scales, with a research span generally in weeks or days, and a time step generally in hours or 15 minutes. Only a few technologies consider long-term-short-term multi-scale coupling. Third, in terms of water level control, most technologies actively reserve ice prevention reservoir capacity during ice-prone period scheduling, reducing the water level in front of the dam and the power generation head, resulting in reduced power generation efficiency, increased water consumption rate, and damaged hydropower benefits. Fourth, in terms of hydraulic connection, most technologies only consider cascade reservoirs, and the hydraulic connection is a one-way connection from upstream to downstream, with relatively limited adjustment flexibility. Summary of the Invention

[0006] In view of the above-mentioned shortcomings in the prior art, the water-wind-solar complementary power generation and ice prevention scheduling optimization method considering water energy storage provided by the present invention solves the technical problem that the prior art cannot simultaneously take into account the efficient utilization of water, wind and solar energy and ensure ice prevention safety.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows:

[0008] A method for optimizing hydro-wind-solar hybrid power generation and ice-prevention dispatch considering hydro-energy storage is provided, which includes the following steps:

[0009] S1. Construct a long-term optimization scheduling model with dual objectives of minimizing the water supply gap of cascade reservoirs and maximizing power generation.

[0010] S2. For multi-energy systems consisting of wind power, photovoltaic power, cascade reservoirs and reversible units or large pumps, construct a short-term optimization scheduling model with dual objectives of minimizing the power supply and demand gap and minimizing the wind and solar curtailment rate.

[0011] S3. Using the ten-day scale runoff during the non-flood season as input (e.g., from early November to late June of the following year, a total of 24 ten-day periods), a multi-objective optimization algorithm is used to perform long-term model optimization calculations to obtain the ten-day scale water level process, reservoir capacity process, flow process, and power process of the cascade reservoirs.

[0012] S4. Using the initial and final reservoir capacities of the first ten-day period of the cascade reservoirs in step S3 as the boundary conditions of the short-term model (the first calculation is the initial and final reservoir capacities in early November), and using hourly runoff, photovoltaic power, and wind power as inputs, a multi-objective optimization algorithm is used to perform short-term model optimization calculations to obtain the hourly water level process, reservoir capacity process, flow process, and power process of the cascade reservoirs and reversible units or pumping units in that ten-day period.

[0013] S5. Feed the final reservoir capacity calculated by the short-term model (final reservoir capacity in early November) back to the long-term model. Combine the runoff input during the remaining scheduling period (mid-November to late June of the following year, a total of 23 ten-day periods) and use a multi-objective optimization algorithm to optimize the long-term model. Use the initial and final reservoir capacities calculated by the long-term model at the first ten-day scale of the remaining scheduling period (the second calculation is the initial and final reservoir capacities at mid-November) as the boundary conditions of the short-term model. Use hourly runoff, photovoltaic power, and wind power as inputs and use a multi-objective optimization algorithm to optimize the short-term model.

[0014] S6. Repeat operation S5 to complete the short-term model optimization calculation for each ten-day period during the non-flood season in sequence, so as to obtain the long-term-short-term coupled hydro-wind-solar complementary power generation and ice prevention scheduling optimization scheme.

[0015] Furthermore, the long-term model includes objective functions and constraints, wherein the objective functions include an objective function for minimizing the water supply gap and an objective function for maximizing power generation;

[0016] The objective function for minimizing the water supply gap is expressed as minimizing the water shortage index, and its expression is:

[0017] ;

[0018] in, To minimize the water shortage index; t For time indexing, , T Total time; For the use of water outside the river channel during certain periods t The amount of water shortage; For the use of water outside the river channel during certain periods t Water demand;

[0019] The expression for the objective function that maximizes power generation is:

[0020] ;

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] in, To maximize power generation; i For reservoir indexing; The number of reservoirs; For reservoir i The power station during the period t Electricity generation; For reservoir i The power station during the period The power generation capacity; The time period is long; The density of water; It is the acceleration due to gravity; For reservoir i The power generation efficiency of the power plant; , and Reservoirs i During the period t The discharge flow, power plant generation flow, and wastewater discharge; , , and Reservoirs i The power station during the period t The average head, average water level in front of the dam, average water level behind the dam, and average head loss; For reservoir i During the period t Average storage capacity; and Reservoirs i During the period t Initial and final storage capacity; , , , and and , , , and All coefficients are obtained using polynomial fitting.

[0028] Furthermore, the constraints of the long-term model include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints.

[0029] The expression for the water balance equation is:

[0030] ;

[0031] The expression for the initial / termination storage capacity constraint is:

[0032] ; ;

[0033] The expression for the reservoir capacity constraint is:

[0034] ;

[0035] The expression for the outflow constraint is:

[0036] ;

[0037] The expression for the power generation flow constraint is:

[0038] ;

[0039] The expression for the power output constraint of the hydropower station is:

[0040] ;

[0041] in, For reservoir During the period Inbound traffic; For reservoir During the period Evaporation rate; and Reservoirs During the period The beginning and end of the storage capacity; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level as the minimum capacity and the reservoir capacity corresponding to the normal water level as the maximum capacity. It is worth noting that the innovation of this invention lies in the fact that, considering water energy storage (reversible units or large pumps) and long-term-short-term multi-scale coupling optimization, the maximum reservoir capacity during the ice prevention period is taken as the reservoir capacity corresponding to the normal water level, so no or less ice prevention reservoir capacity may be reserved. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity.

[0042] Furthermore, the multi-objective optimization algorithm is the NSGA-II algorithm, and step S3 further includes:

[0043] S31. Initialize the parameters of the NSGA-II algorithm, using non-flood season decadal runoff as input;

[0044] S32. Using the decadal-scale discharge flow of the cascade reservoirs as the decision variable, the scale is randomly initialized as follows: initial population ;

[0045] S33. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ;

[0046] S34, Population Based on the two objective functions of the long-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto ranks from low to high. ;

[0047] S35. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1;

[0048] S36. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S37; otherwise, return to step S33.

[0049] S37. Obtain the Pareto solution set and output the corresponding process set of water level, storage capacity, flow rate and power of the cascade reservoirs at the ten-day scale.

[0050] This scheme, by constructing long-term and short-term models, and combining the constraints included in the long-term and short-term models with the solution methods for both models, has the following beneficial effects:

[0051] 1. This invention uses the entire non-flood season (November to June of the following year) as the scheduling period. The initial water level during the scheduling period can be controlled according to the normal water storage level, and the water level at the end of the scheduling period can be controlled according to the flood control limit water level. The beginning and end boundaries of the scheduling period are relatively controllable.

[0052] 2. Water management departments (such as the Yellow River Conservancy Commission) usually carry out long-term forecasting and water allocation planning for the non-flood season (November to June of the following year) at the end of the flood season (October) each year, which is the same time span as the present invention. In addition, the long-term forecast results are updated monthly and ten days a week during the non-flood season, for example, November forecasts December, and December forecasts January of the following year, thus supported by long-term hydrological forecast data.

[0053] 3. This invention adopts the form of objective function or constraint conditions to comprehensively consider the goals of water resource utilization such as water supply, ice prevention, power generation, and ecology during the non-flood season; the NSAGA-II algorithm can provide Pareto solution sets for the two objectives of water supply and power generation, rather than a single solution, which can be used by managers to make multi-scheme comparison and selection decisions.

[0054] 4. Since this invention considers water energy storage (reversible units or large pumps) and long-term-short-term multi-scale coupling optimization, the maximum reservoir capacity during the ice prevention period is taken as the reservoir capacity corresponding to the normal water level. Ice prevention reservoir capacity can be reserved or reserved less, so that the lower reservoir can maintain a high water level and improve the hydropower generation efficiency of the lower reservoir.

[0055] Furthermore, the short-term model includes an objective function and constraints, and the method for constructing the objective function includes:

[0056] S21. Construct a power calculation model for cascade reservoirs:

[0057] ;

[0058] ;

[0059] ;

[0060] ;

[0061] ;

[0062] ;

[0063] in, i For reservoir indexing; The number of reservoirs; For all cascade reservoirs during the time period The power generation capacity; For reservoir i The power station during the period The power generation capacity; The density of water; It is the acceleration due to gravity; For reservoir The power generation efficiency of the power plant; , and Reservoirs During the period The discharge flow, power plant generation flow, and wastewater discharge; , , and Reservoirs The power station during the period The average head, average water level in front of the dam, average water level behind the dam, and average head loss; For reservoir During the period Average storage capacity; and Reservoirs During the period Initial and final storage capacity; , , , and and , , , and All coefficients are obtained by polynomial fitting;

[0064] S22. Construct a power calculation model for a reversible generating unit, using the existing reservoir as the upper and lower reservoirs. This model includes a power generation calculation model and a pumping power consumption calculation model, with the following expressions:

[0065] ;

[0066] ;

[0067] in, and These represent all reversible units during the time period. Power generation and pumping capacity; and Reservoirs With reservoir Reversible units between During the period Power generation and pumping capacity; and These represent reversible units. Power generation efficiency and pumping efficiency; and These represent reversible units. During the period Power generation flow and pumping flow; and Reservoirs With reservoir During the period The average water level in front of the dam; and These represent reversible units. During the period Average head loss for power generation and pumping;

[0068] S23. Construct a power calculation model for large pumps using existing reservoirs as the upper and lower reservoirs:

[0069] ;

[0070] in, This indicates that all major water pumps are operating during the specified time period. Pumping power; Reservoir With reservoir between the large water pumps During the period Pumping power; Indicates a large water pump The pumping efficiency; Indicates a large water pump During the period The pumping flow rate; and Reservoirs With reservoir During the period The average water level in front of the dam; Indicates a large water pump During the period The average head loss during pumping;

[0071] S24. Construct a photovoltaic power generation calculation model:

[0072]

[0073]

[0074] in, For photovoltaic power plant index, , J The number of photovoltaic power plants; For all photovoltaic power plants during the time period The power generation capacity; For photovoltaic power station Rated power generation capacity; The power temperature coefficient; For photovoltaic power station During the period Light intensity; The rated light intensity under standard test conditions; For photovoltaic power station During the period The temperature of the photovoltaic panel; For photovoltaic power station During the period The air temperature; The rated temperature under standard test conditions; This refers to the temperature of the photovoltaic panel during normal operation.

[0075] S25. Construct a wind power generation calculation model:

[0076]

[0077] in, For wind power station indexing, , K The number of wind power stations; For all wind power stations during the time period The power generation capacity; For wind power station Rated power; For wind power station During the period The average wind speed at the height of the wind turbine hub; , and Wind power stations Wind turbine cut-in, cut-out, and rated wind speed;

[0078] S26. Construct a power composition model for photovoltaic and wind power generation:

[0079]

[0080]

[0081] in, and Solar and wind power respectively during the time period The power consumption of the internet connection; and Solar and wind power respectively during the time period The energy storage power section; and Solar and wind power respectively during the time period The portion of abandoned power;

[0082] S27. Based on the various power calculation models constructed in steps S21 to S26, further construct the objective function for minimizing the power supply and demand gap and the objective function for minimizing the wind and solar curtailment rate.

[0083] The expression for the objective function that minimizes the power supply-demand gap is:

[0084]

[0085] in, To minimize the sum of squares of the differences between the total output of multiple power sources and the power load demand; For time period The electricity load demand; Multiple power sources for water, wind, and solar power during different time periods Total power consumption for internet access;

[0086] When reversible units are included, hydropower, wind power, and solar power can be used in various time periods. The expression for the total power consumption for internet access is:

[0087]

[0088] When a large water pump is included, multiple power sources such as water, wind, and solar power are available during different time periods. The expression for the total power consumption for internet access is:

[0089]

[0090] The expression for the objective function that minimizes the wind and solar curtailment rate is:

[0091]

[0092] in, It has the lowest wind and solar curtailment rate.

[0093] The beneficial effects of the above technical solution are as follows: Based on reversible turbine units or large pumps, the cascade reservoir water storage method fully utilizes the curtailment of renewable energy. Water is pumped from the existing lower reservoir to the existing upper reservoir via reversible turbine units or large pumps for energy storage, thereby increasing power generation using existing cascade reservoir units and newly built reversible turbine units. This water storage method can fully utilize the regulating capacity of existing cascade reservoirs to maximize energy storage, effectively reduce wind and solar curtailment, increase renewable energy consumption, improve overall power generation efficiency, and provide important support for the complementary and synergistic development of multiple energy sources including water, wind, solar, and storage. Addressing the need for high-quality consumption of wind and solar power as different transfer methods of traditional "waste electricity," wind and solar power generation is divided into three parts: grid connection, energy storage, and curtailment.

[0094] This invention, within a long-term scheduling time step (ten-day scale), comprehensively considers the dual objectives of minimizing the power supply-demand gap and minimizing wind and solar curtailment rates, thereby achieving a synergy and balance between long-term and short-term benefits, ensuring multiple benefits including flood control, water supply, power generation, new energy, and ecological benefits. Among these, This allows for a match between power supply on the power generation side and power demand on the load side as closely as possible. This can directly reduce wind and solar curtailment, indirectly increasing the energy storage of cascade reservoirs, thereby increasing the water level of existing upper reservoirs and decreasing the water level of existing lower reservoirs. Since the lower reservoirs adjacent to the ice-prevention river sections dynamically pump water from the upper reservoirs during short-term scheduling, it is possible to reserve little or no ice-prevention storage capacity in the reservoirs before ice-prevention scheduling, allowing the lower reservoirs to maintain high water levels and thus significantly improving the power generation efficiency of the lower reservoirs.

[0095] Furthermore, the constraints of the short-term model include cascade reservoir constraints, reversible unit constraints, or large pumping unit constraints.

[0096] The constraints of the cascade reservoirs include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints.

[0097] When a reversible unit is included, the expression for the water balance equation is:

[0098] ;

[0099] When a large pumping unit is included, the expression for the water balance equation is:

[0100] ;

[0101] The expression for the initial / termination storage capacity constraint is:

[0102] ; ;

[0103] The expression for the reservoir capacity constraint is:

[0104] ;

[0105] The expression for the outflow constraint is:

[0106] ;

[0107] The expression for the power generation flow constraint is:

[0108] ;

[0109] The expression for the power output constraint of the hydropower station is:

[0110] ;

[0111] in, For reservoir During the period Inbound traffic; and Reservoirs During the period The beginning and end of the storage capacity; and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; Reservoir With reservoir between the large water pumps During the period Pumping flow rate, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period is provided by the calculation results of the long-term scheduling model; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level and the maximum reservoir capacity corresponding to the normal water level. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity;

[0112] The constraints of the reversible unit include power generation flow constraints, pumping flow constraints, constraints that the power generation and pumping conditions of the reversible unit do not occur simultaneously, power generation constraints, pumping power constraints, and constraints that the pumping energy storage of the reversible unit is provided by photovoltaic and wind power.

[0113] The power generation flow constraint expression for the reversible unit is as follows:

[0114] ;

[0115] The expression for the pumping flow constraint of the reversible unit is:

[0116] ;

[0117] The constraint expression for the reversible unit not occurring simultaneously under power generation and pumping conditions is as follows:

[0118] ;

[0119] The expression for the power generation constraint of the reversible unit is:

[0120] ;

[0121] The expression for the pumping power constraint of the reversible unit is:

[0122] ;

[0123] The constraint expression for the pumped storage energy provided by the reversible unit from photovoltaic and wind power is as follows:

[0124] ;

[0125] in, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; and These represent reversible units. During the period Maximum power generation and pumping flow rate; and These represent reversible units. During the period The power generation and pumping capacity; and These represent reversible units. During the period Maximum power generation and pumping capacity; This indicates that all reversible units are in the time period Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section;

[0126] The constraints on the large pump include pumping flow rate constraints, pumping power constraints, and constraints that the pumping energy storage of the large pump is provided by photovoltaic and wind power.

[0127] The expression for the pumping flow rate constraint of the large pump is:

[0128] ;

[0129] The expression for the pumping power constraint of the large pump is:

[0130] ;

[0131] The constraint expression for the pumping energy storage of the large pump being provided by photovoltaic and wind power is as follows:

[0132]

[0133] in, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; Indicates a large water pump During the period Maximum pumping flow rate; Indicates a large water pump During the period Pumping power; Indicates a large water pump During the period Maximum pumping power; This indicates that all major water pumps are operating during the specified time period. Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section.

[0134] The beneficial effects of the above technical solution are as follows: This invention considers the combination of cascade hydropower and water storage (reversible units or large pumps), transforming the hydraulic connection into a bidirectional regulation mode that is "both downward and upward" (generating power downward and pumping water upward). Corresponding water balance equations are established for each scenario. In the reversible unit scenario, the water balance equation incorporates both pumping and generating flow rates; in the large pump scenario, the water balance equation incorporates the pumping flow rate. Compared to the unidirectional hydraulic connection of traditional cascade scheduling, this invention increases the flexibility and controllability of water regulation, enabling the dual-objective synergy of hydropower-wind-solar hybrid power generation and flood control safety scheduling.

[0135] This invention establishes corresponding constraints for reversible generator units where power generation and pumping occur at different times and where pumping power comes from photovoltaic and wind power storage. By optimizing hydropower regulation and energy storage operation, it can effectively reduce wind and solar curtailment and increase the consumption of new energy sources.

[0136] Furthermore, the multi-objective optimization algorithm is the NSGA-II algorithm, and step S4 further includes:

[0137] S41. Initialize the parameters of the NSGA-Ⅱ algorithm, and use the initial and final reservoir capacities as boundary conditions, and hourly runoff, photovoltaic power, and wind power as inputs;

[0138] S42. Using the hourly outflow from the cascade reservoirs, the pumping flow from the reversible units, and the power generation flow as decision variables, the scale is randomly initialized as follows: initial population ;

[0139] S43. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ;

[0140] S44, Population Based on the objective function of the short-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto levels from low to high. ;

[0141] S45. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1;

[0142] S46. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S47; otherwise, return to step S43.

[0143] S47. Obtain the Pareto solution set and output the hourly water level, reservoir capacity, flow rate, and power process of the cascade reservoirs and reversible units or pumps for the corresponding ten-day period.

[0144] The beneficial effects of the above technical solution are as follows: The present invention uses the NSGA-II algorithm to provide a Pareto solution set for the two objectives of minimizing the power supply and demand gap and minimizing the wind and solar curtailment rate, rather than a single solution, which can be used by managers to make multi-scheme comparison and selection decisions.

[0145] Furthermore, for the long-term model, the water level process refers to the water level process in front of the dam of the cascade reservoirs; the reservoir capacity process refers to the reservoir capacity process of the cascade reservoirs; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoirs; and the power process includes the power generation of the cascade reservoirs.

[0146] Furthermore, for the short-term model, the water level process refers to the water level process in front of the dam of the cascade reservoirs; the reservoir capacity process refers to the reservoir capacity process of the cascade reservoirs; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoirs, the power generation flow and pumping flow of the reversible units, and the pumping flow of the large pumping pumps; the power process includes the power generation of the cascade reservoirs, the grid connection power, energy storage power, and wastewater power of wind and solar power, the power generation and pumping power of the reversible units, and the pumping power of the large pumping pumps.

[0147] Furthermore, when one or more pumped storage power stations are built on the banks of an existing river reservoir as the lower reservoir and an upper reservoir is constructed on the tailrace section of the river, the steps S1 to S6 of this scheme can also achieve the dual benefits of hydropower-wind-solar hybrid power generation and ice control scheduling.

[0148] The beneficial effects of this invention are as follows: This invention considers cascaded water energy storage (reversible units, large pumps, pumped storage power stations) and long-term-short-term multi-scale coupling, and proposes an optimization method for water-wind-solar complementary power generation and ice prevention scheduling. The given calculation scheme can ensure that during ice period scheduling, the abandoned renewable energy is fully utilized for energy storage, and more wind power and photovoltaic power are absorbed, thereby improving the efficiency of wind and solar power generation. In addition, no or little ice prevention reservoir capacity is reserved, so that the lower reservoir is kept at a high water level. Under the premise of ensuring ice prevention safety, the efficiency of hydropower generation in the lower reservoir is improved.

[0149] This invention is based on a cascade reservoir water storage method using reversible turbine units or large pumps. It fully utilizes curtailed renewable energy by pumping water from an existing lower reservoir to an existing upper reservoir using reversible turbine units or large pumps for energy storage. This allows for increased power generation using existing cascade reservoir units and newly built reversible turbine units. This novel water storage method, on the one hand, fully utilizes the regulating capacity of existing cascade reservoirs to maximize energy storage, effectively reducing wind and solar curtailment, increasing renewable energy absorption, and improving overall power generation efficiency. It provides crucial support for the complementary and synergistic development of multiple energy sources including hydropower, wind, solar, and storage. On the other hand, it can also bring new possibilities to flood control and dispatching.

[0150] Compared with existing technologies, the main technical advantages of this scheme are as follows: First, in terms of scheduling objectives, it focuses on the consumption of new energy during ice-prone periods, and comprehensively considers the multi-energy complementarity of hydropower, wind power, and solar power with the ice prevention and safety scheduling objectives, achieving synergistic optimization between the two; Second, in terms of time scale, it considers the coupling of long-term and short-term scales, with the long-term scheduling research spanning the entire non-flood season (November to June of the following year) with a time step of ten days, and the short-term scheduling research spanning ten days with a time step of hours. Long-term scheduling provides boundary conditions for short-term scheduling, and short-term scheduling provides state feedback for long-term scheduling; Third, in terms of water level control, it can reduce or eliminate the need for ice prevention reservoir capacity, effectively increasing the benefits of hydropower generation while ensuring ice prevention safety; Fourth, in terms of hydraulic connection, considering reversible units or large pumps, the hydraulic connection is a two-way connection from upstream to downstream and from downstream to upstream, making the regulation method more flexible and controllable.

[0151] This invention addresses the reshaping of the role of hydropower in the large-scale development of new energy sources and the limitations of traditional reservoir flood control scheduling. Considering the coupling of cascade hydropower station water energy storage (reversible units or large pumps) with long-term and short-term multi-scale processes, it proposes an optimized method for hydro-wind-solar complementary power generation and flood control scheduling. During flood season scheduling, this invention can fully utilize curtailed renewable energy by using reversible units or large pumps to pump water from the lower reservoir to the upper reservoir for energy storage. This allows for the absorption of more wind and solar power, reducing curtailment and improving the efficiency of wind and solar power generation. Furthermore, it minimizes or eliminates the need for pre-reserved flood control storage capacity, maintaining a high water level in the lower reservoir and improving its hydropower generation efficiency. In other words, by combining cascade hydropower with water energy storage (based on reversible units or large pumps), the hydraulic connection becomes a two-way regulation mode of "downward and upward" (generating power downwards and pumping water upwards), increasing the flexibility and controllability of water volume regulation and achieving the dual objectives of hydro-wind-solar complementary power generation and safe flood control scheduling. Attached Figure Description

[0152] Figure 1 A flowchart of an optimized method for hydro-wind-solar hybrid power generation and ice control scheduling, taking into account the energy storage of cascade reservoirs.

[0153] Figure 2 This is a schematic diagram of multi-energy complementary scheduling based on a reversible unit scenario (cascaded water storage type 1).

[0154] Figure 3 This is a schematic diagram of multi-energy complementary scheduling based on a large pumping scenario (cascade water storage form 2).

[0155] Figure 4 This is a schematic diagram of long-term and short-term multi-scale coupled optimization scheduling.

[0156] Figure 5 Historical natural inflow statistics of Liujiaxia Reservoir section from 1991 to 2022 during the flood control period (December to March of the following year).

[0157] Figure 6 This is a historical water level chart of the Liujiaxia Reservoir from 2000 to 2022.

[0158] Figure 7 A diagram showing the reservoir capacity constraints of the lower reservoir, taking into account cascade water storage (reversible units or large pumps).

[0159] Figure 8 This is a schematic diagram of a typical solar-hydro-wind-solar hybrid power generation process. Detailed Implementation

[0160] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0161] This invention addresses the reshaping of the role of hydropower in the large-scale development of new energy sources and the limitations of traditional reservoir flood control scheduling. It proposes an optimization method for hydro-wind-solar hybrid power generation and flood control scheduling that considers cascade reservoir water storage (reversible units or large pumps) and long-term / short-term coupling. Figure 1 As shown.

[0162] Taking two reservoirs with upstream and downstream hydraulic connections as an example, for this reason... , i =1 represents the upper reservoir. i =2 represents the lower reservoir, and the river section downstream of the lower reservoir has ice control requirements. Multi-energy complementary scheduling based on the reversible unit scenario (cascade hydropower storage type 1) is as follows: Figure 2 As shown, the multi-energy complementary scheduling based on the scenario of large pumping units (cascade water storage form two) is as follows: Figure 3 As shown.

[0163] refer to Figure 1 and Figure 4 , Figure 1 The flowchart shown is a flowchart of an optimization method for hydro-wind-solar hybrid power generation and ice control scheduling that considers cascade reservoir water storage. Figure 4 A schematic diagram of long-term and short-term multi-scale coupled optimization scheduling is shown, such as... Figure 1 As shown, the method includes steps S1 to S6.

[0164] In step S1, a long-term optimization scheduling model with dual objectives of minimizing the water supply gap of cascade reservoirs and maximizing power generation is constructed.

[0165] In an embodiment of the present invention, the long-term model includes an objective function and constraints, wherein the objective function includes an objective function for minimizing the water supply gap and an objective function for maximizing power generation;

[0166] The objective function for minimizing the water supply gap is expressed as minimizing the water shortage index, and its expression is:

[0167] ;

[0168] in, To minimize the water shortage index; t For time indexing, , T Total time; For the use of water outside the river channel during certain periods t The amount of water shortage; For the use of water outside the river channel during certain periods t Water demand;

[0169] The expression for the objective function that maximizes power generation is:

[0170] ;

[0171] ;

[0172] ;

[0173] ;

[0174] ;

[0175] ;

[0176] ;

[0177] in, To maximize power generation; i For reservoir indexing; The number of reservoirs; For reservoir i The power station during the period t Electricity generation; For reservoir i The power station during the period The power generation capacity; The time period is long; The density of water; It is the acceleration due to gravity; For reservoir i The power generation efficiency of the power plant; , and Reservoirsi During the period t The discharge flow, power plant generation flow, and wastewater discharge; , , and Reservoirs i The power station during the period t The average head, average water level in front of the dam, average water level behind the dam, and average head loss; For reservoir i During the period t Average storage capacity; and Reservoirs i During the period t Initial and final storage capacity; , , , and and , , , and All coefficients are obtained using polynomial fitting.

[0178] Furthermore, the constraints of the long-term model include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints.

[0179] The expression for the water balance equation is:

[0180] ;

[0181] The expression for the initial / termination storage capacity constraint is:

[0182] ; ;

[0183] The expression for the reservoir capacity constraint is:

[0184] ;

[0185] The expression for the outflow constraint is:

[0186] ;

[0187] The expression for the power generation flow constraint is:

[0188] ;

[0189] The expression for the power output constraint of the hydropower station is:

[0190] ;

[0191] in, For reservoir During the period Inbound traffic; For reservoir During the period Evaporation rate; and Reservoirs During the period The beginning and end of the storage capacity; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level as the minimum capacity and the reservoir capacity corresponding to the normal water level as the maximum capacity. It is worth noting that the innovation of this invention lies in the fact that, considering water energy storage (reversible units or large pumps) and long-term-short-term multi-scale coupling optimization, the maximum reservoir capacity during the ice prevention period is taken as the reservoir capacity corresponding to the normal water level, so no or less ice prevention reservoir capacity may be reserved. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity.

[0192] refer to Figure 5 , Figure 5 This chart shows the historical natural inflow statistics of the Liujiaxia Reservoir section from 1991 to 2022 during the ice flood control period (December to March of the following year). Historical data shows that the natural inflow from December to March of the following year is generally between 50 and 550 m³. 3 Based on scheduling practice, and through controlled release from the Liujiaxia Reservoir, the minimum monthly flow rate at the Lanzhou section (December, January, February, and March) should be controlled at 500, 400, 500, and 450 m³ / s respectively from December to March of the following year. 3 / s, the maximum flow rate should be controlled at 700, 700, 700, and 600 m³ / s respectively. 3 / s. In other words, from December to March of the following year, the overall natural inflow at the Liujiaxia section is less than the outflow. The Liujiaxia Reservoir fills to its normal storage level by the end of the flood season, and even without reserved ice-prevention capacity, the water level in front of the dam will gradually drop during the ice-prevention period. Therefore, during the ice-prevention period, the increased discharge from the Longyangxia Reservoir into the Liujiaxia Reservoir can be accommodated by the gradually freed-up storage capacity of the Liujiaxia Reservoir, and also by pumping water upstream through hydro-wind-solar hybridization and cascade hydropower storage, allowing the upstream reservoirs to absorb the water.

[0193] refer to Figure 6 , Figure 6 The diagram shows the historical water level process in front of the Liujiaxia Reservoir from 2000 to 2022. Historical data shows that in operation, the Liujiaxia Reservoir experiences two water level rises and falls each year: one to reserve flood control capacity during the summer flood season, and the other to reserve ice-breaking capacity during the ice-jam flood season.

[0194] refer to Figure 7 , Figure 7 The diagram shows the reservoir capacity constraints of the lower reservoir considering cascade hydropower storage (reversible units or large pumps). The lower reservoir corresponds to the Liujiaxia Reservoir, the lower reservoir of the Long-Liu Reservoir complex. By considering hydro-wind-solar hybrid power generation and cascade hydropower storage, the dual objectives of hydro-wind-solar hybrid power generation and safe dispatching during ice storms can be achieved with little or no reserved ice storm control capacity.

[0195] In step S2, for a multi-energy system consisting of wind power, photovoltaic power, cascade reservoirs and reversible units or large pumps, a short-term optimization scheduling model with dual objectives of minimizing the power supply and demand gap and minimizing the wind and solar curtailment rate is constructed.

[0196] In an embodiment of the present invention, the short-run model includes an objective function and constraints, and the method for constructing the objective function includes:

[0197] S21. Construct a power calculation model for cascade reservoirs:

[0198] ;

[0199] ;

[0200] ;

[0201] ;

[0202] ;

[0203] ;

[0204] in, iFor reservoir indexing; The number of reservoirs; For all cascade reservoirs during the time period The power generation capacity; For reservoir i The power station during the period The power generation capacity; The density of water; It is the acceleration due to gravity; For reservoir The power generation efficiency of the power plant; , and Reservoirs During the period The discharge flow, power plant generation flow, and wastewater discharge; , , and Reservoirs The power station during the period The average head, average water level in front of the dam, average water level behind the dam, and average head loss; For reservoir During the period Average storage capacity; and Reservoirs During the period Initial and final storage capacity; , , , and and , , , and All coefficients are obtained by polynomial fitting;

[0205] S22. Construct a power calculation model for a reversible generating unit, using the existing reservoir as the upper and lower reservoirs. This model includes a power generation calculation model and a pumping power consumption calculation model, with the following expressions:

[0206] ;

[0207] ;

[0208] in, and These represent all reversible units during the time period. Power generation and pumping capacity; and Reservoirs With reservoir Reversible units between During the period Power generation and pumping capacity; and These represent reversible units. Power generation efficiency and pumping efficiency; and These represent reversible units. During the period Power generation flow and pumping flow; and Reservoirs With reservoir During the period The average water level in front of the dam; and These represent reversible units. During the period Average head loss for power generation and pumping;

[0209] S23. Construct a power calculation model for large pumps using existing reservoirs as the upper and lower reservoirs:

[0210] ;

[0211] in, This indicates that all major water pumps are operating during the specified time period. Pumping power; Reservoir With reservoir between the large water pumps During the period Pumping power; Indicates a large water pump The pumping efficiency; Indicates a large water pump During the period The pumping flow rate; and Reservoirs With reservoir During the period The average water level in front of the dam; Indicates a large water pump During the period The average head loss during pumping;

[0212] S24. Construct a photovoltaic power generation calculation model:

[0213]

[0214]

[0215] in, For photovoltaic power plant index, , J The number of photovoltaic power plants; For all photovoltaic power plants during the time period The power generation capacity; For photovoltaic power station Rated power generation capacity; The power temperature coefficient; For photovoltaic power station During the period Light intensity; The rated light intensity under standard test conditions; For photovoltaic power station During the period The temperature of the photovoltaic panel; For photovoltaic power station During the period The air temperature; The rated temperature under standard test conditions; This refers to the temperature of the photovoltaic panel during normal operation.

[0216] S25. Construct a wind power generation calculation model:

[0217]

[0218] in, For wind power station indexing, , K The number of wind power stations; For all wind power stations during the time period The power generation capacity; For wind power station Rated power; For wind power station During the period The average wind speed at the height of the wind turbine hub; , and Wind power stations Wind turbine cut-in, cut-out, and rated wind speed;

[0219] S26. Construct a power composition model for photovoltaic and wind power generation:

[0220]

[0221]

[0222] in, and Solar and wind power respectively during the time period The power consumption of the internet connection; and Solar and wind power respectively during the time period The energy storage power section; and Solar and wind power respectively during the time period The portion of abandoned power;

[0223] S27. Based on the various power calculation models constructed in steps S21 to S26, further construct the objective function for minimizing the power supply and demand gap and the objective function for minimizing the wind and solar curtailment rate.

[0224] The expression for the objective function that minimizes the power supply-demand gap is:

[0225]

[0226] in, To minimize the sum of squares of the differences between the total output of multiple power sources and the power load demand; For time period The electricity load demand; Multiple power sources for water, wind, and solar power during different time periods Total power consumption for internet access;

[0227] When reversible units are included, hydropower, wind power, and solar power can be used in various time periods. The expression for the total power consumption for internet access is:

[0228]

[0229] When a large water pump is included, multiple power sources such as water, wind, and solar power are available during different time periods. The expression for the total power consumption for internet access is:

[0230]

[0231] The expression for the objective function that minimizes the wind and solar curtailment rate is:

[0232]

[0233] in, It has the lowest wind and solar curtailment rate.

[0234] The constraints of the short-term model include cascade reservoir constraints, reversible unit constraints, or large pump constraints.

[0235] The constraints of the cascade reservoirs include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints.

[0236] When a reversible unit is included, the expression for the water balance equation is:

[0237] ;

[0238] When a large pumping unit is included, the expression for the water balance equation is:

[0239] ;

[0240] The expression for the initial / termination storage capacity constraint is:

[0241] ; ;

[0242] The expression for the reservoir capacity constraint is:

[0243] ;

[0244] The expression for the outflow constraint is:

[0245] ;

[0246] The expression for the power generation flow constraint is:

[0247] ;

[0248] The expression for the power output constraint of the hydropower station is:

[0249] ;

[0250] in, For reservoir During the period Inbound traffic; and Reservoirs During the period The beginning and end of the storage capacity; and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; Reservoir With reservoir between the large water pumps During the period Pumping flow rate, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period is provided by the calculation results of the long-term scheduling model; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level and the maximum reservoir capacity corresponding to the normal water level. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity;

[0251] The constraints of the reversible unit include power generation flow constraints, pumping flow constraints, constraints that the power generation and pumping conditions of the reversible unit do not occur simultaneously, power generation constraints, pumping power constraints, and constraints that the pumping energy storage of the reversible unit is provided by photovoltaic and wind power.

[0252] The power generation flow constraint expression for the reversible unit is as follows:

[0253] ;

[0254] The expression for the pumping flow constraint of the reversible unit is:

[0255] ;

[0256] The constraint expression for the reversible unit not occurring simultaneously under power generation and pumping conditions is as follows:

[0257] ;

[0258] The expression for the power generation constraint of the reversible unit is:

[0259] ;

[0260] The expression for the pumping power constraint of the reversible unit is:

[0261] ;

[0262] The constraint expression for the pumped storage energy provided by the reversible unit from photovoltaic and wind power is as follows:

[0263] ;

[0264] in, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; and These represent reversible units. During the period Maximum power generation and pumping flow rate; and These represent reversible units. During the period The power generation and pumping capacity; and These represent reversible units. During the period Maximum power generation and pumping capacity; This indicates that all reversible units are in the time period Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section;

[0265] The constraints on the large pump include pumping flow rate constraints, pumping power constraints, and constraints that the pumping energy storage of the large pump is provided by photovoltaic and wind power.

[0266] The expression for the pumping flow rate constraint of the large pump is:

[0267] ;

[0268] The expression for the pumping power constraint of the large pump is:

[0269] ;

[0270] The constraint expression for the pumping energy storage of the large pump being provided by photovoltaic and wind power is as follows:

[0271]

[0272] in, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; Indicates a large water pump During the period Maximum pumping flow rate; Indicates a large water pump During the period Pumping power; Indicates a large water pump During the period Maximum pumping power; This indicates that all major water pumps are operating during the specified time period. Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section.

[0273] S3. Using the ten-day scale runoff during the non-flood season as input (e.g., from early November to late June of the following year, a total of 24 ten-day periods), a multi-objective optimization algorithm is used to perform long-term model optimization calculations to obtain the ten-day scale water level process, reservoir capacity process, flow process, and power process of the cascade reservoirs.

[0274] In an embodiment of the present invention, the multi-objective optimization algorithm is the NSGA-II algorithm, and step S3 further includes:

[0275] S31. Initialize the parameters of the NSGA-II algorithm, using non-flood season decadal runoff as input;

[0276] S32. Using the decadal-scale discharge flow of the cascade reservoirs as the decision variable, the scale is randomly initialized as follows: initial population ;

[0277] S33. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ;

[0278] S34, Population Based on the two objective functions of the long-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto ranks from low to high. ;

[0279] S35. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1;

[0280] S36. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S37; otherwise, return to step S33.

[0281] S37. Obtain the Pareto solution set and output the corresponding process set of water level, storage capacity, flow rate and power of the cascade reservoirs at the ten-day scale.

[0282] In step S37, for the long-term model, the water level process is the water level process in front of the dam of the cascade reservoir; the reservoir capacity process is the reservoir capacity process of the cascade reservoir; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoir; and the power process includes the power generation of the cascade reservoir.

[0283] In step S4, the initial and final reservoir capacities of the cascade reservoirs in step S3 at the first ten-day scale are used as the boundary conditions of the short-term model (the first calculation is the initial and final reservoir capacities in early November). Hourly runoff, photovoltaic power, and wind power are used as inputs. A multi-objective optimization algorithm is employed to perform short-term model optimization calculations, obtaining the hourly water level process, reservoir capacity process, flow process, and power process of the cascade reservoirs and reversible units or large pumps for that ten-day period.

[0284] In an embodiment of the present invention, the multi-objective optimization algorithm is the NSGA-II algorithm, and step S4 further includes:

[0285] S41. Initialize the parameters of the NSGA-Ⅱ algorithm, and use the initial and final reservoir capacities as boundary conditions, and hourly runoff, photovoltaic power, and wind power as inputs;

[0286] S42. Using the hourly outflow from the cascade reservoirs, the pumping flow from the reversible units, and the power generation flow as decision variables, the scale is randomly initialized as follows: initial population ;

[0287] S43. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ;

[0288] S44, Population Based on the objective function of the short-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto levels from low to high. ;

[0289] S45. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1;

[0290] S46. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S47; otherwise, return to step S43.

[0291] S47. Obtain the Pareto solution set and output the hourly water level, reservoir capacity, flow rate, and power process of the cascade reservoirs and reversible units or pumps for the corresponding ten-day period.

[0292] In step S47, for the short-term model, the water level process is the upstream water level process of the cascade reservoirs; the reservoir capacity process is the reservoir capacity process of the cascade reservoirs; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoirs, the power generation flow and pumping flow of the reversible units, and the pumping flow of the large pumping pumps; the power process includes the power generation of the cascade reservoirs, the grid connection power, energy storage power, and wastewater power of wind and solar power, the power generation and pumping power of the reversible units, and the pumping power of the large pumping pumps.

[0293] refer to Figure 8 , Figure 8 A schematic diagram of a typical hydro-wind-solar hybrid power generation process is shown. The results indicate that during peak solar power generation in the daytime, the output of the cascade reservoirs decreases; when solar power generation exceeds channel limits, reversible turbines or large pumps can be used for pumped water storage; at night, when solar power is not generating, the output of the cascade reservoirs or reversible turbines increases for compensation and regulation. In other words, through multi-energy complementarity of hydro-wind-solar and cascade reservoir water storage, new energy sources can be fully utilized, reducing the curtailment of renewable energy. Due to the pumped water storage provided by reversible turbines and large pumps, water from the lower reservoir is pumped back to the upper reservoir for water energy recycling, thus achieving minimal or no ice-prevention storage capacity during ice storm periods.

[0294] In step S5, the final reservoir capacity calculated by the short-term model (final reservoir capacity in early November) is fed back to the long-term model. Combined with the runoff input during the remaining scheduling period (mid-November to late June of the following year, a total of 23 ten-day periods), a multi-objective optimization algorithm is used to optimize the long-term model. The initial and final reservoir capacities calculated by the long-term model at the first ten-day scale of the remaining scheduling period (the second calculation is the initial and final reservoir capacities at mid-November) are used as the boundary conditions of the short-term model. Hourly runoff, photovoltaic power, and wind power are used as inputs, and a multi-objective optimization algorithm is used to optimize the short-term model.

[0295] In step S6, the operation S5 is repeated to complete the short-term model optimization calculation for each ten-day period during the non-flood season in sequence, so as to obtain the long-term-short-term coupled hydro-wind-solar complementary power generation and ice prevention scheduling optimization scheme.

[0296] In summary, this invention utilizes cascade reservoirs to achieve water energy storage (reversible units and large pumps), transforming the hydraulic connection into a bidirectional regulation mode that can be both "downward and upward" (generating power downward and pumping water upward). This increases the flexibility and controllability of water volume regulation, enabling the synergistic achievement of dual objectives: hydropower, wind power, and solar power generation, and ice storm prevention and safety scheduling. It also increases the absorption of new energy sources, enhances the power generation efficiency of multi-energy systems, and ensures ice storm prevention safety.

[0297] It should be noted that this invention focuses on reversible generating units or large pumping units using existing reservoirs as upper and lower reservoirs, i.e., cascade reservoir water storage, and proposes a method for hydro-wind-solar hybrid power generation and optimized ice control scheduling. Furthermore, as an extension of this invention, for one or more pumped storage power stations using an existing river reservoir as the lower reservoir and constructing an upper reservoir on the riverbank of its tailrace, if the total capacity and regulation capacity of the upper reservoir are sufficiently large compared to the lower reservoir, the technical solution proposed in this invention can also achieve the dual benefits of hydro-wind-solar hybrid power generation and ice control scheduling.

Claims

1. A method for optimizing hydro-wind-solar hybrid power generation and ice control dispatch considering hydro-storage, characterized in that, Including the following steps: S1. Construct a long-term optimization scheduling model with dual objectives of minimizing the water supply gap of cascade reservoirs and maximizing power generation. S2. For multi-energy systems consisting of wind power, photovoltaic power, cascade reservoirs and reversible units or large pumps, construct a short-term optimization scheduling model with dual objectives of minimizing the power supply and demand gap and minimizing the wind and solar curtailment rate. S3. Using the ten-day scale runoff during the non-flood season as input, a multi-objective optimization algorithm is used to perform long-term model optimization calculations to obtain the ten-day scale water level process, reservoir capacity process, flow process and power process of the cascade reservoirs. S4. Using the initial and final reservoir capacities of the first ten-day period of the cascade reservoirs in step S3 as the boundary conditions of the short-term model, and using hourly runoff, photovoltaic power, and wind power as inputs, a multi-objective optimization algorithm is used to perform short-term model optimization calculations to obtain the hourly water level process, reservoir capacity process, flow process, and power process of the cascade reservoirs and reversible units or pumping units in that ten-day period. S5. Feed the final reservoir capacity calculated by the short-term model back to the long-term model. Combine the runoff input during the remaining scheduling period and use a multi-objective optimization algorithm to optimize the long-term model. Use the initial and final reservoir capacities calculated by the long-term model at the first ten-day scale of the remaining scheduling period as the boundary conditions of the short-term model. Use hourly runoff, photovoltaic power, and wind power as inputs and use a multi-objective optimization algorithm to optimize the short-term model. S6. Repeat operation S5 to complete the short-term model optimization calculation for each ten-day period during the non-flood season in sequence, so as to obtain the long-term-short-term coupled hydro-wind-solar complementary power generation and ice prevention scheduling optimization scheme.

2. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 1, characterized in that, The long-term model includes objective functions and constraints, and the objective functions include an objective function for minimizing the water supply gap and an objective function for maximizing power generation. The objective function for minimizing the water supply gap is expressed as minimizing the water shortage index, and its expression is: ； in, To minimize the water shortage index; t is the time index. T is the total time; The amount of water shortage for the three types of water use outside the river channel during time period t; The water demand for the three types of water use outside the river channel during time period t; The expression for the objective function that maximizes power generation is: ； ； ； ； ； ； ； in, To maximize power generation; i is the reservoir index; The number of reservoirs; Let be the power generation of the power station at reservoir i during time period t; For the power station of reservoir i during the time period The power generation capacity; The time period is long; The density of water; It is the acceleration due to gravity; Let be the power generation efficiency of the power station in reservoir i; , and These represent the outflow from reservoir i, the power generation flow from the power station, and the wastewater discharge during time period t, respectively. , , and These represent the average head, average water level in front of the dam, average water level behind the dam, and average head loss of the power station at reservoir i during time period t. Let i be the average reservoir capacity of reservoir i during time period t; and These represent the reservoir capacity of reservoir i at the beginning and end of time period t, respectively. , , , and and , , , and All coefficients are obtained using polynomial fitting.

3. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 2, characterized in that, The constraints of the long-term model include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints. The expression for the water balance equation is: ； The expression for the initial / termination storage capacity constraint is: ； ； The expression for the reservoir capacity constraint is: ； The expression for the outflow constraint is: ； The expression for the power generation flow constraint is: ； The expression for the power output constraint of the hydropower station is: ； in, For reservoir During the period Inbound traffic; For reservoir During the period Evaporation rate; and Reservoirs During the period The beginning and end of the storage capacity; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level and the maximum reservoir capacity corresponding to the normal water level. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity.

4. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 2 or 3, characterized in that, The multi-objective optimization algorithm is the NSGA-II algorithm, and step S3 further includes: S31. Initialize the parameters of the NSGA-II algorithm, using non-flood season decadal runoff as input; S32. Using the decadal-scale discharge flow of the cascade reservoirs as the decision variable, the scale is randomly initialized as follows: initial population ; S33. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ; S34, Population Based on the two objective functions of the long-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto ranks from low to high. ; S35. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1; S36. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S37; otherwise, return to step S33. S37. Obtain the Pareto solution set and output the corresponding process set of water level, storage capacity, flow rate and power of the cascade reservoirs at the ten-day scale.

5. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 1, characterized in that, The short-term model includes an objective function and constraints, and the method for constructing the objective function includes: S21. Construct a power calculation model for cascade reservoirs: ； ； ； ； ； ； Where i is the reservoir index; The number of reservoirs; For all cascade reservoirs during the time period The power generation capacity; For the power station of reservoir i during the time period The power generation capacity; The density of water; It is the acceleration due to gravity; For reservoir The power generation efficiency of the power plant; , and Reservoirs During the period The discharge flow, power plant generation flow, and wastewater discharge; , , and Reservoirs The power station during the period The average head, average water level in front of the dam, average water level behind the dam, and average head loss; For reservoir During the period Average storage capacity; and Reservoirs During the period Initial and final storage capacity; , , , and and , , , and All coefficients are obtained by polynomial fitting; S22. Construct a power calculation model for a reversible generating unit, using the existing reservoir as the upper and lower reservoirs. This model includes a power generation calculation model and a pumping power consumption calculation model, with the following expressions: ； ； in, and These represent all reversible units during the time period. Power generation and pumping capacity; and Reservoirs With reservoir Reversible units between During the period Power generation and pumping capacity; and These represent reversible units. Power generation efficiency and pumping efficiency; and These represent reversible units. During the period Power generation flow and pumping flow; and Reservoirs With reservoir During the period The average water level in front of the dam; and These represent reversible units. During the period Average head loss for power generation and pumping; S23. Construct a power calculation model for large pumps using existing reservoirs as the upper and lower reservoirs: ； in, This indicates that all major water pumps are operating during the specified time period. Pumping power; Reservoir With reservoir between the large water pumps During the period Pumping power; Indicates a large water pump The pumping efficiency; Indicates a large water pump During the period The pumping flow rate; and Reservoirs With reservoir During the period The average water level in front of the dam; Indicates a large water pump During the period The average head loss during pumping; S24. Construct a photovoltaic power generation calculation model: in, For photovoltaic power plant index, J represents the number of photovoltaic power plants; For all photovoltaic power plants during the time period The power generation capacity; For photovoltaic power station Rated power generation capacity; The power temperature coefficient; For photovoltaic power station During the period Light intensity; The rated light intensity under standard test conditions; For photovoltaic power station During the period The temperature of the photovoltaic panel; For photovoltaic power station During the period The air temperature; The rated temperature under standard test conditions; This refers to the temperature of the photovoltaic panel during normal operation. S25. Construct a wind power generation calculation model: in, For wind power station indexing, K represents the number of wind power stations; For all wind power stations during the time period The power generation capacity; For wind power station Rated power; For wind power station During the period The average wind speed at the height of the wind turbine hub; , and Wind power stations Wind turbine cut-in, cut-out, and rated wind speed; S26. Construct a power composition model for photovoltaic and wind power generation: in, and Solar and wind power respectively during the time period The power consumption of the internet connection; and Solar and wind power respectively during the time period The energy storage power section; and Solar and wind power respectively during the time period The portion of abandoned power; S27. Based on the various power calculation models constructed in steps S21 to S26, further construct the objective function for minimizing the power supply and demand gap and the objective function for minimizing the wind and solar curtailment rate. The expression for the objective function that minimizes the power supply-demand gap is: in, To minimize the sum of squares of the differences between the total output of multiple power sources and the power load demand; For time period The electricity load demand; Multiple power sources for water, wind, and solar power during different time periods Total power consumption for internet access; When reversible units are included, hydropower, wind power, and solar power can be used in various time periods. The expression for the total power consumption for internet access is: When a large water pump is included, multiple power sources such as water, wind, and solar power are available during different time periods. The expression for the total power consumption for internet access is: The expression for the objective function that minimizes the wind and solar curtailment rate is: in, It has the lowest wind and solar curtailment rate.

6. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 5, characterized in that, The constraints of the short-term model include cascade reservoir constraints, reversible unit constraints, or large pump constraints. The constraints of the cascade reservoirs include water balance equations, initial / terminal reservoir capacity constraints, reservoir capacity constraints, outflow constraints, power generation flow constraints, and hydropower station output constraints. When a reversible unit is included, the expression for the water balance equation is: ； When a large pumping unit is included, the expression for the water balance equation is: ； The expression for the initial / termination storage capacity constraint is: ； ； The expression for the reservoir capacity constraint is: ； The expression for the outflow constraint is: ； The expression for the power generation flow constraint is: ； The expression for the power output constraint of the hydropower station is: ； in, For reservoir During the period Inbound traffic; and Reservoirs During the period The beginning and end of the storage capacity; and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; Reservoir With reservoir between the large water pumps During the period Pumping flow rate, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; For reservoir Storage capacity at the beginning of the scheduling period; For reservoir The target storage capacity at the end of the scheduling period is provided by the calculation results of the long-term scheduling model; and Reservoirs During the period The minimum and maximum reservoir capacities are determined by taking the reservoir capacity corresponding to the dead water level and the maximum reservoir capacity corresponding to the normal water level. and Reservoirs During the period The minimum and maximum discharge flows are determined by the following: the minimum discharge flow is the larger of the ecological flow and the lower limit of the control range of the discharge flow during the ice prevention period; the maximum discharge flow is the upper limit of the control range of the discharge flow during the ice prevention period. and Reservoirs The power station during the period The minimum and maximum power generation flow rates; and Reservoirs The power station during the period The minimum and maximum power generation capacity; The constraints of the reversible unit include power generation flow constraints, pumping flow constraints, constraints that the power generation and pumping conditions of the reversible unit do not occur simultaneously, power generation constraints, pumping power constraints, and constraints that the pumping energy storage of the reversible unit is provided by photovoltaic and wind power. The power generation flow constraint expression for the reversible unit is as follows: ； The expression for the pumping flow constraint of the reversible unit is: ； The constraint expression for the reversible unit not occurring simultaneously under power generation and pumping conditions is as follows: ； The expression for the power generation constraint of the reversible unit is: ； The expression for the pumping power constraint of the reversible unit is: ； The constraint expression for the pumped storage energy provided by the reversible unit from photovoltaic and wind power is as follows: ； in, and Reservoirs With reservoir Reversible units between During the period Power generation flow and pumping flow; and These represent reversible units. During the period Maximum power generation and pumping flow rate; and These represent reversible units. During the period The power generation and pumping capacity; and These represent reversible units. During the period Maximum power generation and pumping capacity; This indicates that all reversible units are in the time period Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section; The constraints on the large pump include pumping flow rate constraints, pumping power constraints, and constraints that the pumping energy storage of the large pump is provided by photovoltaic and wind power. The expression for the pumping flow rate constraint of the large pump is: ； The expression for the pumping power constraint of the large pump is: ； The constraint expression for the pumping energy storage of the large pump being provided by photovoltaic and wind power is as follows: in, Reservoir With reservoir between the large water pumps During the period The pumping flow rate; Indicates a large water pump During the period Maximum pumping flow rate; Indicates a large water pump During the period Pumping power; Indicates a large water pump During the period Maximum pumping power; This indicates that all major water pumps are operating during the specified time period. Pumping power; and These represent the total photovoltaic and wind power generation during the time period, respectively. The energy storage power section.

7. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 5 or 6, characterized in that, The multi-objective optimization algorithm is the NSGA-II algorithm, and step S4 further includes: S41. Initialize the parameters of the NSGA-Ⅱ algorithm, and use the initial and final reservoir capacities as boundary conditions, and hourly runoff, photovoltaic power, and wind power as inputs; S42. Using the hourly outflow from the cascade reservoirs, the pumping flow from the reversible units, and the power generation flow as decision variables, the scale is randomly initialized as follows: initial population ; S43. A population size of [size missing] is generated using crossover and mutation operations. offspring population and the parent population With offspring population Merge into a population ; S44, Population Based on the objective function of the short-term model, a fast non-dominated ranking is performed to obtain several non-dominated layers with Pareto levels from low to high. ; S45. Calculate the crowding degree of individuals in the non-dominated layer, and select the population based on the non-dominated ranking and crowding degree. In Each individual generates a new parent population. Then set the evolutionary generation. Add 1; S46. Determine whether the current iteration count exceeds the set number of generations. If yes, terminate the iteration and proceed to step S47; otherwise, return to step S43. S47. Obtain the Pareto solution set and output the hourly water level, reservoir capacity, flow rate, and power process of the cascade reservoirs and reversible units or pumps for the corresponding ten-day period.

8. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 4, characterized in that, For the long-term model, the water level process refers to the water level process in front of the dam of the cascade reservoirs; the reservoir capacity process refers to the reservoir capacity process of the cascade reservoirs; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoirs; and the power process includes the power generation of the cascade reservoirs.

9. The method for optimizing hydro-wind-solar hybrid power generation and ice control scheduling according to claim 7, characterized in that, For the short-term model, the water level process refers to the water level process in front of the dam of the cascade reservoirs; the reservoir capacity process refers to the reservoir capacity process of the cascade reservoirs; the flow process includes the outflow, power generation flow, and wastewater discharge of the cascade reservoirs, the power generation flow and pumping flow of the reversible units, and the pumping flow of the large pumping pumps; the power process includes the power generation of the cascade reservoirs, the grid connection power, energy storage power, and wastewater power of wind and solar power, the power generation and pumping power of the reversible units, and the pumping power of the large pumping pumps.

Images