73 results about "Gross generation" patented technology

A prediction method of solar-generated power includes: storing past data obtained by associating weather data and power generation data of a solar cell output via a PCS for at least one year before a prediction target day; calculating a sunny power generation curve from the past data; obtaining an annual transition curved line indicating an annual transition of a total power generation amount; obtaining a sunny power generation model from the sunny power generation curve so as to match the annual transition curved line; obtaining a the sunny power generation model for the entire year; obtaining a weather coefficient; and acquiring a weather forecast and obtaining prediction generated power from the sunny power generation model and the weather coefficient.

The invention discloses a scheduling rule optimization method for a water-wind-light integrated system, and relates to the technical field of energy system scheduling. Comprising the following steps: designing a water-wind-light multi-energy complementary long-term scheduling graph, initializing upper and lower scheduling lines of the scheduling graph and deciding output parameters to calculate the monthly total generating capacity; designing a middle-term scheduling rule, and distributing the monthly total generating capacity to each day to obtain daily generating capacity; designing a short-term scheduling rule, and distributing the daily total power generation amount to each hour to obtain a day-ahead power generation plan; determining the load state of each hydropower station in the cascade hydropower stations, and constraining the hydraulic connection and power connection between different hydropower stations to obtain a real-time scheduling strategy; and performing updating iteration optimization on optimization variables of the multi-objective optimization scheduling model to obtain a Pareto solution set, and determining a water-wind-light integrated scheduling rule according to a compromise solution. According to the invention, the risks of power abandoning and load loss in the operation process can be reduced to the greatest extent.

The invention provides a multi-energy system regulation and control optimization method and device considering demand side flexible resources. The multi-energy system comprises a first energy supply side and a second energy supply side, and the multi-energy system regulation and control optimization method comprises the steps that according to the power generation condition of the second energy supply side under a historical weather sample, the second power generation amount is predicted; wherein the sum of the first generating capacity and the second generating capacity is the total generating capacity; a power supply distribution model of a target area is established, the target area is gridded through a topological network, each grid of the target area is marked according to identity information registered by a power utilization object, and regulation and control are performed according to comparison between power consumption of areas with different priorities and power supply quantity of a multi-energy system. The technical problem solved by the embodiment of the invention is that an effective regulation and control mode is lacked between different energy power stations, so that the total electric energy supply quantity of an energy supply side is far greater than the demand quantity of an energy consumption side, and thus energy excess and energy waste are caused.

The invention discloses a new energy bearing capacity-considered adjustable resource ratio and energy storage distribution point optimization method, which comprises the following steps of: establishing a wind power generation model, a photovoltaic power generation model and a storage battery model, and calculating the optimal energy storage system capacity, namely the storage battery capacity; taking the distribution proportion of wind power and photoelectricity in the optimal energy storage system capacity state as a constraint condition, taking the maximum value of the annual total generating capacity of wind power and photovoltaic energy in each region in the power grid as a target function, establishing a wind and light storage capacity optimal proportion model, and solving to obtain the optimal proportion of each distributed resource capacity; and determining the optimal layout position of the energy storage system in the power grid, establishing an energy storage stationing optimization model by taking the maximum energy storage utilization rate and the minimum energy storage construction and maintenance cost as objective functions, and solving to obtain the optimal energy storage stationing position. According to the method, the bearing capacity of the power grid to renewable resources is improved, the adaptability and flexibility are high, and system configuration can be dynamically adjusted according to resource conditions and load requirements of different regions.

The invention relates to a power grid hour-level green electricity source tracing method and system based on space-time matching. The method comprises the following steps: firstly, collecting power generation data of a power generation end containing a power generation equipment identifier, power generation quantity and a power generation timestamp and power utilization data of a power utilization end containing a user identifier, power utilization quantity and a power utilization timestamp, and preprocessing and integrating into a power generation record and a power utilization record; for each to-be-traced power utilization record, dynamically delimiting a time window according to the power utilization timestamp; all power generation records in the window are inquired and aggregated to calculate the total power generation amount; then, according to the proportion of the generating capacity of each power generation device in the total generating capacity, green electric quantity distributed to the electricity utilization record is calculated, and a distribution relation is recorded to generate a traceability result containing a user identifier, a power generation device identifier, the distributed electric quantity, a time window and matching confidence; and finally, generating an ESG report and an electronic certificate based on the traceability result. Compared with the prior art, the method has the advantages of high traceability precision, high automation degree, high reliability and the like.

The invention relates to a micro-grid optimization operation method considering different operation modes, and belongs to the technical field of micro-grids. According to the method, based on a micro-grid operation mode and interaction electric quantity of a micro-grid and a large power grid, a first objective function is constructed by taking interaction cost minimization of the micro-grid and the large power grid as an objective; based on the rated power of each unit in the micro-grid and the gas consumption of the gas turbine, constructing a second target function by taking the operation cost minimization as a target; based on the gas turbine power generation power, the total power generation amount of the wind turbine generator, the total power generation amount of the photovoltaic unit, and the charging power and the discharging power of the energy storage unit, constructing a third objective function by taking micro-grid income maximization as an objective; and carrying out joint solution on the plurality of objective functions based on set constraints to obtain a micro-grid optimization operation scheme. According to the method, the utilization rate of new energy output in the micro-grid can be effectively improved, the adjustment capability of flexible resources such as energy storage in the micro-grid is fully exerted, and the operation cost of the micro-grid is reduced.

The invention discloses a power generation prediction method, device and system of a distributed photovoltaic power generation system. The method comprises the steps that real-time data corresponding to a photovoltaic panel in the distributed photovoltaic power generation system are collected, the real-time data comprise real-time values of multiple environmental parameters, and the multiple environmental parameters comprise illumination intensity, air temperature and wind speed; performing similarity comparison on the real-time data and the load prediction reference table, and determining initial prediction generating capacity; performing deviation comparison calculation on the total generating capacity and the initial predicted generating capacity of the distributed photovoltaic power generation system to obtain a deviation result; performing aging analysis on the deviation result to obtain an aging analysis result; and adjusting the initial predicted generating capacity according to an aging analysis result to obtain a target predicted generating capacity. According to the method and the device, the technical problems of low speed of putting the photovoltaic power generation system into use and low accuracy of an electric power prediction method due to the fact that the electric power prediction method depends on historical electric power output data in related technologies are solved.

The invention relates to the technical field of wind power generation, particularly provides a multi-target yaw wake flow optimization method for a wind power plant, electronic equipment and a storage medium, and aims to solve the technical problem that the service life of a wind turbine generator is remarkably shortened possibly due to the fact that an existing yaw control strategy considers the whole power generation capacity but does not consider fatigue damage of the generator. In order to achieve the purpose, the wind power plant multi-target yaw wake flow optimization method comprises the steps that unit information, inflow condition information and a fatigue damage agent model of a target wind power plant are acquired; establishing an initial population based on the unit information; starting from the initial population, performing target iteration by using a genetic algorithm to maximize a first optimization target and minimize a second optimization target; when the first optimization target and the second optimization target converge, obtaining a Pareto frontier of multi-target optimization; and obtaining the optimal yaw angle combination of the target wind power plant based on the Pareto front. The fatigue damage of the unit is effectively inhibited while the total generating capacity is improved by bringing the fatigue damage of the unit into a control optimization target.

The invention provides a float-discrete differential dynamic programming successive approximation method for cascade reservoir group scheduling, comprising the following steps: water levels of cascade reservoir group are raised from small to large according to water surface areas of reservoirs; the cascade reservoir group generates electricity after raising the water level according to incoming water; at the end of calculation period, and initial water level trajectory is obtained when the raised water level of the cascade reservoir group falls back to the set water level; based on the initial water level trajectory obtained, discrete differential dynamic programming calculation of each reservoir is carried out from upstream to downstream with the goal of maximizing the cascade total power generation, and the improved water level trajectory of each cascade reservoir is obtained; taking the improved water level trajectory of each cascade reservoir as the initial trajectory, and the iterative optimization is carried out.

The invention discloses an intelligent electric energy distribution device for an industrial park. The intelligent electric energy distribution device comprises a data acquisition unit, a cloud power plant unit and an intelligent regulation and control unit. The data acquisition unit records the total generating capacity of modes of connecting industrial park power transmission line power supply end green energy and coal-fired power generation and the like and the real-time power consumption of the industrial park, and the data acquisition unit and the real-time power consumption upload measured data to the cloud power plant unit; the cloud power plant unit constructs an LSTM prediction model, learns the data, and predicts a difference value between the total power generation amount and the power consumption amount. A TTAO optimization algorithm is constructed, and the optimal electricity price and the optimal distribution of electric power resources are found; and the intelligent regulation and control unit adjusts the electricity price and the electric power resource according to the optimal electricity price found by the cloud power plant unit and the optimal electric power resource distribution. Compared with the prior art, electricity price adjustment and power resource allocation are carried out according to the total power generation amount of the power supply end of the power transmission line connected with the industrial park, and the problems that a virtual power plant mechanism is not flexible in regulation and control and resources cannot be allocated can be solved.

The application relates to the technical field of wind power generation, and particularly provides a wind farm multi-target yaw wake optimization method, an electronic device and a storage medium, and aims to solve the technical problem that the service life of a wind turbine is significantly shortened due to the fact that the existing yaw control strategy considers the total power generation but does not consider the fatigue damage of the unit. To this end, the wind farm multi-target yaw wake optimization method comprises the following steps: obtaining unit information, inflow condition information and a fatigue damage proxy model of a target wind farm; establishing an initial population based on the unit information; starting from the initial population, a genetic algorithm is used to perform target iteration to maximize a first optimization target and minimize a second optimization target; when the first optimization target and the second optimization target are converged, a Pareto frontier of multi-target optimization is obtained; and the optimal yaw angle combination of the target wind farm is obtained based on the Pareto frontier. By taking the unit fatigue damage into the control optimization target, the total power generation is improved while the unit fatigue damage is effectively inhibited.

The invention provides a long-term power generation capacity collaborative optimization method and device in a multi-basin hydropower station group, electronic equipment and a computer readable storage medium. According to the collaborative optimization method for the medium-and-long-term power generation capacity of the multi-basin hydropower station group, global collaborative optimization of the multi-basin hydropower station group under the multi-dimensional constraint conditions of time, space, safety and the like can be achieved, the medium-and-long-term total power generation capacity of the regional hydropower station group is improved, and power market transaction decisions are effectively supported.

The application discloses a kind of water wind light integration system scheduling rule optimization method, it is related to energy system scheduling technical field.Disclosed in the application includes: design water wind light multi-energy complementary long-term scheduling chart, initialize the up and down scheduling line on scheduling chart and decision output parameter, to calculate monthly total power generation;Design medium-term scheduling rule, monthly total power generation is distributed to each day, to obtain daily power generation;Design short-term scheduling rule, daily total power generation is distributed to each hour, to obtain day-ahead generation plan;Determine the load state of each hydropower station in cascade hydropower station, and the hydraulic connection and electric connection between different hydropower stations are constrained, to obtain real-time scheduling strategy;The optimization variable of multi-objective optimization scheduling model is updated and iterated to obtain pareto solution set, and water wind light integration scheduling rule is determined according to compromise solution.The application can minimize the risk of power rejection and load loss during operation.

The invention relates to the field of wind power generation control, in particular to a wind power generation equipment comprehensive monitoring method and system based on multiple sensors and a power distribution cabinet. Comprising the following steps: collecting wind power parameters of power generation equipment in a target area through a monitoring unit, generating a wind power diagram, and verifying by combining a position vector between the power generation equipment and a target wind power vector in the wind power diagram; generating N groups of input data based on the wind power parameters, the equipment parameters and the N operation modes, and respectively calculating wake flow distribution, generating capacity and equipment loss value corresponding to each group of data through a wake flow prediction model and a power generation prediction model; and superposing the wake flow information into the wind power data of other equipment, finally calculating the total power generation amount and the total loss amount of all wake flow branches, and selecting the optimal operation mode of each power generation equipment through multi-objective optimization. Cooperative control of power generation equipment is realized, and power generation efficiency and equipment loss are effectively balanced.

The invention relates to the technical field of wind power generation, and discloses an offshore large-scale wind power plant micro-siting method, device, equipment and product, which considers the influence of different wind directions to accurately calculate a wind speed value and can more truly reflect the wind energy resource condition during the actual operation of a wind driven generator. Furthermore, by taking the total generating capacity as a guide, through a particle swarm optimization algorithm, the wake effect is optimized for different wind conditions, the influence of the wake effect on the generating capacity of the wind power plant can be reduced on the premise of ensuring the solving efficiency, and meanwhile, through collaborative optimization, the splitting property of optimization only in a single stage in a traditional method is avoided, and the optimization efficiency is improved. And the overall power generation efficiency of the wind power plant is effectively improved. And finally, according to the optimized optimal layout position of the wind driven generator, a target layout scheme of the to-be-built offshore large-scale wind power plant is determined, actual construction can be guided, reasonable layout of the wind power plant in the planning stage is guaranteed, wake flow loss is reduced, and the power generation level of the wind power plant is improved.

The application provides a hydropower station power generation capacity adjusting method, relates to the field of hydropower dispatching, and particularly relates to a hydropower station power generation capacity adjusting method, which comprises the following steps: selecting an adjusting mode and determining a power generation proportion under the adjusting mode; setting a tentative operation time and a tentative operation day of a hydropower station unit group to determine a monthly power generation plan; estimating a total power generation capacity according to an already generated power generation capacity and the monthly power generation plan of the hydropower station unit group; calculating a proportional total monthly power generation capacity according to the power generation proportion corresponding to the adjusting mode; estimating an expected evaluation power generation capacity and an expected reward power generation capacity in combination with an evaluation standard and a reward coefficient; and adjusting a proportion coefficient to make the expected evaluation power generation capacity meet a constraint condition of the evaluation standard. The hydropower station power generation capacity adjusting method has the beneficial effects that: the power generation plan can be simulated in combination with water quantity and peak regulation requirements, the expected evaluation power generation capacity and the expected reward power generation capacity are estimated, the basis for adjusting the power generation plan is obtained, the power generation plan meets the evaluation standard and the reward power generation capacity is obtained, the cost is reduced, and economic benefits are obtained.

The unit economic operation method and system based on the control of the drought limit water level of a reservoir provided by this application. The method includes the following steps: calculating and obtaining the phased drought limit water levels of the reservoir by using the hourly sliding calculation method respectively; based on the phased drought limit water levels of the reservoir, constructing a unit economic operation model with maximizing the total power generation of the reservoir within the planned period as the objective function and satisfying the physical constraint conditions of the reservoir - hydropower station - unit; based on the constructed unit economic operation model, using the locust optimization algorithm to seek the optimal economic operation strategy of each working unit under the optimal criterion of power generation. This application builds a framework based on "drought limit water level control - unit economic operation - intelligent optimization", constructs and efficiently solves a general model for unit economic operation based on the control of the drought limit water level of the reservoir, and proposes a unit economic operation method based on the control of the drought limit water level of the reservoir, which can provide a theoretical basis and technical support for the scientific formulation of the unit economic operation plan under the phased control of the drought limit water level of the basin reservoir.

The present invention relates to the technical field of energy storage control. The present invention discloses an energy storage control system for new energy power generation consumption; it includes calculating the consumption control period of the energy storage system, obtaining the comprehensive energy consumption data of the power grid system during the control period, predicting the power consumption value in the next control period, and calculating the consumption demand value. According to the total power generation and the consumption demand value, the corresponding consumption control mode is selected to control the new energy power generation system and the energy storage system to supply power to the power grid system; compared with the prior art, the present invention can provide a basis for analyzing and determining whether there will be a shortage of power supply in the future of the power grid system, and reasonably formulate the corresponding consumption control mode and corresponding consumption power supply measures according to the total power generation of the new energy power generation system, ensuring that the new energy power generation system and the energy storage system can perform power scheduling operations in advance to the power grid system, preventing the phenomenon of insufficient power supply in the future of the power grid system.

The invention discloses a fan power optimal configuration method and system based on a transmission tower group. The method comprises the following steps: determining a first node and a second node in a plurality of transmission tower nodes corresponding to the transmission tower group; determining transportation consumed electric energy of the unmanned aerial vehicle based on the electric energy consumption coefficient corresponding to the unmanned aerial vehicle and the distance between the first node and the second node; determining an electric energy supply-demand balance constraint based on the total generating capacity, the electric energy of the energy storage battery, the load demand electric energy and the transportation consumption electric energy; determining a fan cost function matched with the fan power of the first node, and determining a target function based on the fan cost function; on the basis of the target function and constraint conditions, optimization solution is carried out, a fan power optimal configuration scheme corresponding to the first node is obtained, the constraint conditions comprise electric energy supply and demand balance constraint, a proper transmission tower can be selected to be used for installing a fan, power configuration of the installed fan is optimized, the wind energy utilization efficiency is improved, and the power utilization rate of the fan is increased. Meanwhile, the installation cost of the fan is reduced.

The present invention relates to a method for optimizing the operation of a microgrid considering different operation modes, belonging to the technical field of microgrids. Based on the operation mode of the microgrid and the interactive power between the microgrid and the large power grid, a first objective function is constructed with the goal of minimizing the interactive cost between the microgrid and the large power grid; based on the rated power of each unit in the microgrid and the gas consumption of the gas turbine, a second objective function is constructed with the goal of minimizing the operation cost; based on the power generation power of the gas turbine, the total power generation of the wind turbine group, the total power generation of the photovoltaic unit group, the charging power and discharging power of the energy storage unit, a third objective function is constructed with the goal of maximizing the microgrid revenue; based on the set constraints, multiple objective functions are jointly solved to obtain an optimized operation plan for the microgrid. The method of the present invention can effectively improve the utilization rate of new energy output in the microgrid, give full play to the regulation ability of flexible resources such as energy storage in the microgrid, and reduce the operation cost of the microgrid.

The invention relates to the technical field of thermoelectricity, and particularly discloses a cogeneration heat regeneration system which comprises a boiler, a first back pressure machine, a first power generator, a second back pressure machine, a second power generator and a water supplementing heat regeneration system. Wherein the boiler comprises a superheater; a steam outlet of the superheater is communicated with a steam inlet of the first back pressure machine; the first generator is coaxially connected with the first backpressure turbine; a steam inlet of the second back pressure machine is communicated with a steam exhaust port of the first back pressure machine; the second generator is coaxially connected with the second backpressure turbine; exhaust steam of the second back pressure machine is used for heating and replenishing water, and finally the supplied water enters the boiler. Compared with a conventional heat regeneration system, the combined heat and power supply heat regeneration system has the advantages that under the condition that steam supply parameter conditions are not changed, the total power generation amount is increased, the power purchase amount from a factory to a power grid is reduced, and then the power utilization cost of the factory is reduced.

The invention discloses an inter-provincial power dispatching method and device, computer equipment and a readable storage medium, which can improve the utilization efficiency and safety of regional power resources and guarantee the stability of power supply. The method comprises the following steps: calculating a first total power generation amount and a first total power consumption amount corresponding to a first target province by adopting a power supply structure model and a power consumption characteristic model, and calculating a second total power generation amount and a second total power consumption amount corresponding to a second target province; inputting the first total power generation amount, the second total power generation amount, the first total power consumption amount and the second total power consumption amount into an inter-province power mutual aid demand model to obtain an inter-province power mutual aid demand amount; constructing an initial power transmission scheme according to the inter-provincial power mutual aid demand quantity, continuously adopting the power transmission constraint model and the optimization scheduling model to optimize the initial power transmission scheme until a preset optimization stopping condition is met, and taking the optimized power transmission scheme as a target power transmission scheme; and performing inter-provincial power dispatching according to the target power transmission scheme.

The invention provides an electric field micro-siting optimization method and device, electronic equipment and a storage medium, and relates to the technical field of new energy, and the method comprises the steps: constructing a wake flow speed model according to wake flow characteristic parameters; according to the kinetic energy balance theory, a wake effect model between the power generation devices is built based on the wake flow velocity model; constructing a wind direction and wind speed model based on the wind direction parameters and the wind speed parameters according to Weibull probability distribution; obtaining a power model according to the initial wind speed, the wind speed characteristics, the wind direction characteristics and the power curve of the power generation equipment; constructing a state space according to the wind speed, wind direction and position of the power generation equipment; optimizing a state space through an Actor network and a power model, and constructing an action space by taking the maximum generating capacity as a target; and optimizing the state space set and the action space set through the Critic network, and determining an action space result by taking the maximum total generating capacity as a target for constructing a site selection layout of the power generation equipment.

This invention discloses a method for optimizing the capacity allocation and multi-scale scheduling of a multi-energy complementary system, belonging to the field of multi-energy complementary configuration and scheduling technology. It analyzes the different resource characteristics and complementary relationships within a watershed, constructing a capacity allocation optimization model for hydropower, wind power, and solar power complementarity with the primary objective of maximizing total annual power generation and the secondary objective of maximizing minimum power output. The model is solved using a particle swarm optimization algorithm, with a focus on considering the capacity limitations of transmission channels. The results of scheduling operations for different energy allocation ratios are analyzed at different time scales, including medium- to long-term annual complementarity and short-term intraday complementarity. This invention can be applied to the planning stage of wind and solar energy capacity design, providing capacity allocation references and suggested optimization processes for hydropower.

This invention discloses a micro-site selection method for wind farms based on the coupling of micro-meteorology and micro-topography, relating to the field of wind power processing technology. The method includes: determining the annual total power generation model of the target wind farm, which is obtained by summing the target wake models of each wind turbine, used to calculate the annual power generation of each turbine; using the maximization of annual total power generation as the optimization objective, searching for the optimal location of each turbine in the annual total power generation model using the PSO algorithm to obtain the optimal location of each turbine in the target wind farm; the target wake model of each turbine is determined by the turbine parameters, altitude, moist air density, location, and turbine availability of each turbine. Through this technical solution, the influence of key physical factors such as altitude on wake and turbine output can be corrected, improving the accuracy and reliability of turbine location, and thus improving the accuracy and reliability of annual power generation prediction.

The application discloses a power scheduling method applied to a regional combined heat and power unit, and is based on a three-part framework of a combined heat and power system, a regional energy system and a heat and power separation system. After a relational expression of the three parts is established, the regional energy system heat load is introduced, the minimum power generation of the unit when the heat load demand is met is obtained, and the reasonable operation space of the total power generation of the combined heat and power unit is established based on the total cost of the combined heat and power unit being less than the total cost of the heat and power separation system. Through the analysis on the heat supply characteristics of the combined heat and power unit and the comparative analysis with the heat and power separation system, the best operation interval and the maximum benefit operation mode of the combined heat and power unit are obtained, so that the operation practice can be correctly guided.

Wind turbine with a total electrical output of at least 20 MW, characterized in that - the plant has several generators, each with a rated output of no more than 12 MW; - the generators are mechanically connected to the rotor shaft via a gearbox system with power sharing; - each generator is operated at a rated speed of at least 1000 rpm; - each generator is assigned a separate inverter; - each generator converter path can be switched on or off independently; - a central control system is in place which, in partial load operation, only activates the number of generator-converter paths required to meet the current power demand; - the control system is designed in such a way that the activated paths operate in the area of ​​highest efficiency.

The invention discloses an energy storage and pressurization method for improving the power generation capacity of a small hydropower station. Relates to the technical field of hydroelectric generation. The water turbine further communicates with a water pump, a water storage chamber and a gas storage chamber; two branches are arranged between the water pump and the water storage chamber, the water pump is arranged on one branch, and the water pump is driven by a motor; under a conventional water flow condition, water flow in a reservoir drives a generator through a water turbine for direct grid-connected power generation; starting a water pump to build pressure in the gas storage chamber by utilizing surplus electric energy of the power grid, and gradually raising the water head of the water storage chamber; after pressure building is completed, in the dry season, water in the water storage chamber and the reservoir drives the water turbine and the generator at the same time, variable-speed power generation is achieved through control of the converter, and the high-water-head and small-flow operation conditions are met; through energy storage and pressurization, a low-flow water body is creatively lifted to a high-pressure state, so that ecological flow can also be used for stable power generation, original waste water resources are converted into precious electric energy, and the annual power generation hours and the total power generation capacity of the power station are directly increased.

The invention provides a hydropower station generating capacity adjusting method, and relates to the field of hydropower dispatching, in particular to a hydropower station generating capacity adjusting method which comprises the steps that an adjusting mode is selected, and the generating proportion in the adjusting mode is determined; setting the planned operation time and the planned operation days of the hydropower station unit group to determine a monthly power generation plan; estimating the total generating capacity according to the generated capacity and the monthly power generation plan of the hydroelectric machine station group; according to the power generation proportion corresponding to the adjustment mode, calculating the total proportion monthly power generation quantity; estimating a predicted assessment electric quantity and a predicted reward electric quantity in combination with the assessment standard and the reward coefficient; and adjusting the proportionality coefficient to make the predicted assessment electric quantity accord with the constraint condition of the assessment standard. The method has the beneficial effects that the power generation plan can be simulated by combining the water quantity and the peak regulation requirements, the predicted assessment electric quantity and the predicted reward electric quantity are estimated, the basis for power generation plan adjustment is obtained, the power generation plan conforms to the assessment standard, the reward electric quantity is obtained, the cost is reduced, and economic benefits are obtained.

The invention relates to the technical field of power systems, and particularly discloses a short-term optimization operation method for a water-wind-light-storage multi-energy complementary system. The method comprises the following steps: S1, constructing a water-wind-light-storage multi-energy complementary short-term optimization operation model by taking maximization of the load tracking degree of the water-wind-light-storage multi-energy complementary system, minimization of the intraday output fluctuation of a downstream daily regulation hydropower station and maximization of the daily total power generation amount of clean energy as targets; s2, constructing constraint conditions of a water-wind-light-storage multi-energy complementary short-term optimization operation model; and S3, solving and calculating the water-wind-light-storage multi-energy complementary short-term optimization operation model by adopting a two-stage calculation dimensionality reduction decoupling method to realize short-term optimization operation of the water-wind-light-storage multi-energy complementary system. The method has the advantages that a multi-target scheduling model for water, wind, light and storage multi-energy complementary short-term optimization operation is established, a two-stage calculation model efficient dimension reduction decoupling solving method is provided, and optimization operation decision of the water, wind, light and storage multi-energy complementary system is achieved.