50results about How to "Balance load" patented technology

The invention discloses an energy storage energy management system for improving a demand protection algorithm, and the system comprises a data collection module which is used for obtaining energy storage system load data, distributed energy operation data, and energy storage system operation data; the correlation feature analysis module is used for acquiring a correlation feature set between the load and the energy supply; the control strategy generation module is used for adjusting a charging and discharging threshold value and formulating a charging and discharging control strategy; the control strategy execution module is used for formulating a charging and discharging control strategy and adjusting the working mode of the energy storage converter; the cooperative execution module is used for dynamically optimizing a power distribution strategy by dispatching distributed energy and power grid cooperative work; and the dynamic power adjustment strategy adjustment module is used for adjusting the charging and discharging protection threshold value and the power adjustment strategy through a feedback mechanism. Through an intelligent control and scheduling mechanism, the charging and discharging efficiency of the energy storage system is improved, the stability and flexibility of the power grid are enhanced, and effective guarantee is provided for safe operation of the power grid.

The invention provides a production scheduling calculation method of a production plan scheduling platform. The method comprises the steps of data collection, demand prediction intelligent analysis, productivity planning and bottleneck analysis, production scheduling plan making, real-time monitoring and dynamic adjustment, plan execution and feedback analysis and report generation and decision support. Through distributed scheduling and real-time dynamic adjustment, the production plan can respond to emergencies such as equipment failure and order change in production in time, the continuity and stability of the production process can be ensured, production stagnation or delay caused by the emergencies is avoided, meanwhile, the production scheduling plan can be rapidly adjusted through real-time data feedback, and the production efficiency is improved. Resource utilization is optimized, waste is reduced, production efficiency is improved, intelligent productivity analysis and bottleneck identification are utilized, an enterprise can comprehensively know the use condition of each production resource, and possible bottleneck problems are found and solved in advance.

The invention relates to the technical field of wind energy management, and discloses a fine energy management method and system for a wind power plant, and the method comprises the following steps: S1, obtaining multi-source data, including real-time operation data, meteorological data and power grid load data of the wind power plant; s2, preprocessing the acquired multi-source data, including data cleaning, denoising, interpolation filling and standardization processing; s3, the generating capacity of the wind power plant is predicted based on a deep learning model, and the deep learning model is a hybrid model and comprises a long and short-term memory network and a convolutional neural network; and S4, using the generating capacity data output by the prediction model, and combining with the power grid load demand. Through deep learning, reinforcement learning and machine learning technologies, the power generation prediction precision of the wind power plant is improved, the scheduling and energy storage management strategy is optimized, and fault prediction and health monitoring of the wind turbine generator are realized, so that the operation efficiency and reliability of the wind power plant are improved.

The invention provides a layered optimization scheduling method and system for a wind power cluster and a medium, and relates to the technical field of power system optimization scheduling, and the method comprises the steps: determining evaluation indexes, obtaining the variable weight of each evaluation index, employing a membership function and a fuzzy comprehensive evaluation method, and obtaining the variable weight of each evaluation index; obtaining a membership score of each wind power plant of the wind power cluster under each evaluation index, and obtaining a comprehensive degradation score of each wind power plant; taking the ultra-short-term power predicted value of the wind power plant as the basis for judging the power change trend of the wind power plant, determining the climbing classification of the wind power plant, and determining the scheduling sequence of the wind power plant; on the premise that the power balance constraint between the wind power plants is met, the total output power of all the wind power plants is adjusted and controlled in real time according to the dispatching requirement for power increasing or power reducing of the wind power cluster and based on the dispatching sequence of the wind power plants of all the wind power plant groups. According to the method, the time-varying property and uncertainty of the wind power plant are fully considered, and the fatigue and fluctuation conditions of the whole wind power cluster are reduced.

The invention provides a personalized settlement method, system and device, and relates to the technical field of information, and the method comprises the steps: training and generating a power utilization optimization model through combining a user power utilization behavior portrait, a device adjustable space, an unadjustable device power supply scheme and an electricity price adjustment scheme; determining an optimal equipment power utilization scheduling scheme and a differentiated electricity price adjustment strategy under different power utilization time periods by utilizing the power utilization optimization model and aiming at the adjustable equipment of each user, and generating a personalized power utilization plan; real-time power grid load data is continuously monitored, when the load data exceeds a load threshold value, personalized power utilization plan dynamic optimization is triggered, and according to the optimized personalized power utilization plan, differentiated electricity price adjustment and equipment power utilization scheduling are executed on each adjustable device. Personalized requirements of users are met, the load of the power grid is effectively balanced, and fine management and optimization of power utilization of the smart home are realized.

The invention relates to the technical field of municipal drainage pipeline one-map modeling processing, in particular to a municipal drainage pipeline one-map modeling processing method. The method comprises the following steps: extracting pipeline structure data based on a municipal drainage pipeline diagram, carrying out rainfall flood drainage main road analysis, and predicting the rainfall flood drainage capability of the main road. And calculating the pressure of the main trunk of the drainage pipeline, and carrying out bearing capacity analysis, including pipeline deformation, fracture probability evaluation and bearing capacity evaluation. Urban rainfall and topographic data are obtained, a runoff drainage pipeline network structure model is constructed, and water flow overload carrying analysis is carried out. According to the water flow overload carrying data and the bearing capacity data, real-time drainage optimization is carried out, and the drainage effect of the drainage pipeline network is improved. According to the method, the real-time drainage technology of the municipal drainage pipe is more efficient and safer through one-map modeling processing optimization of the municipal drainage pipe.

The invention belongs to the technical field of charging pile management, and discloses a charging pile intelligent management method and system. Comprising the following steps: carrying out data acquisition on a target area and charging piles needing to be managed in the target area to obtain corresponding charging pile data and area load data; uploading the data to a pre-constructed scheduling block chain; performing electric pile diagnosis on the corresponding charging pile based on the collected electric pile data to obtain a corresponding fault diagnosis result, judging whether the charging pile has a fault based on the fault diagnosis result, and if not, marking the corresponding charging pile as a healthy electric pile; if the fault exists, fault information is generated and fault early warning is carried out; performing power distribution load management on the corresponding healthy electric piles in combination with the collected regional load data; according to the invention, intelligent management of the charging pile is realized, the operation efficiency and safety of the charging pile are improved, and more efficient power distribution load management is realized in combination with the charging demand of a user.

The invention provides a multi-objective optimization method, device and equipment based on flexible resources of a charging station, and can be applied to the technical field of new energy automobiles. The method comprises the following steps: in response to a scheduling request for flexible resources of a charging station, obtaining a preset comprehensive resource transaction parameter, a predicted charging amount, a charging duration and historical charging information; obtaining a dynamic resource transaction parameter according to the predicted charging amount and the charging duration; according to the historical charging information, a preset membership function and the fuzzy set, obtaining respective initial discharging willingness of the target object in the N time periods; taking the lowest operation consumption of the charging station and the highest discharge exchange value of the new energy vehicle as target functions, and adjusting the initial resource transaction parameters and the initial discharge intention based on a target constraint condition and a double-layer decision model constructed according to the initial discharge intention and the dynamic resource transaction parameters; and obtaining respective target resource transaction parameters of the N time periods and respective target discharge willingness of the target object in the N time periods.

The invention relates to a wind-solar-storage-coordinated power distribution network optimization scheduling method, computer equipment and a wind-solar-storage-coordinated power distribution network optimization scheduling system. The method comprises the steps of determining intra-day predicted operation cost of the power distribution network according to intra-day wind and light cost parameters; obtaining the load side power consumption demand quantity and the source side power generation quantity in the day; according to the intra-day predicted operation cost, the intra-day load-side power consumption demand and the intra-day source-side power generation amount, determining the intra-day source-side planned power supply amount; when it is determined that power supply of the power distribution network is insufficient according to the source side planned power supply amount in the day and the source side actual power supply amount in the day, power utilization scheduling is carried out by adopting B-type excitation type demand response, so that load balance and peak load shifting of the power distribution network are achieved; and when it is determined that power supply of the power distribution network is excessive according to the source side planned power supply amount in the day and the source side actual power supply amount in the day, redundant electric energy is stored. By adopting the method, both load balance and utilization efficiency of power resources can be considered.

The invention relates to the technical field of power grid influence analysis, and relates to a method for analyzing the influence of multi-access electric vehicle charging piles on power grid harmonic waves, which comprises the following steps: setting a monitoring time period, and simulating that the multi-access electric vehicle charging piles are accessed to a power grid under the set number; collecting power grid load data under each set number of electric vehicle charging piles in the current monitoring time period, and performing prediction analysis on the power grid harmonic level under each set number of electric vehicle charging piles in each future monitoring time period according to the power grid load data, the maximum number of the electric vehicle charging piles which can be accessed to the power grid in each future monitoring time period is determined according to the maximum number and the set power grid harmonic tolerance threshold value and is output to an external device, the number and distribution of the charging piles are reasonably controlled by scientifically analyzing the influence of the access of the charging piles on the harmonic pollution of the power grid, the load of the power grid can be effectively reduced, and the reliability of the power grid is improved. The stability and the power supply quality of the power grid are improved, and the configuration and the utilization of power resources are optimized.

The invention discloses a V2G scheduling method and system based on a double-layer optimization model, and the method comprises the steps: obtaining electric vehicle data and power grid load data of a target region, and screening a first electric vehicle set participating in scheduling according to the electric vehicle data; in the first optimization process, performing optimization scheduling on the first electric vehicle set based on the power grid load data and a pre-constructed first scheduling optimization model to obtain a first optimization result; in the second optimization process, secondary optimization scheduling is carried out on the first optimization result according to the electric vehicle data and a pre-constructed second scheduling optimization model, and a second optimization result is obtained; taking the second optimization result as the input of the first optimization process, and iterating the first optimization process and the second optimization process to preset times to obtain a final optimization result; and performing scheduling processing on the first electric vehicle set according to the final optimization result. According to the method provided by the invention, the V2G scheduling efficiency is improved.

The invention discloses a configuration method and device of an energy storage system. The method comprises the following steps: acquiring predicted electricity demand data of a to-be-interacted power grid object; evaluating the power consumption demand data, and respectively generating a plurality of capacity configuration schemes and a plurality of power configuration schemes of the energy storage system to be configured based on an evaluation result; inputting the capacity configuration schemes into the operation models of the to-be-interacted power grid objects, and constructing a discharge power demand curve according to the obtained output results of the models; respectively inputting the power configuration scheme into a pre-constructed operation model of a to-be-interacted power grid object, and constructing a discharge capacity demand curve according to each obtained model output result; processing an intersection result of the discharge power demand curve and the discharge capacity demand curve according to an optimization target to obtain an optimal set; and executing the preparation strategy constructed by the optimal set. According to the method provided by the invention, a quantitative guidance range is provided for the distribution and storage demand of the energy system.

The invention discloses a peak-valley period demarcation method based on guiding charging load translation. The peak-valley period demarcation method based on guidance of charging load translation comprises the following steps: acquiring residential area data including private charging pile historical data and basic load data, and analyzing data features of the residential area data; establishing an upper-layer power grid total load model by taking peak load shifting as an objective function; establishing a lower-layer resident charging load model by taking the minimum charging cost as an objective function; according to the method, the charging load translation is guided, so that the defects in the aspect of charging period management in the prior art are overcome.

The invention belongs to the technical field of data processing, and particularly relates to an energy storage transaction data processing method and model based on an electric power spot market environment, and the method comprises the steps: analyzing the historical energy storage state of an electric power spot market platform to obtain a historical energy storage state feature value, and analyzing the historical transaction state of the electric power spot market platform to obtain a historical energy storage state feature value; obtaining a historical transaction state characteristic value, combining a real-time meteorological state data set, performing comparison to obtain a predicted daily charging frequency of an energy storage battery, a predicted power transmission line power factor and a predicted power grid load capacity, and performing comparison based on a scheduling optimization characteristic value to obtain an electric power spot market platform scheduling optimization scheme; the system comprises an energy storage state characteristic value analysis module, a transaction state characteristic value analysis module, a meteorological state data set acquisition module, a prediction data analysis module and a scheduling optimization scheme comparison module. The method can improve the capability of judging the future power demand and supply condition, helps to balance the power grid load, and enhances the flexibility and stability of the power system.

The invention relates to the technical field of new energy automobile charging management, in particular to an intelligent charging and discharging optimization method and system for a new energy automobile charging station battery, and the method comprises the steps: constructing a charging demand prediction model through employing a long short-term neural network LSTM model, and predicting the charging demand of a future time period; constructing a multi-type optimized charging and discharging strategy which comprises a peak load shifting strategy and a new energy consumption strategy; a battery charging efficiency evaluation model is constructed, the charging efficiency is monitored in real time, and abnormity is warned in time; based on the evaluated battery charging efficiency, constructing a battery charging scheduling model of the charging station, and when a plurality of batteries are charged at the same time, solving a global optimal charging power distribution scheme; according to the method, multiple aspects of charging demand prediction, charging and discharging strategy optimization, battery efficiency evaluation, charging scheduling and the like are comprehensively considered, and an effective solution is provided for intelligent operation of the new energy automobile charging station.

The present invention discloses a reactive power optimization method for distribution network of electric vehicle station taking into account transfer reinforcement learning, describes the charging and discharging scheduling problem of a single electric vehicle as a Markov decision process, and solves the decision process by adopting the PPO method; adopts the TRL technology to migrate the trained EV strategy model to vehicles of different types and regions to obtain the EVS model; models the EVS model into a reinforcement learning intelligent agent to participate in the reactive power optimization of the distribution network, and uses the PPO method to train the reactive power optimization strategy of the intelligent agent, and the reactive power regulation model of the distribution network based on the EVS; uses the real time-varying electricity price, EV travel behavior distribution, and PDN load to train the model of the Markov decision process, and finally obtains the charging and discharging strategy model and reactive power regulation strategy model of the EVS, and tests and deploys the model online. This method can effectively utilize the reactive power output capacity of the EVS, improve the power loss of the distribution network, and thus improve the operation efficiency and stability of the entire power grid.

The utility model discloses a novel liquid homogenizing device for an evaporator, and relates to the technical field of evaporators. The novel liquid homogenizing device for the evaporator comprises the evaporator, an air outlet is formed in the top of the evaporator, a liquid homogenizing device is welded to the inner wall of the evaporator, a liquid inlet pipe is arranged at the top of the liquid homogenizing device, and the liquid inlet pipe communicates with an expansion valve through a pipeline; the liquid uniformizing device comprises a distribution head, a distribution pipe, a liquid uniformizing pipe and a mounting plate. According to the novel liquid equalizing device for the evaporator, load management is carried out on a unit according to the actual load of a whole air conditioning system, and the situation that a compressor carries liquid and cannot return oil due to compressor oil deficiency caused by air conditioning load changes is avoided; false alarm and false start and stop caused by unit load jump are avoided, heat exchanger pipe drying can be caused by too small expansion valve opening, liquid carrying caused by incomplete evaporation can be caused by too large expansion valve opening, and suction liquid carrying is reduced while superheat degree control is achieved.

The utility model relates to pre -stress construction technical field discloses a kind of machine head of threading machine, including base, including base, the horizontal tensile mechanism is separately arranged on the base along its length direction, and the steel strand clamping mechanism is arranged at each horizontal tensile mechanism end portion;When working, the steel strand clamping mechanism at different positions is alternately clamped to steel strand, and the horizontal tensile mechanism is alternately operated, and the relay conveying to steel strand is completed;The utility model can realize the efficient, stable, continuous threading operation of steel strand, and improve work efficiency.

The present application provides a personalized settlement method, system and equipment, which relates to the field of information technology, including: training and generating a power consumption optimization model by combining the user's power consumption behavior portrait, the adjustable space of the equipment, the power supply plan of the non-adjustable equipment and the power price adjustment plan; using the power consumption optimization model, for each user's adjustable equipment, in different power consumption periods, determine the optimal equipment power consumption scheduling plan and differentiated power price adjustment strategy, and generate a personalized power consumption plan; continuously monitor the real-time power grid load data, and when the load data exceeds the load threshold, trigger the dynamic optimization of the personalized power consumption plan, and perform differentiated power price adjustment and equipment power consumption scheduling for each adjustable equipment according to the optimized personalized power consumption plan. Meet the personalized needs of users, effectively balance the power grid load, and realize the refined management and optimization of smart home power consumption.

The present invention discloses a three-condition system with an ejector, aiming to provide a three-condition system in which a single-stage compression refrigeration system is used in air conditioning working condition, a quasi-two-stage compression refrigeration system with an ejector and intermediate air supply is used in ice making working condition, and a quasi-two-stage compression heat pump system with an ejector and intermediate air supply is used in winter heating working condition, so as to reduce the initial investment cost of the system, reduce energy consumption and operating costs, and save energy. The system includes a compressor with intermediate air supply, a four-way reversing valve, an outdoor heat exchanger, an indoor heat exchanger, an ice making evaporator, an economizer, an ejector, a throttling device, a regulating valve group and a plurality of valves. The switching of the single-stage compression refrigeration system, the quasi-two-stage compression refrigeration system with an ejector and the quasi-two-stage compression heat pump system with an ejector and intermediate air supply is realized by opening and closing a plurality of valves, thereby reducing the initial investment of the system.

The invention discloses a charging energy storage adjustment processing method and system, through real-time monitoring and historical data prediction, in combination with an intelligent charging and discharging management strategy, the operation efficiency of a charging pile and the load balance capability of a power grid are improved, the accurate control of the system on the current condition is ensured through real-time data, and the real-time monitoring of the system is ensured. Historical data analysis enhances the accuracy of prediction, and dynamic charging and discharging management optimizes energy use, reduces power waste, and has positive influence on the stability of a power grid.

The invention discloses a V2G-based microgrid architecture on an ocean floating island. The V2G-based microgrid architecture comprises an alternating current side system, a direct current side system and an alternating current-direct current conversion management system, the direct-current side system comprises a battery energy storage system, a wind power / photovoltaic power generation system, a fuel cell power generation system and a direct-current hydrogen production system which are connected to a direct-current power grid; the battery energy storage system comprises a power grid system inherent battery energy storage station and a vehicle energy storage battery connected to a direct current charging station. The direct-current hydrogen production system is used for electrolyzing water to produce hydrogen and storing the hydrogen when the generating capacity of the wind power / photovoltaic power generation system is surplus; the fuel cell power generation system is used for generating power by using hydrogen when electric quantity is insufficient; the AC-DC conversion management system is used for mutual conversion of electric energy between the AC side system and the DC side system. A three-stage energy stabilization system which takes a battery energy storage station as a main part, a direct current hydrogen production system and a fuel cell as auxiliary parts and an energy storage battery of a vehicle as a standby part is adopted, so that the stability and the reliability of the micro-grid are effectively improved.

The invention discloses a silurus meridionalis ecological breeding method based on a land-based round pond and a rice field system, which comprises the following steps: firstly, building the rice field system and the land-based round pond, connecting the rice field system with the land-based round pond through a water body circulating system, and limiting a water body volume ratio; and then putting the small-sized primary fries into the land-based round pond, feeding the small-sized primary fries with feeds with different particle sizes for cultivation, screening out large-sized secondary fries from the land-based round pond after cultivation for 30-45 days, transferring the large-sized secondary fries to a rice field system, feeding the large-sized secondary fries with feeds with different particle sizes and natural baits, and continuing to cultivate the large-sized secondary fries until adult fishes are obtained. The land-based round pond, the rice field system and the water body circulation system are combined to form an ecological circulation culture system, the relation between the nitrogen and phosphorus bearing capacity of the rice field system per unit water body and the discharge concentration of the tail water of the round pond is accurately defined by setting the water body proportion of the rice field system and the land-based round pond, the pollutant load is balanced, and the yield of the round pond is improved. Therefore, the water quality purification efficiency is improved, the problem of large water quality fluctuation in a traditional mode is solved, and the ecological coupling efficiency is improved.

The application discloses a control method for reducing energy consumption of a variable-frequency refrigerator, which judges the temperature difference of an environment sensor, a refrigeration sensor and a freezing sensor, combines to judge the refrigerator load condition, controls the compressor rotating speed, controls the temperature difference of the opening and stopping point of the non-freezing chamber, increases the frequency of the opening and stopping of the non-freezing chamber air door, reduces the temperature fluctuation of the non-freezing chamber, balances the load of each chamber, reduces the starting load, thereby reduces the starting power loss, and realizes the reduction of energy consumption.

The invention discloses a large-scale load transient response system and method for a power grid, and relates to the technical field of power systems, and the system comprises a data collection module, a central processing unit, a load adjustment module, a user interface module, a safety protection module, and an output voltage and frequency adjustment module. The data acquisition module is used for acquiring operation data of a power grid in real time and transmitting the data to the central processing unit through a high-speed communication network; the large-scale load transient response system can effectively improve the transient response capability of the power grid, ensures the stable operation of the power grid under the large-scale load condition, and can balance the load of the power grid, reduce the energy waste and improve the power utilization efficiency through real-time monitoring and rapid adjustment under the condition of not influencing the normal power utilization of a user. And meanwhile, an output voltage and frequency adjustment module is introduced, so that the loss in the energy conversion process is minimized, and the operation efficiency and the environmental protection performance of the power grid are further improved.

The modularized wearable upper limb exoskeleton comprises a shoulder rest module attached to the shoulder and back of a human body, one end of the shoulder rest module is connected with a power control module, the other end of the shoulder rest module is connected with an upper arm exoskeleton module, the upper arm exoskeleton module is attached to the upper arm of a user, and the bottom of the upper arm exoskeleton module is connected with an elbow joint module; the elbow joint module is connected with the forearm exoskeleton module; the forearm exoskeleton module is attached to the forearm of the human body and can rotate with the elbow joint module as the center axis. The forearm exoskeleton module is connected with the hand exoskeleton module, and the hand exoskeleton module accommodates the hand of a user; and the lengths of the upper arm exoskeleton module and the front arm exoskeleton module are adjustable. The mechanical structures of the shoulders, the upper arms, the elbows, the forearms and the hands of the modular mechanical exoskeleton flexibly adapt to the sizes of different parts of the body of a patient; the light-weight mechanical exoskeleton is convenient for the patient to use and perform rehabilitation training in daily life.

The invention discloses a charging power distribution method and device, a storage medium and electronic equipment. The method relates to the technical field of intelligent power grids, and comprises the following steps: carrying out calculation processing based on power generation parameters of different power generation objects of a regional power grid and carbon emission factors corresponding to the power generation objects to obtain regional carbon emission factors; based on the regional carbon emission factor and a preset constraint condition, a preset optimization algorithm is adopted to solve an objective function taking minimization of the carbon emission as an objective, and optimal charging power parameters corresponding to different charging periods of the object to be subjected to power distribution are obtained; and distributing the charging power of the object to be subjected to power distribution in each different charging period based on each optimal charging power parameter. According to the method, the power use of the charging pile is optimized, the power grid carbon emission is reduced to the maximum extent, the power grid load is balanced, and the working efficiency of the charging pile is improved.

The invention relates to the technical field of efficiency improving systems, in particular to an air cooling unit efficiency improving system which comprises a compressed air energy storage and release module, a heat exchange module, an air cooling adjusting module, an intelligent control module, a waste heat recovery and utilization module and an environment monitoring and self-adaptive adjusting module. The compressed air energy storage and release module comprises a compression unit, an energy storage unit, a heat exchange and heat storage unit and a power generation unit, and the heat exchange module comprises a heat exchange core unit, a heat source supply unit, a cooling medium supply unit, a monitoring unit and an auxiliary equipment unit. The air cooling adjusting module comprises an intelligent optimization control unit, an air cooling system unit, a power supply unit, an auxiliary heat dissipation unit and an alarm unit. According to the system, heat generated in the operation process of the air cooling unit can be efficiently recovered through the waste heat recovery and utilization module, the unit can automatically adjust operation parameters according to external environment parameters and operation data through the intelligent control and self-adaptive adjustment functions, and the optimal efficiency is kept.

The invention belongs to the technical field of petroleum field operation devices, and particularly relates to a pumping unit which comprises a base, a large frame, a rear support, a motor, a speed reducer, a crank, a lower connecting rod, a rocker, an upper connecting rod, a walking beam, a horse head and a balance weight. The lower connecting rod is connected with the middle part of a rocker; the lower part of the rocker is connected with the rear bracket; the upper part of the rocker is connected with the lower part of an upper connecting rod; the upper part of the upper connecting rod is connected with the rear part of a walking beam; the horsehead is flexibly connected with a wellhead load, and the rear part of the walking beam is connected with a counterweight. Compared with a crank balance beam-pumping unit, the crank balance beam-pumping unit has the beneficial effects that the crank balance beam-pumping unit is simple in structure, the length of the crank is shortened, parts are light in weight, installation and maintenance are convenient, practicability is high, industrial production is facilitated, stress of the crank and the connecting rod is reduced, the net torque peak value on the crank shaft is reduced, the installed power is reduced, and electric energy loss is effectively reduced; and the power-saving effect is obvious. And particularly for low-yield wells, the energy-saving effect is particularly obvious, and the popularization and application prospects are wide.

The invention belongs to the technical field of power systems, and relates to a cascade collaboration-based intraday optimal scheduling method, system and equipment for a hybrid pumped storage power station, and a medium. The method comprises the following steps: collecting input data; calculating cascade output of each power station in a peak regulation period and cascade power station output in a valley filling period according to the collected data; calculating the sum of the output of the cascade power stations in the peak shaving period and the sum of the output of the cascade power stations in the valley filling period; taking the maximum sum of the output of the cascade power stations in the peak regulation period and the minimum sum of the output of the cascade power stations in the valley filling period as targets to construct an optimization target function; setting constraint conditions; according to the constructed optimization objective function and a set constraint condition, with benefit optimization as a target, constructing a cascade power station intra-day collaborative peak regulation optimization model; input data are obtained, calculation is carried out through the cascade power station intra-day collaborative peak regulation optimization model, and a cascade power station intra-day collaborative peak regulation optimization strategy is obtained. The problem of intra-day scheduling after hybrid pumped storage is built is solved.