26results 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 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 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 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 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 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 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 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.

The invention discloses a smart park big data comprehensive management and control system, and the system comprises a data module which obtains the energy consumption data of a park and the external environment data of the park in real time, and carries out the processing of the energy consumption data and the environment data; and the energy management module takes the processed energy consumption data and environmental data as the input and output of a prediction model to obtain an energy optimization result, and sends the energy optimization result to the park service module and the multi-dimensional display module, and the multi-dimensional display module is used for displaying the energy optimization result in multiple dimensions. By acquiring the energy consumption data and the external environment data of the park in real time, the park can predict the future energy consumption condition based on the actual data and output the energy optimization result, so that the park can dynamically adjust the energy use strategy, the energy waste is reduced, and the energy utilization efficiency is improved. Meanwhile, personalized energy-saving schemes can be formulated according to behavior habits and requirements of different users, and the energy-saving awareness of the users can be improved.

The utility model discloses a spliced plastic floating platform flat ship, and mainly relates to the technical field of water carriers. Comprising a plurality of cuboid plastic floating boxes, each plastic floating box is provided with a water inlet / outlet and a sealing plug used for sealing the water inlet / outlet, and the buoyancy of the plastic floating boxes in water can be adjusted by injecting water into the plastic floating boxes; connecting plates are arranged at the four corners of the outer side walls of the plastic buoyancy tanks, mounting holes for mounting connecting bolts are formed in the connecting plates, the adjacent plastic buoyancy tanks are connected into a whole through the connecting bolts, and the upper surfaces of the spliced plastic buoyancy tanks are located on the same plane; the ship is convenient to disassemble and assemble and convenient to carry on a vehicle, corresponding areas can be spliced according to needs, water can be added according to needs to increase counter weights, loads of all parts of the ship body can be balanced, and the draft depth can be adjusted.

The invention discloses a gas turbine and light storage combined distributed new energy comprehensive allocation system, and belongs to the technical field of gas turbines.The gas turbine and light storage combined distributed new energy comprehensive allocation system comprises a gas turbine, the gas turbine internally comprises a gas compressor, a combustion chamber, a turbine and a power generator, and a photo-thermal system is connected between the gas compressor and the combustion chamber; the exhaust end of the turbine is connected with a waste heat utilization system, and the output end of the generator is connected with a power supply system. By adopting the gas turbine and light storage combined distributed new energy comprehensive allocation system, efficient, clean, flexible and economical energy supply can be realized, and wide application of renewable energy sources and transformation of energy structures are promoted.

The invention discloses a heat pump electricity storage system and method for coupling flue gas waste heat utilization and hydrogen fixation ammonia production, and the system comprises a solar heating device, a water electrolysis hydrogen production device, an ammonia synthesis device, a heat pump circulation device, a heat storage circulation device, and an organic Rankine cycle and carbon capture circulation device. The solar heating device, the water electrolysis hydrogen production device, the ammonia synthesis device, the heat pump circulating device, the heat storage circulating device and the organic Rankine cycle and carbon capture circulating device are connected in sequence; heat energy in flue gas waste heat is transferred into a working medium through electric driving, then the heat energy is stored in a high-grade heat energy form, when electric energy needs to be used, the stored heat energy is converted back to the electric energy, energy conversion and storage are achieved, the energy utilization efficiency is improved, utilization of renewable energy sources is supported, the load of a power grid is balanced, and the service life of the power grid is prolonged. The flue gas waste heat of the thermal power plant is recycled, the power generation efficiency of the power plant is improved, and coal consumption is reduced.

The invention relates to a wind-light-storage energy system optimal scheduling method containing an optimal dynamic grid-connected coefficient strategy, which comprises the following steps of: 1, constructing an HDEED model, and designing an objective function and a constraint condition of the HDEED model; 2, designing an optimal dynamic grid-connected coefficient strategy to stabilize the fluctuation of new energy power generation; 3, establishing an improved thermal power test system comprising a photovoltaic power station and a wind power station, and setting test system parameters; 4, designing a GWOH algorithm, initializing parameters of the GWOH algorithm, and defining a target function Fobj as a fitness function Fit of the algorithm; and step 5, obtaining a Pareto optimal leading edge of the HDEED model by adopting a GWOH algorithm, obtaining a compromise solution by utilizing a fuzzy theory, and obtaining a scheduling scheme for comprehensively optimizing the economical efficiency and the environmental protection property of the system through an optimal dynamic grid-connected strategy on the premise of stabilizing the fluctuation of new energy power generation.

The utility model provides an oil-free vacuum machine which comprises a cam main shaft, a first bearing sleeved on the cam main shaft, a double-eccentric cam sleeved on the first bearing, a second bearing sleeved on the double-eccentric cam, a guide sliding block and a driving assembly for driving the cam main shaft to rotate, a cylinder assembly and a piston assembly which are arranged in a rotary connection mode and horizontally opposite to each other are arranged on the connecting rod, the cylinder assembly is provided with an air inlet used for pumping high-pressure air into the cylinder assembly and an air outlet used for discharging the high-pressure air, and when the cam main shaft rotates, a first bearing arranged on the cam main shaft in a sleeving mode drives the double-eccentric cam. The double-eccentric cam drives the second bearing to do corresponding circular motion in the guide sliding block, the connecting rod drives the piston assembly to do reciprocating rectilinear motion on the same plane and the same center line on the air cylinder assembly, and when the piston assembly does reciprocating rectilinear motion, air is pumped through the air inlet and exhausted through the air outlet, so that a reciprocating cycle is completed.

The utility model discloses a regulation and storage system suitable for a combined system intercepting type sewage pipe network, and particularly relates to the technical field of sewage treatment, the regulation and storage system comprises an intercepting well, a treating pond and a regulation and storage pond, one side of the intercepting well is connected with the treating pond through a connecting pipe, and the rear end of the intercepting well is connected with the regulation and storage pond through a water guide pipe; intercepting valves are arranged between the blow-off pipe, the water guide pipe and the connecting pipe and the intercepting well; the rear end of the regulation and storage tank is connected with a plurality of reservoirs through shunt pipes; and water level detectors are mounted at the tops of the interception well, the treatment tank, the regulation and storage tank and the reservoirs. Through the interception well, the treatment tank, the regulation and storage tank and the water storage tank, the regulation and storage tank and the water storage tank can temporarily store part of sewage during rainfall or sewage discharge peak, the stored sewage is gradually discharged into the treatment system to be treated after the peak, and the regulation and storage tank and the water storage tank are distributed and mounted in a modularized manner, so that the sewage treatment efficiency is improved. The floor area of a single unit is reduced, assembly and installation are easy, the bearing capacity is high, and the application range is wide.

The invention relates to the technical field of energy consumption monitoring, in particular to a water, electricity, gas, heating and cooling energy consumption monitoring and collaborative energy saving method which comprises the following steps that energy consumption data of all energy systems are collected in real time through multiple sensor nodes installed in a building, and the energy systems comprise a water supply system, a power supply system, a gas supply system, a heating system and a cooling system; the energy consumption data comprises consumption data, fluctuation amplitude and an energy consumption time period; transmitting the energy consumption data to a central processing unit for preprocessing to form a complete energy consumption data set; comprehensively analyzing the mutual relationship among the energy systems, and generating an energy consumption interaction influence model among the energy systems; and the energy consumption peak period and the redundant use condition are identified, a collaborative energy-saving strategy is automatically generated, and scheduling among the energy systems is optimized. According to the invention, the overall energy efficiency of each energy system can be greatly improved, the load among the systems can be effectively balanced, and reasonable utilization of energy and long-term stable operation of the system are ensured.

The present application relates to the technical field of production planning and operation optimization, in particular to a cigarette equipment capacity matching optimization method based on an improved NSGA-Ⅱ algorithm, comprising: obtaining basic data of matching of cigarette production resources and demand; calculating constraint parameters of each product according to the basic data; constructing a cigarette equipment capacity matching multi-objective optimization model based on the constraint parameters; solving the cigarette equipment capacity matching multi-objective optimization model based on the improved NSGA-Ⅱ algorithm to obtain an optimal capacity matching scheme. The embodiment of the present application constructs a multi-objective optimization model, covers capacity gap, surplus rate balance and overtime, and improves the accuracy and efficiency of the algorithm in a complex production environment through an improved initial population generation strategy and a self-adaptive crossover and mutation mechanism. The method can accurately match capacity and demand, reduce waste, overtime and uneven load, significantly improve production efficiency and resource utilization, and optimize cigarette production management.

The invention discloses a vehicle charging intelligent reservation method, device and equipment and a medium. Comprising the steps that when a charging reservation request sent by a user is received, multiple pieces of charging basic information are acquired, and according to the charging basic information, the target charging amount and at least one charging point location are determined; acquiring power supply information of each charging point, and acquiring an optimal charging scheme of each charging point according to the charging basic information, the target charging amount and the power supply information of each charging point; the optimal charging schemes of all the charging point locations are screened and sorted, and a sorting result is pushed to a user side; and initiating a charging reservation request to the target charging point according to the target charging scheme selected by the user, and entering a charging management state after the target charging point is successfully reserved. By adopting the technical scheme, the optimal charging scheme can be automatically calculated according to user requirements, and multi-dimensional optimization is performed on the charging cost, the charging experience and the power grid load on the basis of ensuring that charging is completed.