745 results about "Generating capacity" patented technology

Disclosed in the present invention are a load-prediction-based control method and apparatus for an energy storage apparatus, and a terminal device and a storage medium. The method comprises: using a preset load prediction model to perform prediction on the basis of real-time operation data, so as to obtain a predicted load value of a micro-grid within a future time period; then, on the basis of a power generation capacity and the predicted load value, determining whether there is surplus electricity after the current power generation capacity of the micro-grid satisfies a future load demand; if so, controlling an energy storage apparatus to be charged, so as to avoid the waste of electric energy; and if not, controlling the energy storage apparatus to supply power to the micro-grid, so as to ensure that the micro-grid can satisfy the future load demand, thereby effectively ensuring the stable power supply of the micro-grid.

The invention discloses a wind-solar complementary power generation system and method based on intelligent monitoring, belongs to the field of wind-solar complementary power generation, and is used for solving the problems of fixed parameter weight, lack of environment-equipment coupling analysis and large power generation capacity prediction deviation of a traditional system. Generating a standard matching curve template to match the current working condition, and monitoring a working condition fluctuation index to trigger updating; key equipment parameters are screened based on historical data and association degree, an environmental working condition scene association rule base is constructed, generating capacity fluctuation is judged through double references, and a core influence chain is traced; matching historical samples through Euclidean distance to calculate an initial generating capacity predicted value, constructing three types of correction coefficients of environmental deviation, equipment health and a core influence chain, and obtaining a comprehensive correction factor and a correction predicted value; the monitoring accuracy and the fluctuation attribution capability are improved, the prediction deviation is reduced, and the system operation strategy is ensured to adapt to the actual power generation demand.

The utility model provides a peak-shaving steam supply system for deep waste heat utilization of a thermoelectric unit, which deeply recovers cold end waste heat and flue gas waste heat of a cogeneration unit, is coupled with a two-stage compression heat pump, extracts waste heat to heat demineralized water, and serves as a primary heat source for supplying industrial steam, so that the waste heat participates in external heat supply; the superheater utilizes the generating capacity of the unit to enable industrial steam to reach steam supply parameters, the waste heat of the unit and the generating capacity are combined for external steam supply, the circulating heat efficiency is improved, the steam supply capacity is improved, meanwhile, the on-grid electricity is reduced, thermoelectric decoupling is achieved, the unit adjusting operation interval is expanded, the operation cost and pollutant emission are reduced, and peak regulation or spot transaction earnings are improved. And a clean, low-carbon, flexible, efficient, economical and energy-saving combined heat and power generation system is constructed.

This invention provides a graph neural network-based distributed solar power output prediction method and system that improves prediction accuracy from three aspects: data, models, and parameters, and offers a practical and needs-based solution for highly accurate short-term predictions of distributed solar power plants. [Solution] The method initializes the irradiation data of distributed solar power generation for a set period prior to the current time using spatial kriging interpolation, expands the initialized irradiation data based on a graph-diffuse convolutional network to obtain expanded irradiation data, combines the graph-diffuse convolutional model and a spatial Transformer module using a residual structure to capture spatial features, and uses a trend gate recurrent unit network as input to obtain a prediction result of distributed solar power generation output for a set period after the current time.

Provided are a method and apparatus for detecting a failure of a solar module. The method includes obtaining real-time power generation data of each of a plurality of solar modules included in at least one solar array, setting a reference value using at least one of past power generation data of the plurality of solar modules and specifications of the plurality of solar modules, determining each of the plurality of solar modules to be either a normal solar module or an abnormal solar module by comparing the reference value with a power generation amount of each of the plurality of solar modules, which is calculated using the real-time power generation data, and providing an interface displaying a solar module determined to be the abnormal solar module.

The invention relates to the technical field of wind power plant generating capacity prediction. The invention provides a wind power plant generating capacity prediction method and system considering a maintenance plan and an equipment health degree. The method comprises the following steps: collecting multi-source data of a wind turbine generator, and carrying out preprocessing and space-time alignment; based on the health monitoring data, state features are extracted, and a real-time health degree index is calculated by adopting a fuzzy comprehensive evaluation method; optimizing the maintenance plan according to the health degree index, and establishing a mapping relation among the health degree, the maintenance measures and the power generation loss; taking the meteorological data, the historical operation data, the health degree index and the maintenance influence coefficient as input and the historical power generation amount as output, and constructing and training a machine learning prediction model; and inputting data of a to-be-predicted time period to obtain a preliminary prediction result, and dynamically correcting model parameters through deviation analysis to obtain a final power generation prediction value. The problem that the prediction precision is insufficient due to the fact that an existing wind power plant generating capacity prediction method does not systematically consider the dynamic influence of the equipment health state and the maintenance plan is solved.

The invention belongs to the technical field of energy planning, and discloses a coal mining area green electricity direct connection planning method and system, and the method comprises the steps: integrating geographic space information, obtaining a three-dimensional geographic space information database, carrying out the processing through a land recycling evaluation model, obtaining a thermodynamic diagram, and carrying out the quantitative analysis of the thermodynamic diagram, and obtaining the power generation amount. Processing and fusing by using a space-time convolutional neural network and a distributed intelligent sensing model to generate a meteorological database; analyzing by using a wind power and photovoltaic space-time output model to obtain a photovoltaic combined sample; processing by using the load prediction model to obtain a load prediction curve set; a source-load time sequence mismatch quantitative model is input for analysis, and an energy storage collaborative configuration scheme is obtained; inputting a multi-target line optimization model for analysis to obtain a direct connection line topological structure diagram; and performing data-driven optimization decision optimization to obtain a source storage load collaborative optimization model, and performing coal mining area green electricity direct connection planning through the source storage load collaborative optimization model. The green electricity is obtained through direct connection, and the cost is reduced.

The invention discloses a polar region environment-oriented two-stage micro-siting optimization method for a wind generating set, and relates to the technical field of polar region renewable energy planning and wind power generation, the optimization method comprises the following steps: polar region environment parameter initialization and scene modeling; the first stage is grid primary selection based on mixed integer linear programming; the second stage is coordinate refinement based on a multi-population genetic algorithm; and scheme output and efficiency evaluation. According to the method, a sector reweighting mechanism of extremely cold correction parameters is realized through reweighting of biochemical parameters and scenes in an environment special for a polar region, the extremely cold correction parameters are directly embedded into a wind regime scene set and a power model, and the problem that a conventional land model can obviously underestimate or overestimate single-machine power and wake flow propagation distance under extremely low temperature and low roughness conditions, so that the reliability of the model is improved is solved. Therefore, the power prediction and wake flow loss evaluation are more practical under the polar region conditions such as the south pole, so that the engineering reliability of site selection decision and the accuracy of generating capacity prediction are improved.

The invention discloses a multi-element flexible load feature extraction method based on hydrogen energy demand response, and relates to the technical field of hydrogen energy demand resource planning. In order to construct an optimization control model responding to a power grid signal, hydrogen production efficiency maximization and power utilization planning rationalization are realized. The method specifically comprises the following steps: obtaining new energy power generation power characteristic data, predicting daily average generating capacity data according to the data, obtaining all-day time-of-use electricity price characteristic data of a commercial power grid, and dividing the data into peak / flat / valley time periods; according to the multi-element flexible load feature extraction method and the control strategy, the electric energy use strategy and the hydrogen production and hydrogen supply equipment operation strategy suitable for the whole hydrogen energy supply project can be formulated according to the stirring filtering of the new energy generating capacity, so that the energy consumption is reduced on the premise that the stable and sufficient hydrogen supply amount is ensured. The power consumption of the hydrogen energy supply project in the peak period and the flat period of the power grid is effectively reduced, and the comprehensive energy efficiency and the green power consumption rate of the hydrogen energy supply project are effectively improved.

The present invention belongs to the field of power generation scheduling of power systems. Disclosed is a cascade pre-flood energy storage risk analysis and control method for a hydro-wind-solar complementary system. The method comprises: using pre-flood energy storage as a constraint to establish a dry-season drawdown model and a flood-season water storage scheduling rule, so as to determine a simulation operation criterion; constructing a set of dry-season power shortage, flood-season water abandonment, insufficient year-end energy storage and wind-solar power curtailment indexes, so as to quantify multi-stage and multi-source operation risks; and coupling Monte Carlo and fuzzy membership degrees to characterize multi-dimensional uncertainty scenarios and probabilities thereof, and using simulation analysis to determine quantitative relationships between pre-flood energy storage and hydro-wind-solar complementary benefits, risk probabilities and risk losses. Results of instance analysis of a hydro-wind-solar complementary system in a certain extremely-large drainage basin show that the present invention can comprehensively describe risks in terms of occurrence probabilities and losses, and a verification result shows that by means of accurate risk description and reasonable energy storage control, the system power generation is increased by 580 million kWh, and the risk loss is reduced by 42% on average, and therefore the present invention exhibits good practicability.

The invention provides a user side shared energy storage multilayer optimization method considering joint pricing and demand response, and relates to the technical field of integrated energy systems.The method comprises the steps that firstly, basic operation parameter data in a regional integrated energy system are collected, and the relation between the power of a shared energy storage power station and the power of the shared energy storage power station used by each user is determined; and calculating the price excitation demand response income and peak regulation cost of the user group, and further constructing a user-side shared energy storage multilayer optimization model and solving the user-side shared energy storage multilayer optimization model. Through optimizing a joint pricing and energy scheduling strategy, the model significantly reduces the overall operation cost of a user group, and effectively reduces the power purchase demand of a power grid in a peak period. Meanwhile, the system fully consumes the renewable energy generating capacity, and the problem of low utilization rate caused by resource waste is avoided. Therefore, the power supply pressure of the power grid is relieved, the operation stability is improved, the synergistic interaction of the source network load storage is realized, and the win-win situation among multiple main bodies is achieved.

The invention relates to the technical field of wind turbine generators, and discloses an active wake flow yaw regulation and control method and device considering fatigue damage of a wind turbine generator. A wake flow yaw optimization model is constructed by combining wind conditions, unit coordinates and operating parameters with an engineering wake flow model, and it is ensured that wake flow evaluation fits the actual working condition; the fatigue damage of the unit is accurately quantified by calculating the structural load and the target damage equivalent load, so that the yaw limiting angle is determined, and the damage is prevented from being intensified due to excessive yaw in the regulation and control process; a multi-target yaw optimization method for balancing generating capacity and fatigue damage is adopted for iterative solution to obtain a field-level yaw control matrix, damage deterioration caused by the fact that an old strategy is still used after fatigue of a unit is increased is avoided, long-term safe and efficient operation of the wind power plant is finally guaranteed, and the dual targets of long-term safe operation and efficient power generation of the wind power plant are achieved. And the dual requirements of the wind power plant on the operation safety and the economical efficiency in the whole life cycle are practically met.

The invention relates to the technical field of micro-grids, in particular to a supply-demand relationship-based micro-grid dynamic balance adjusting system, which comprises a data acquisition module, a data processing module, a standard line determination module and a control instruction generation module. The data acquisition module is used for acquiring historical data and current data; the data processing module is used for determining a predicted power demand in the target time period based on the historical power consumption data and the current power consumption data, and determining a predicted power generation amount in the target time period based on the historical power generation data, the historical environment data and the predicted environment data; the standard line determination module is used for determining an expected temporary storage energy standard line in a target time period based on the predicted power demand and the predicted generating capacity; and the control instruction generation module is used for generating a control instruction based on the current storage electric quantity and the expected temporary storage energy standard line.

This application relates to a control method, device, equipment, and storage medium for new energy power generation equipment. The method includes: acquiring multi-dimensional operational data of the new energy power generation equipment; predicting the operational state of the new energy power generation equipment based on a target analysis model adapted to the data type of the multi-dimensional operational data, obtaining state prediction data; using the state prediction data as input data, performing global optimization scheduling processing with the optimization objectives of maximizing power generation and minimizing the failure rate of the new energy power generation equipment, obtaining optimized scheduling parameters; encapsulating the optimized scheduling parameters into scheduling control instructions; and using the scheduling control instructions to control the new energy power generation equipment. This method can accurately identify faults in new energy power generation equipment, effectively maintain the equipment, and shorten its lifespan degradation rate.

This invention discloses a PIDNN-SO-based method for optimizing the layout of offshore wind farms, belonging to the field of wind farm optimization design technology. The method first inputs wind farm, turbine, and wind resource parameters, sets constraints on turbine spacing, boundaries, and wake overlap rate, and constructs a high-precision wake flow field physical model based on actuator disk theory, Navier-Stokes equations, and a weighted quadratic wake superposition model. Secondly, it builds a physical information dual neural network (PIDNN) with dual encoders, integrating physical equation loss and data loss to train the model, achieving rapid and accurate prediction of wake wind speed. Then, it uses the snake optimization algorithm (SO) to optimize the environmental evolution factor, completing an efficient search for turbine layout. Finally, it constructs a PIDNN-SO collaborative optimization framework, trains a PIDNN surrogate model through initial sampling, and outputs the optimal layout that maximizes annual power generation. This invention can effectively reduce wake loss and significantly improve the power generation efficiency of offshore wind farms.

This invention provides a method for detecting anomalies in low-voltage residential photovoltaic (PV) power generation. The method includes acquiring low-voltage PV power generation user profile information and identifying user data for each user; calculating the electricity consumption data for each user based on their user data; establishing preliminary anomaly screening rules correlated with daily power generation and installed capacity; and filtering all PV users in the low-voltage PV user profile information by combining their user data and corresponding electricity consumption data to obtain PV users that meet the preliminary anomaly screening rules; and using a support vector machine (SVM) algorithm to perform cluster analysis on the PV users that meet the preliminary anomaly screening rules to further select anomalous PV users. This invention also provides a low-voltage residential PV power generation anomaly detection system. Implementing this invention overcomes the problems of complex operation, low efficiency, and low accuracy in existing low-voltage residential PV power generation anomaly detection methods.

This invention relates to the field of thermal power generation cost accounting technology, and proposes a dynamic modeling method and system for the cost per kilowatt-hour based on the forward and reverse balance method. The method includes: real-time acquisition of data on instantaneous flow rate of the coal feeder, coal pile volume, density, coal analysis upon entering the furnace, unit operation, and fuel price; calculation of dynamic coal quality data using a multimodal fusion algorithm; calculation of forward fuel cost based on flow rate, coal quality, and price data; calculation of reverse balance theoretical cost by inferring the theoretical standard coal quantity based on unit operation data; comparison and verification of forward and reverse costs to determine the final fuel cost; and calculation of dynamic cost per kilowatt-hour by combining variable cost and power generation data. This invention achieves a nonlinear dynamic mapping from multi-dimensional real-time data to accurate cost per kilowatt-hour, enabling high-precision, real-time, and automated dynamic modeling of the cost per kilowatt-hour for thermal power generation enterprises.

The invention relates to the technical field of building energy saving and intelligent control, and discloses a tropical zero-carbon building operation capacity and energy consumption coupling mechanism and an intelligent regulation and control method, and the method comprises the following steps: S1, building related data collection and preprocessing; s2, constructing a photovoltaic power generation quantity model, constructing an air conditioner refrigeration load and electric power quantification model, and constructing other electric load prediction models; s3, constructing a photovoltaic-air conditioning refrigeration-other electrical load coupling mechanism model; s4, constructing a multi-objective optimization model; and S5, rolling time domain intelligent regulation and control. According to the tropical zero-carbon building operation capacity and energy consumption coupling mechanism and the intelligent regulation and control method, on the premise that only the refrigeration working condition is considered, the photovoltaic power generation power, the air conditioner refrigeration electric power and other electric loads are uniformly incorporated into an electric energy balance equation; the quantitative relation between the power boundary and the power grid electricity purchasing power is clearly described through the power boundary and the power fluctuation penalty term, and a coupling mechanism model which can be directly used for engineering design and simulation is formed.

This invention belongs to the field of coal procurement technology, and relates to a procurement decision-making method and system based on multi-timescale coal demand forecasting. It includes: acquiring power generation influencing factor data at at least two time scales, and generating power generation forecast values ​​corresponding to each time scale based on the power generation influencing factor data; fusing the power generation forecast values ​​at each time scale to obtain a fused power generation forecast value; decomposing the fused power generation forecast value into initial demand quantities for different coal types according to the consumption rate of each generating unit for different coal types, and adjusting the initial demand quantities according to a preset blending strategy to obtain the target demand quantity for each coal type; acquiring coal price time series data for each coal type, and generating future coal price forecast values ​​for each coal type based on the coal price time series data; and determining a procurement decision scheme based on the target demand quantity for each coal type and the coal price forecast value. This invention achieves accurate decision-making and cost control in fuel procurement.

The present application belongs to the field of electric power engineering, and particularly relates to a new energy engineering conductor heat loss estimation method and a conductor cross section selection method, comprising obtaining power generation information of an existing new energy power station, and obtaining initial expected power of a newly built new energy power station through new energy power station output simulation simulation; according to the power generation information and the initial expected power, obtaining conductor heat loss information of the newly built new energy power station during operation under a plurality of conductor cross-sectional areas, to complete the estimation of the conductor annual average heat loss power of the newly built new energy power station during operation under a plurality of conductor cross-sectional areas; the technical problem that the existing power station conductor heat loss estimation method does not consider the actual output characteristics of the new energy project, it is difficult to accurately estimate the conductor heat loss of the new energy project, and it is difficult to accurately obtain the economic cross section of the new energy project.

The invention belongs to the field of oil field well site energy supply, and discloses a gravity and electrochemistry hybrid energy storage oil well micro-grid system and an energy supply method. The system comprises a clean energy power generation device, an energy storage device, a production load, a power distribution device and an energy management device. Wherein the energy storage device comprises gravity energy storage equipment and electrochemical energy storage equipment, and the gravity energy storage equipment is formed by transforming an idle well in a well site. According to the system, the super-generating capacity of wind and light power generation is converted into potential energy to be stored in the gravity energy storage equipment, the gravity energy storage equipment can serve as a long-time energy storage device, when wind and light output is insufficient and the electrochemical energy storage equipment is insufficient in energy supply, the potential energy of the gravity energy storage equipment can be converted into electric energy to supply power to a load, and the energy utilization rate is increased; and the energy supply stability of the system is enhanced. In addition, the gravity energy storage device is formed by transforming an idle well in a well site, and is economical and environmentally friendly.

This system enables energy management that automatically creates an economically efficient operating schedule for energy storage devices, taking into account electricity procurement costs. [Solution] Customer 5 is equipped with an electrical load 25, a solar power generation device 50, and energy storage devices 20, 30, and is capable of buying and selling electricity to and from the power grid 3. Server 10 creates an operation schedule for the energy storage devices 30, 40 for the next day based on the power procurement unit price for each of several time slots that divide the next day's 24 hours, the predicted power generation amount by the solar cells 50 and the predicted power consumption amount of customer 5 for each of the multiple time slots, and the comparison and determination result of the power procurement unit price and determination threshold in the time slot group that includes the default operating candidate period for the energy storage devices 30, 40 among the multiple time slots. HEMS 20 generates operation commands for the energy storage devices 30, 40 according to the operation schedule created by Server 10.

This invention relates to the field of clean energy power generation technology, and proposes a three-source coupled synergistic power generation device based on hydropower, gravity, and kinetic energy. The device includes a water storage tank, a wheel, an upper water tank, an upper water baffle, a closed-loop water tank pump system, a main shaft, counterweight grooves, counterweight blocks, high-pressure spherical bearings, buffer springs, and a dual-start transmission power generation assembly. The wheel diameter is unlimited and can be arbitrarily enlarged according to actual power demand. The wheel size is directly proportional to the output torque and power generation. The upper water tank is circularly arranged on the wheel. The closed-loop water tank pump system is installed on the upper side of the water storage tank. Multiple counterweight grooves are arranged in a circular array on both sides of the top water tank of the wheel. Multiple high-pressure spherical bearings are respectively installed at the bottom of each counterweight block. Multiple buffer springs are symmetrically installed on the upper and lower sides of each counterweight groove. This technical solution solves the problems of limited power output, single starting method, low energy conversion efficiency, and inability to operate with zero carbon emissions in traditional power generation equipment.

A method for configuring a wind-solar system is provided. The wind-solar system includes: wind turbines, photovoltaic (PV) modules, and shared electrical equipment and infrastructure. The power limit of the wind-solar system is one of the full-power output of the wind turbines and the full-power output of the PV modules. The electrical equipment operates under the power limit. The configuration method includes: predicting the time-period power generation under the power limit and installed capacity configuration ratio based on resource data of the wind-solar system; determining the power generation revenue of the wind-solar system based on the time-period power generation and the time-period electricity price; determining expenditure cost data based on the installed capacity configuration ratio, electrical equipment, and infrastructure; determining evaluation indicators based on the time-period power generation, time-period electricity price, power generation revenue, and expenditure cost data; and adjusting the installed capacity configuration ratio based on the evaluation indicators to obtain an optimized installed capacity configuration ratio.

The invention discloses a self-driven bridge deformation monitoring system and method based on vibration energy collection, the monitoring system comprises a power supply, a control circuit board, a cloud platform database and an upper computer, the power supply is connected with the control circuit board, and the power supply provides electric energy for the control circuit board; the detection method comprises the following steps: 1, calculating the generating capacity of the generator and the bridge displacement through a formula; 2, machine learning is adopted; 3, constructing a cloud platform database and developing an upper computer; and 4, by taking the displacement and voltage corresponding model obtained in the step 2 as a basis, laying a hardware system on key parts of the midspan of the bridge and the top of the pier. The device has the advantages that the device is adaptive to the low-power-consumption requirement of long-term outdoor monitoring of the bridge, the power supply maintenance cost is reduced, tiny vibration and deformation of the bridge can be accurately captured, the positioning precision reaches + / -0.5 m, the operation and maintenance efficiency is high, and the device is adaptive to the large-scale monitoring requirement of bridges with different spans.

A federated learning framework including household agents configured to continuously learn model parameters for managing charging periods and discharging periods of household batteries, and microgrid agents to maximize use of local energy based on a pricing policy, including accessing power from other microgrids when there is insufficient local energy to cover local demand. and selling surplus energy to the other microgrids when power generation by the microgrid surpasses the local demand. Each household machine learning agent is configured to control household energy demand from and supply to a microgrid which they are connected in order to minimize household energy cost while adapting to changes in the energy price that is determined based on the pricing policy of the microgrid agent that encourages reduction of carbon emission. A federated learning engine combines the model parameters from the household machine learning agents to update a global household machine learning agent.

According to some embodiments, an energy analysis device comprises: a processor; and a memory configured to store instructions that, when executed by the processor, cause the processor to: generate weather interpolation data for a region of interest by performing data interpolation on the basis of observation values of weather observation data for the region of interest to which a renewable energy power plant belongs; generate a power generation amount estimation function on the basis of the weather interpolation data and past power generation amount data of the renewable energy power plant; and estimate an expected power generation amount of the renewable energy power plant on the basis of weather forecast data for the region of interest and the power generation amount estimation function.

The invention provides a method and a device for absorbing photovoltaic abandoned electricity by utilizing heat storage of a deaerator. According to the method, the photovoltaic power abandoning rate can be effectively reduced, local consumption of the photovoltaic super-generating capacity in the low-load period of the power plant is achieved, waste of clean energy is avoided, meanwhile, heat storage adjustment is achieved through transformation of an existing deaerator, the consumption cost is remarkably reduced, and the operation stability of the system is guaranteed.

The utility model provides a temperature difference change generator, which comprises a main body and a water inlet II, the right side of the upper end of the main body is provided with a water inlet I and a water inlet II, the water inlet I and the water inlet II have the same specification, and the outer side of the main body is provided with a group of frames for limiting the position of the main body. Compared with the prior art, the thermoelectric power generation device has the advantages that external water is led into the thermocouple and the condenser through the first water inlet and the second water inlet respectively, the two sets of water are heated and cooled, the temperature of the two sets of water is lowered, and the temperature of the two sets of water is lowered. The cold water is guided into the cold and hot temperature difference box I and the cold and hot temperature difference box II through a hot flow guide pipe and a cold water guide pipe, and temperature difference changes are generated in the cold and hot temperature difference box I and the cold and hot temperature difference box II, so that thermoelectric generators in the cold and hot temperature difference box I and the cold and hot temperature difference box II generate thermoelectric electromotive force of semiconductors and generate power; compared with single cold and hot temperature difference box power generation, power generation efficiency and power generation capacity can be effectively improved.

The invention relates to the technical field of photovoltaic power generation, in particular to a component-level energy-storage network-constructing converter system and an operation method thereof. According to the invention, the distributed energy storage units directly connected with the photovoltaic modules are arranged nearby the direct current side of the module-level energy storage networking conversion system, so that the energy response path is greatly shortened, the transmission loss is reduced, the wooden barrel effect is eliminated, and the overall efficiency and the generating capacity of the system are remarkably improved; secondly, a plurality of distributed energy storage units are connected in series to form at least one photovoltaic group string, a single-point fault is fundamentally avoided through a dispersed framework, global operation is not affected by local unit failure, and the system reliability is greatly enhanced; meanwhile, the small-capacity energy storage battery simplifies a battery management system, systematic safety risks such as thermal runaway and circulation are effectively restrained, and operation and maintenance cost and safety pressure are reduced; in addition, the modular design also endows the system with excellent flexibility and expandability, and is convenient to install and maintain and upgrade and reconstruct the existing power station.