134 results about "Renewable energy system" patented technology

The invention discloses a source network load storage real-time scheduling method for MADRL-GAN collaborative optimization, and the method comprises the steps: firstly constructing a carbon pollution collaborative optimization model, and converting the model into a solvable convex problem through function linearization and mixed integer conversion; further mapping the model into a multi-agent reinforcement learning model, dividing agents according to an electrical coupling degree, and designing a state and action space containing a dual-Critic reward mechanism; thirdly, learning system uncertainty distribution by using a generative adversarial network, generating diversified scenes to train a reinforcement learning model, and obtaining a preliminary strategy; and finally, correcting the strategy through the generative adversarial network, generating a final scheduling action through a strategy mixing mechanism, and realizing distributed real-time optimal scheduling. According to the method, the problems of multi-target collaboration, high-uncertainty scheduling and real-time distributed decision making in a high-proportion renewable energy system are effectively solved.

The invention discloses a multi-energy power system optimization scheduling method based on improved robust optimization, and relates to the technical field of power system scheduling. Minimizing the total operation cost of the power system as a total objective function; establishing constraint conditions for the total target, wherein the constraint conditions comprise thermal power generating unit constraint, renewable energy system constraint and energy storage system constraint; establishing a robust optimization scheduling model according to the total objective function and each constraint condition, and processing robust optimization by adopting a Benders decomposition method to obtain a decision variable meeting the objective function; and adjusting a scheduling plan according to the decision variable to realize optimal scheduling of the power system. Introducing a constraint condition of multi-energy overall balance; an adjustment factor is introduced to control the balance between robustness and economy, the uncertainty influence of wind power photovoltaic fluctuation is dynamically controlled through an uncertainty influence factor, Benders are introduced, a large-scale problem is decomposed into a main problem and a sub-problem, the calculation complexity is reduced while efficient solving is achieved, and the method is suitable for large-scale real-time scheduling.

The invention discloses a photovoltaic module early-stage fault early-warning method based on electric-thermal characteristic joint analysis, and belongs to the field of photovoltaic module early-stage fault early-warning, and the method comprises the steps: segmenting an irregular high-temperature or low-temperature region according to a temperature distribution image through employing a data segmentation algorithm, and extracting the boundary contour and area quantification characteristics of the abnormal region; performing joint feature vector construction by using the abnormal region boundary contour and area quantization feature and the current and voltage fluctuation amplitude in the electrical signal time sequence to obtain the comprehensive fault diagnosis vector; according to the preliminary fault classification label, extracting a temperature electrical corresponding association mode of a similar fault case from a historical fault diagnosis database, and obtaining an enhanced fault corresponding relation model; and generating a system risk assessment report by adopting the final fault diagnosis classification result, triggering a corresponding alarm mechanism, and judging the overall risk level of the renewable energy system.

The invention relates to the technical field of nuclear energy comprehensive utilization, and discloses an energy system with nuclear energy as base load and a control method.The system comprises a nuclear power secondary loop system, a renewable energy system, an energy storage system, a steam supply system, a seawater desalination system, a hydrogen production system, a heating system and a refrigeration system; the heat of the reactor core enters the steam generator to generate main steam; the photovoltaic module and the wind turbine generator set carry out renewable energy power generation; a storage battery is used for storing renewable energy electric power, and a molten salt heat storage system is used for storing heat energy; the steam supply heat exchanger is used for heating fresh water produced by the seawater desalination system to obtain superheated steam; the low-temperature multi-effect evaporation system and the reverse osmosis membrane method seawater desalination system generate fresh water; the electrolytic bath generates hydrogen and oxygen; the heating system and the refrigerating system are used for refrigerating in summer and heating in winter, and nuclear energy, wind energy, solar energy and the like are coupled and utilized in a stepped mode.

A method of adjusting energy delivered by a renewable energy system to an electrical grid and an energy-consuming load is disclosed. The method may comprise determining a production schedule of a renewable energy system (RES) and establishing a prioritization order between the electrical grid and the energy-consuming load. The method may further comprise setting a power receiving threshold for the electrical grid or the energy-consuming load based on the prioritization order, and adjusting the energy delivered by the RES by controlling a first amount of energy delivered to the electrical grid and a second amount of energy delivered to the energy-consuming load. A variability schedule of at least one of the first amount of energy or the second amount of energy can be amplified or dampened over a time period relative to the natural variability energy production schedule of the RES.

A load frequency controller for the integration of a thermal power generator with renewable energy generators includes first and second power systems situated in separate geographic regions, interconnected through an inter-area tie-line. Each power system incorporates a 3DOF-FOPIDN controller, programmed with a salp swarm algorithm to adjust the controller gain parameters. A model predictive controller (MPC) slaved to the 3DOF-FOPIDN controller generates droop correction values then transmitted to the energy generators. The power deviations from the resources, the tie-line power deviations and a load center power deviation are combined to generate a combined power deviation signal. A frequency generator converts the combined power deviation signal to a frequency deviation value for each area. Feedback loops channel the frequency deviation value to bias factor generator in each area. An ACE signal is generated, which is utilized by the 3DOF-FOPIDN-MPC controller to modulate frequency and maintain grid stability.

The invention discloses an operation state prediction method and device of a building new energy system, and the method comprises the steps: obtaining various monitoring variables of a target building, inputting the various monitoring variables of the target building into a trained prediction model, and obtaining the prediction results of the various monitoring variables of the target building in a set prediction time range; based on the prediction result, evaluating the operation state of the target building: firstly calculating a basic threshold value, and then determining a dynamic threshold value according to the basic threshold value, an equipment aging factor and a seasonal factor; the prediction result is compared with a dynamic threshold value, and if the prediction result is smaller than or equal to the dynamic threshold value, the operation state of the building new energy system is a normal state; and if the prediction result is greater than the dynamic threshold value, indicating that the operation state of the building new energy system deviates from the normal interval and the building new energy system has an abnormal phenomenon.

The invention discloses a method and a system for evaluating internal dynamic complementary characteristics of a multi-energy complementary power system. The method comprises the following steps: S1, acquiring an actual output time sequence of each unit; defining a fluctuation energy unit total output sequence, an adjustment energy unit total output sequence and a system total output sequence; s2, basic quantitative indexes of the random fluctuation dimension, the climbing trend dimension and the energy time shift dimension are calculated respectively; s3, calculating a random fluctuation compensation index, a climbing compensation index and an energy time shift index; s4, a comprehensive evaluation index MIRCI is calculated; s5, calculating an adjustment capability utilization factor RUF of each adjustment unit; and S6, based on MIRCI and RUF, performing complementary effect diagnosis. According to the method, the overall stabilizing effect of the adjusting resources on the fluctuating energy is effectively quantified, diagnosis of the complementary effect and limiting factor positioning are achieved, and the absorption capacity and the operation efficiency of the high-proportion renewable energy system are remarkably improved.

A renewable energy production system includes a plurality of solar panels and a torque tube. The torque tube has an exterior shape defined by an arcuate surface and a flat surface connected to the arcuate surface. The plurality of solar panels are coupled to the flat surface. A plurality of support columns is used to support the torque tube.

An intelligent catalyst discovery and electrolysis optimization system for the production of green hydrogen, consisting of: • a schematic water electrolysis unit configured to simulate the electrolytic splitting of water into hydrogen and oxygen by modeling the hydrogen evolution reaction (HER) at a cathode and the oxygen evolution reaction (OER) at an anode and enabling analysis of catalyst effectiveness in reducing energy input; • a catalyst structure analysis unit configured to visualise and simulate atomic and molecular structures of candidate catalyst materials, including base metals, transition metal-based nanostructures and two-dimensional materials, and to evaluate charge distribution, surface morphology and active site behaviour; • a computational modeling and simulation unit using density functional theory (DFT) for quantum simulations to evaluate the thermodynamic stability, electronic structure, reaction energetics and adsorption energy of potential catalysts; • a machine learning optimization module trained on simulated and experimental data, using supervised and unsupervised learning models to determine optimal catalyst descriptors and predict catalytic activity, stability, and durability; • an experimental validation and test interface comprising electrochemical test environments including three-electrode cells and electrolyzers for performance benchmarking under realistic electrolysis conditions and capable of logging overvoltage, efficiency and degradation behavior; • an energy integration unit configured to interface with renewable energy systems, including photovoltaic systems, to dynamically power the electrolysis process and manage energy consumption through a power management subsystem; • a data processing and control interface to manage cross-system communication between simulation, experimental, and machine learning modules, enabling real-time parameter tuning and visualization of system diagnostics; and • a secure storage and logging unit adapted for storing simulation data, machine learning training sets and experimental results, with features for offline retrieval and integration with cloud platforms for collaborative research.

The invention discloses a water-wind-light hybrid energy system optimization capacity configuration method and equipment considering resource space-time heterogeneity, and relates to the field of hybrid renewable energy system planning and optimization. According to the method, fine modeling is carried out on inherent high-dimensional space-time heterogeneity and related planning uncertainty of water, wind and light resources, meanwhile, high-fidelity water and electricity simulation is integrated, and therefore optimal configuration of the whole system is achieved. According to the method, firstly, a high-dimensional problem is simplified through a strategy of clustering first and then decomposition; and diversified climate scenes are generated in combination with a conditional variation auto-encoder and Latin hypercube sampling, and rare events are covered to enhance robustness. Results show that through fine consideration of spatial-temporal heterogeneity and uncertainty, remarkable and quantifiable economic and reliable double benefits can be brought.

The present disclosure provides systems and methods for managing electrical energy generated by a renewable microgrid. One or more processors of a system may store priorities for one or more consumer loads; forecast an amount of available electrical energy for a time period; allocate a first electrical energy amount to a first consumer load to a first energy limit for the time period; determine more electrical energy is forecast to be available from the RES or the ESS for the time period; identify a second consumer load of the one or more consumer loads; allocate a second electrical energy amount to the second consumer load for the time period; and direct electrical energy from the RES or the ESS to the first and second consumer loads according to the allocations.

The invention relates to the development of low-cost functionalised copper (II) hydroxide (f-Cu(OH)2) electrodes for energy storage technologies and electrochemical devices. By means of surface functionalisation using high-energy X-rays, the energy storage capacity of the material is increased and an environmentally friendly production process is provided. The electrodes produced by this method can be used in applications such as supercapacitors, portable electronic devices, and renewable energy systems.

The invention discloses a renewable energy coupling hydrogen production control method and system based on a virtual synchronous machine. The control method comprises the steps that a virtual synchronous machine controller obtains renewable energy power generation system parameters; setting a given value of a virtual synchronous machine controller; establishing a power distribution strategy of the ALK hydrogen production system, the PEM hydrogen production system and the electric energy storage device BMS system according to the output active power condition of the renewable energy power generation system; constructing a virtual synchronous machine model of the renewable energy coupling hydrogen production system according to the obtained parameters, and associating the current condition of the coupling hydrogen production system according to the model; output parameters of the virtual synchronous machine model are sent to a grid-side converter, and a switching signal required by a switching tube is generated; and distributing the given output of the power distribution strategy to the corresponding system through the grid-side converter. The problems that an existing system is not high in integration degree, electric power splicing of a renewable energy system and a hydrogen production system is singly considered, and the renewable energy fluctuation stabilizing capacity is limited are solved.

The invention discloses a virtual power plant collaborative optimization scheduling method and system based on multi-time scale prediction, and relates to the technical field of virtual power plant collaborative optimization scheduling, and the method comprises the steps: obtaining multi-dimensional operation data of a virtual power plant scheduling object; the scheduling object comprises a distributed renewable energy system, an energy storage system and a controllable load system; performing medium and long term and short term multi-time scale prediction according to the acquired data; performing preliminary scheduling planning on the basis of medium and long term prediction results, and generating a short-term optimization scheduling plan in a rolling manner by taking the preliminary planning result as a constraint and utilizing a short-term rolling optimization model introducing a reinforcement learning algorithm to continuously adjust the weight of an objective function of the optimization model according to the short-term prediction data; and taking the short-term optimization scheduling plan as a reference, performing calculation by using a real-time control model based on measured data, and issuing a real-time control instruction to each scheduling object. According to the invention, adaptive optimization scheduling of the virtual power plant can be realized, and comprehensive benefits are guaranteed.

The invention discloses a new energy station and distributed pumped storage power station coordinated optimization method and system, and the method comprises the steps: firstly constructing an output power time sequence model of wind power generation and photovoltaic power generation, and predicting the output power at different moments; secondly, the fluctuation rate of the new energy station yard is calculated according to the output power, and the wind and light capacity ratio is optimized to reduce fluctuation; a distributed pumped storage power station output model is constructed based on hydrological conditions; and finally, combining the output model of the pumped storage power station with the optimized wind and light capacity ratio, constructing a multi-objective optimization function, and outputting the optimal capacity ratio of the new energy station yard to the pumped storage power station. According to the method, the wind and light output time sequence characteristics of the new energy station and the operation constraint of the distributed pumped storage power station are combined, a multi-objective optimization function with the total cost minimization and new energy consumption maximization as objectives is constructed, new energy and energy storage collaborative optimization is achieved through calculation, decision support is provided for planning of a high-proportion renewable energy system, and the method is suitable for large-scale popularization and application. And investment and decision risks are reduced.

The application relates to a kind of digital power energy storage system dynamic network reconfiguration methods in the technical field of power energy storage, S1. Build energy storage system;It is composed of intelligent layer, control layer and data layer;S2. Energy storage network modeling;Adopt graph capsule neural network to learn the optimal control strategy of energy storage network;S3. Dynamic network reconfiguration;Based on Markov decision process, generate fault emergency response model;By systematic optimization of the topological structure and optimal control strategy of energy storage network, the quick isolation of fault area is realized, and the dynamic adjustment and reconfiguration of the working mode of energy storage equipment and load equipment are realized, to ensure that the energy storage network can still operate stably under fault situation, improve the flexibility and elasticity (fault tolerance) of energy storage system in dynamic environment;By reducing the energy loss in the transmission process, balancing network load and preventing local failure, the technical problems existing in the prior art are solved, and the sustainable development of new renewable energy system is promoted.

The application belongs to the field of green building and building construction technology, and specifically discloses a green low-carbon building civil engineering integrated efficient construction building method. In view of the problems of design construction disconnection, multi-specialty cross conflict, high carbon emission and serious resource waste in traditional building civil engineering construction, the application constructs a 'cooperative design-factory prefabrication-assembly construction-low-carbon operation and maintenance' integrated system, and the method comprises the following steps: multi-specialty cooperative deepening design and carbon emission calculation based on BIM; factory prefabrication of low-carbon concrete components and integration of thermal insulation structure exterior wall; on-site assembly type construction and dry method connection; renewable energy system and photovoltaic building integrated synchronous installation; and whole life cycle carbon footprint monitoring and closed loop optimization. The application realizes the synchronous construction of the envelope structure and the main structure by driving the deep integration of industrialized production and assembly type construction through digital design, so that the construction period can be shortened, the whole life cycle carbon emission of the building can be reduced, and the civil engineering integrated green construction is realized.

Disclosed is a battery aging assessment method based on multi-source and multi-scale high-dimensional state space modeling in the field of energy storage in renewable power systems. The method includes: acquiring a time series of each discharge process within a preset number of discharge cycles of a sample battery; determining a first state transition path and a second state transition path based on discharge parameters corresponding to the time series; establishing a benchmark working-state transition path; calculating multiple sample distances between the second state transition path and the benchmark working-state transition path; training a battery aging assessment model using the sample distances as input and corresponding target state-of-health values as output; calculating a target distance between a state transition path of a to-be-predicted target battery and the benchmark working-state transition path.

The present invention relates to an electrodynamically synchronized DC-to-AC inverter / converter system (100) that generates a near-sinusoidal output with minimal reliance on high-frequency power electronic switching. A motor-driven cyclic connector (114) sequentially connects multiple voltage stages from a battery or capacitor bank (104), forming a stepped waveform that is smoothed by a reactor (140). In standalone mode, a DC shunt motor (112DM) provides the necessary rotation; for grid-tied operations, a synchronous motor (112SM) automatically locks the output to the grid frequency. The high- current flow bypasses the motor windings, reducing switching losses, electromagnetic interference, and complex gating circuits. Protective devices (116) isolate fault conditions, while optional transformers (130) enable voltage stepping or galvanic isolation. By avoiding high-frequency gating, the invention offers robust, efficient performance for renewable energy systems and other power electronics applications. Simplicity and scalability make it ideal for industrial applications.

The invention relates to the technical field of carbon emission accounting, and provides a carbon emission accounting method for a high-speed rail passenger station, and the method comprises the steps: determining the building information of a to-be-accounting high-speed rail passenger station and the accounting boundary information of carbon emission; based on the building information and the accounting boundary information of the carbon emission, determining a carbon emission source list of the to-be-accounting high-speed rail passenger station; based on the carbon emission source list, the carbon emission generated by using energy, treating generated waste, operating vertical transportation equipment, providing hot water, using a communication system, maintaining the passenger station, using a cooling system, heating and refrigerating, using a standby power supply, operating a lighting system and the like in the unit operation time of the high-speed rail passenger station to be checked is determined. The carbon emission reduction amount of the operation renewable energy system and the carbon sequestration amount of the operation carbon absorption system; and based on each carbon emission amount, carbon emission reduction amount and carbon sequestration amount, determining the total carbon emission amount of the to-be-checked high-speed rail passenger station in the unit operation time. According to the invention, carbon emission accounting can be accurately carried out on the high-speed rail passenger station.

A method for estimating the state of health (SOH) of a supercapacitor system, which obtains a number of discharge segment data and a number of charging segment data based on the historical charge and discharge data of the supercapacitor system under actual operating conditions; obtains the SOH label of the supercapacitor system in different historical preset time periods based on each discharge segment data; obtains the power characteristics and module voltage characteristics of the supercapacitor system in different historical preset time periods based on each charging segment data, as health characteristics of different historical preset time periods; trains an estimation model based on the health characteristics and SOH labels of different historical preset time periods to obtain an SOH estimation model of the supercapacitor system; and uses the SOH estimation model to estimate the health state of the supercapacitor system. This application can accurately estimate the health state of the supercapacitor system in the actual operation of the electrified transportation system carrier and the renewable energy system, and improve the safety and economic benefits of the operation of the electrified transportation system carrier and the renewable energy system.

The invention belongs to the technical field of power systems, and discloses a hybrid renewable energy system, a control method and a charging system.The hybrid renewable energy system comprises a bidirectional Zeta converter, an inverter, a photovoltaic power source and a wind power source; the bidirectional Zeta converter comprises a first switch tube, a second switch tube, a first capacitor, a second capacitor, a third capacitor, a filter capacitor, a first inductor, a second inductor and a diode. The inverter comprises an inverter first switch tube, an inverter second switch tube, an inverter third switch tube, an inverter fourth switch tube, an inverter fifth switch tube and an inverter sixth switch tube; the source electrode of the fifth switch tube of the inverter is connected with the drain electrode of the sixth switch tube of the inverter; and the inverter is connected with a power grid. According to the invention, the efficiency of the photovoltaic system is obviously improved, so that photovoltaic and wind power generation systems are integrated into a power grid, and continuous and reliable power supply is provided for charging of the electric vehicle.

1. The name of this design product: Silicon carbide power module. 2. Application of this design product: Used for power conversion and drive control in power electronic equipment such as electric vehicles, renewable energy systems, industrial motor drives, power supplies, and data centers. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

A platform arranged to support a renewable energy system, the platform comprising a central structure (103), wherein the central structure comprises at least three pivot connections (104); and at least three radial arms (102), each radial arm configured to be pivotably connected to a respective pivot connection of the central structure such that each of the at least three radial arms are configured to pivot between a folded configuration and an unfolded configuration.

The invention relates to a wind-light-heat storage system collaborative operation optimization method and device based on data driving, and the method comprises the steps: 1, building a historical database, collecting the historical data of a wind-light-heat storage system, and carrying out the preprocessing of the collected data, and obtaining a standardized data set; the wind-solar heat storage system is a multi-modular hybrid energy power generation system; step 2, based on historical data, establishing a photovoltaic output prediction model, a wind power output prediction model and a load power consumption prediction model by using a deep learning method; and step 3, based on prediction results of the photovoltaic output prediction model, the wind power output prediction model and the load power consumption prediction model, dynamically optimizing a system operation strategy through an optimization model. The method can achieve the precise matching of the system output and the load demand, is suitable for a hybrid scheduling mechanism of a large-scale centralized renewable energy system, and improves the overall reliability of the system.

This invention discloses a frequency security planning method for grid-based energy storage in high-proportion renewable energy systems. The method includes: acquiring basic data of the high-proportion renewable energy system; establishing an equivalent model of frequency dynamic response by quantifying the coupling relationship of relevant parameters and constructing frequency security constraints; then establishing a medium-to-long-term time-series operation simulation energy storage planning model with the goal of minimizing the total life cycle cost; and finally solving the time-series segmented problem to obtain the result and regulate the system. This invention proposes a frequency security planning method for grid-based energy storage in high-proportion renewable energy systems. By quantifying the coupling relationship between grid-based energy storage parameters and system frequency dynamics, embedding multi-dimensional frequency security constraints, and integrating them into a medium-to-long-term time-series planning model, it can solve the problem that in the medium-to-long-term time-series operation planning of energy storage in high-proportion renewable energy systems, the lack of quantification of the coupling relationship between grid-based energy storage parameters and system frequency dynamics, and the absence of embedded frequency security constraints, makes it difficult to ensure system frequency security.

The application discloses a photovoltaic energy-saving curtain wall based on a renewable energy system and belongs to the technical field of photovoltaic energy-saving curtain walls, which comprises a longitudinal beam assembly installed on a building outer wall, a cross beam assembly vertically installed on the longitudinal beam assembly, and a positioning frame sealingly installed between the longitudinal beam assembly and the cross beam assembly; a folding photovoltaic power generation module is used to convert renewable solar energy into electric energy; the folding photovoltaic power generation module comprises a fixed strip plate fixedly installed in the center of the positioning frame, two groups of movable strip plates symmetrically installed in the positioning frame relative to the fixed strip plate, and two groups of photovoltaic plates arranged between the movable strip plates and the positioning frame and rotationally connected with each other; the photovoltaic energy-saving curtain wall can control the rotation and folding of the multiple groups of photovoltaic plates according to the needs of building ventilation, illumination and light energy conversion, and can synchronously drive the longitudinal movement of a cleaning flow guide module during the operation process, so that the surface of the photovoltaic plate can be automatically cleaned.

This invention introduces a novel energy conversion system and method that synergistically combines the electrohydraulic and piezoelectric effects to enhance electricity generation efficiency. By leveraging the overunity energy potential of cavitation, the system achieves exceptionally high energy efficiency for producing electrical energy. It features a hermetically sealed container filled with a pressurized dielectric liquid, electrodes connected to a high-voltage power source to induce cavitation, and a geometric shape incorporating piezoelectric material to directly convert energy from pressure shock waves into electricity. This approach uniquely exploits cavitation dynamics to generate sustainable and efficient electrical power, offering a scalable solution adaptable to various applications. The invention has the potential to revolutionize renewable energy systems by providing a cleaner and highly efficient source of electricity.