2353 results about "Solar power" patented technology

The present application relates to the technical field of power plant optimization, and discloses a thermal power plant auxiliary power system optimized dispatching method and system considering a wind-solar-storage system, and a device and a storage medium. The method specifically comprises: collecting thermal power plant auxiliary power system data, and establishing an auxiliary power system multi-objective function on the basis of the thermal power plant auxiliary power system data and a wind-solar power generation cluster model in an auxiliary power system; introducing constraint penalties and constraint conditions to the auxiliary power system multi-objective function, and constructing a thermal power plant auxiliary power system optimized dispatching model; and processing the thermal power plant auxiliary power system optimized dispatching model by using a dynamic learning factor-based particle swarm algorithm to obtain an optimized dispatching result, and completing thermal power plant auxiliary power system optimized dispatching on the basis of the optimized dispatching result. According to the present application, the optimal interactive output among wind turbine units, photovoltaic units, energy storage units, and a generating set can be determined on the basis of the optimized dispatching result, auxiliary power system low-carbon optimized dispatching is implemented, and the problem in the prior art of lacking dispatching in which new energy and thermal power plant auxiliary loads are integrated for analysis is solved.

The invention discloses a virtual power plant intelligent regulation and control method and system based on artificial intelligence, and belongs to the technical field of electric power system intelligent regulation and control, and the virtual power plant intelligent regulation and control method based on artificial intelligence comprises the following steps: S1, aggregating equipment side data, desensitizing to generate topological codes, and constructing time scale matrix synchronization; s2, constructing a dynamic model by equipment parameters, and mapping real-time data to output a difference map; s3, adding equipment constraints, building a multi-objective function, optimizing a strategy and performing correlation analysis; s4, a wind and light fluctuation overrun trigger RL strategy and an abnormal switching base line generate a mixed instruction; s5, locally verifying the instruction, and correcting and feeding back parameters if the prediction is out of limit; s6, generating a three-dimensional thermodynamic diagram, and displaying an association report and a historical record by AR; s7, aggregating the data to reconstruct the training set, locally fine-tuning the strategy network and performing incremental updating; the method has the beneficial effects that the regulation and control pain point of the virtual power plant is systematically solved, the operation and maintenance cost is reduced, the new energy consumption capability is improved, and the equipment out-of-limit risk is reduced.

The invention discloses a slope multi-modal monitoring and early warning system and method based on digital twinning, and relates to the technical field of slope monitoring, and the system comprises a data acquisition module, a data processing module, a digital twinning modeling module, a deformation prediction module, an early warning visualization module and a solar power supply module. According to the invention, slope multi-source monitoring data is obtained through the data acquisition module, and after the slope multi-source monitoring data is preprocessed by the data processing module, a slope digital twinborn model is constructed and calibrated by the digital twinborn modeling module; deformation prediction is realized by combining a space-time prediction model which contains a space correlation and time sequence analysis module and is optimized by multi-scale neighborhood aggregation, a DTW loss function and transfer learning, and a future-state digital twin is generated through an early warning visualization module and risks are visualized. And the solar power supply module is matched to ensure the operation of a scene without an external power supply and the flexible deployment of the assembly connection module, so that a multi-mode, high-precision and sustainable slope monitoring and early warning scheme is formed.

The invention discloses a fault diagnosis and remote monitoring system and method for a solar power supply system, and relates to the technical field of fault diagnosis of a solar system, and the system comprises a heterogeneous multi-mode sensing module which collects the multi-dimensional information of an assembly through a plurality of sensors; the memristor storage and calculation integrated unit is used for realizing data filtering and feature extraction; the multi-scale causal diagnosis engine is used for diagnosing faults by fusing deep learning and causal diagrams; a self-adaptive topology communication network ensures data transmission; a digital twinborn monitoring platform and visual operation and maintenance are adopted, and in addition, an intelligent evolution decision and self-reconfiguration sensor network module is further arranged, so that the intelligence and reliability of the system are improved. Through cooperation of multiple modules, accurate fault diagnosis and positioning are realized, the diagnosis time is shortened, stable data transmission is ensured, self-repairing and autonomous learning capabilities are provided, the operation and maintenance cost can be reduced, the power generation efficiency can be improved, and the reliability and economic benefits of a solar power supply system can be enhanced.

The invention relates to a power system scheduling method and device based on multi-modal data fusion. The method comprises the following steps: acquiring multi-modal data of a power system, wherein the multi-modal data comprises power grid topology data, meter information, wind and light energy output prediction data, maintenance plan text data and energy comprehensive data; performing feature extraction, space-time alignment processing and hierarchical attention learning on each modal data to obtain a fusion feature vector; training the scheduling model by using the fusion feature vector until a total loss function meets a preset condition, the total loss function comprising a power flow equation constraint term; the method comprises the following steps: acquiring real-time multi-modal data of a power system, and obtaining a real-time fusion feature vector through feature extraction, space-time alignment processing and hierarchical attention learning; and inputting the real-time fusion feature vector into the trained scheduling model to obtain a real-time scheduling decision, and scheduling the power system according to the real-time scheduling decision. The method can improve the dispatching precision of the power system.

The invention discloses a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, and relates to the technical field of energy storage charging. Comprising the following steps: S1, collecting wind-solar complementary energy storage data in real time, and carrying out data preprocessing; s2, converting wind-solar power generation into direct current, judging the flow direction of wind-solar power generation energy, and performing corresponding wind-solar power generation energy transmission power supply; s3, judging the limit of the output power of the charging pile, and controlling and adjusting the output of the charging pile in stages; s4, quantifying the liquid cooling flow required by heat dissipation, and performing heat source heat dissipation on the energy storage system and the charging pile; and S5, carrying out coordinated regulation and control, strategy optimization and multi-dimensional visualization on the flow direction of wind and light power generation energy, charging pile output and heat source heat dissipation. The problems that an existing charging station is difficult to deploy in remote and power transmission difficult areas, high-power charging heat dissipation and energy efficiency bottlenecks are prominent, and the efficiency of traditional air cooling and alternating current conversion is low, so that efficient, safe and green energy supplementation is difficult to achieve are solved.

The invention discloses a wind and light storage station power reporting and tracking method based on energy storage rapid power response. The method comprises the following steps: acquiring wind and light power probability prediction data, power grid real-time operation state data, station operation state data and power grid examination allowable power deviation data in a current scheduling period; generating a dynamic power reporting interval of the next scheduling period based on the wind-solar power probability prediction data, the power grid real-time operation state data, the station operation state data and the power grid examination allowable power deviation data; and based on the dynamic power reporting interval and the real-time operation data of the wind and light storage station, a flexible control strategy is adopted to control the charging and discharging behaviors of an energy storage system in the station. By generating the dynamic power reporting interval with self-adaptive change and adopting the flexible control strategy, the operation condition of the energy storage system can be obviously optimized, the fluctuation of the wind and light power can be effectively stabilized, and the economy and reliability of the operation of the station can be improved on the premise of ensuring that the wind and light storage station tracks the power grid assessment requirement.

The invention belongs to the technical field of intelligent traffic and new energy power supply, particularly relates to a traffic equipment solar power supply fault diagnosis system, and aims to solve the problems that a solar power supply system is not timely in fault diagnosis, low in precision and difficult to distinguish instantaneous interference and continuous faults. The system collects multi-source data through an environment sensing and electrical parameter monitoring module, generates a power deviation sequence and extracts time sequence characteristics by combining dynamic expected power modeling with actual output comparison; the fault identification module adopts a multi-level logic discrimination and 12-hour continuous verification mechanism, accurately identifies photovoltaic panel pollution, storage battery aging, poor line contact and controller faults, and distinguishes instantaneous interference; and the decision alarm module generates graded alarms according to fault types and grades, and realizes accurate positioning and operation and maintenance scheduling in linkage with geographic information. The system also has the functions of internal resistance pulse detection, dual-channel redundancy sampling, adaptive threshold adjustment and model self-learning, and the diagnosis accuracy and the operation and maintenance efficiency are significantly improved.

The invention, which relates to the technical field of energy management, discloses a multi-target collaborative optimization prediction system and method for regional-level water-wind-light power generation power, and the system comprises a data collection module which is used for obtaining power generation power data, meteorological environment data and power grid load demand data in real time; the optimization processor is used for receiving the data fed back by the data acquisition module, and constructing a multi-target optimization model based on spatial-temporal feature extraction to generate a plurality of candidate optimization paths; the screening module is used for screening the candidate paths through a dynamic weight distribution algorithm and screening out an optimal collaborative optimization path; and the dynamic feedback module is used for carrying out online correction on the optimal collaborative optimization path in the real-time optimization process according to the power grid frequency deviation, the energy storage charge state and the meteorological abrupt change signal. The optimization processor constructs the multi-target optimization model based on the spatial-temporal characteristics, generates a plurality of candidate optimization paths and screens out the optimal path, and compared with a traditional single energy prediction and simple scheduling mode, the precision of power generation power prediction is improved.

The invention discloses a water-wind-light combined intelligent control system based on multi-energy coordinated control, and belongs to the technical field of multi-energy coordinated control, and the system comprises the steps: firstly collecting environment and operation parameters of wind power, photovoltaic and hydroelectric equipment, and carrying out the preprocessing of the environment and operation parameters to form a structured data set with a space-time label and a dynamic sampling identifier; performing space-time correlation analysis on the data set, constructing a wind power fluctuation and hydropower regulation margin real-time response matrix and a photovoltaic output attenuation and hydropower storage capacity compensation time sequence correlation model, and quantifying the multi-energy dynamic complementation degree and grading the data credibility through a two-dimensional coupling algorithm; then combining with a historical meteorological scene association rule base, constructing a water-wind-light combined power supply capability prediction model containing an energy characteristic mutual compensation coefficient, and generating a hierarchical regulation and control strategy with a space-time priority; and finally, executing a regulation and control strategy to complete parameter adjustment, continuously monitoring through closed-loop feedback, and triggering multi-energy collaborative complementary regulation when the single energy regulation capability is saturated, thereby realizing water-wind-light efficient collaborative control.

A landing pad receives and stores packages delivered from an aerial vehicle or awaiting pickup from an aerial vehicle. The landing pad can be placed outside of a window and can contain a transmitter for sending out an identification signal via radio frequency to aid aerial vehicles in finding the landing pad. The landing pad contains a landing platform with a trapdoor that leads to a storage compartment. The trapdoor can be configured to only open when it receives a signal from an authorized aerial vehicle. The storage compartment can be accessed via a storage compartment door which can contain a locking mechanism. The storage compartment can be climate controlled. The landing pad can also have a transmitter that emits sounds to discourage animals from nesting on or near the landing pad. The landing pad can also include a solar power generator as a source of electrical energy.

The invention relates to the technical field of water electrolysis hydrogen production, and discloses an electrolytic bath outlet temperature control method and system, a medium and a program product, a flow control valve is arranged at an inlet of an electrolytic bath, the electrolyte input flow is converted into a core regulation variable directly influencing the outlet temperature, and active control over the outlet temperature is achieved. Furthermore, the flow control valve is directly connected with the control device, the opening degree signal can be received in real time, the flow can be adjusted, it is ensured that the temperature control instruction can be rapidly converted into the actual flow change, and the response speed to power fluctuation is increased. Furthermore, through a real-time operation state parameter set and a real-time temperature monitoring parameter set, it is ensured that a control signal is generated based on a real working condition, and the temperature control stability under fluctuating power is improved. Furthermore, through the synergistic effect of an electrolyte flow feedforward control signal and an electrolyte flow rear-end control signal, frequent current change caused by wind-solar power fluctuation can be effectively handled, and the fluctuation amplitude of the outlet temperature is reduced.

The invention discloses a monitoring device and a monitoring method for construction organization, belongs to the technical field of intelligent construction safety monitoring, and mainly solves the problems of monitoring blind areas, insufficient fixed visual angle coverage and difficulty in field long-term power supply caused by dynamic shelters in the construction process. According to the technical scheme, a camera is fixed to a double-shaft electric holder with a horizontal rotating and pitching adjusting mechanism, a processor, a communication unit and a battery are arranged in a base, a solar panel is arranged on the top of the base, and an electric lifting column is connected with the base and the holder; the environment sensor group is mounted on the camera; the solar panel is connected with the battery and supplies power to the whole device; the processor calculates a target monitoring path for eliminating a blind area in combination with a preset three-dimensional coordinate of a key area, generates a control signal to drive the holder and the lifting column to move, and dynamically adjusts the path execution frequency and the movement speed of each mechanism according to the electric quantity of a battery and the solar power. The device is mainly used for dynamic dead-corner-free safety monitoring of key areas of a building construction site.

The invention relates to the technical field of hydrogen load capacity configuration, in particular to a multi-scene hydrogen load comprehensive energy system double-layer capacity optimal configuration method, which comprises the following steps of: firstly, constructing a multi-scene model containing strong, weak, discontinuous and non-hydrogen loads based on the time sequence characteristics of hydrogen loads in an industrial park; then a comprehensive energy system mathematical model covering wind and light power generation, hydrogen energy conversion, multi-type energy storage and cogeneration units is established; then, constructing a double-layer capacity optimization configuration model of which the upper layer takes the whole life cycle cost minimization and the lower layer takes the operation cost minimization and the system stability optimization as targets; and finally, solving a Pareto leading edge by adopting a non-dominated sorting genetic algorithm with an elitist strategy, making a decision by utilizing an approximate ideal solution sorting method, and screening out a capacity configuration scheme with optimal comprehensive performance. The problem that a traditional configuration scheme is difficult to adapt to multi-scene hydrogen load fluctuation is effectively solved, and the economical efficiency, the stability and the renewable energy consumption capacity of the system are remarkably improved.

The invention relates to a mixed scale optimization regulation and control method and device for rural energy and a storage medium, and belongs to the technical field of new energy. According to the method, layered optimization is carried out by establishing a monthly time scale optimization scheduling model, a day-ahead time scale optimization scheduling model and an intra-day time scale optimization scheduling model which are connected with one another, and long-term economic planning and medium-short-term operation scheduling are organically combined, so that multi-target collaboration and multi-energy complementation are realized; specifically, through monthly optimization, an optimal purchase and inventory strategy can be formulated according to seasonal price fluctuation of biomass, the fuel cost is remarkably reduced from the source, and the overall economical efficiency of the system is improved; through a day-ahead gas storage plan and intra-day real-time scheduling, the fluctuation and intermittency of wind energy and solar energy power generation can be effectively stabilized by utilizing the stability and controllability of biomass power generation, and the power load demand can be stably met under various working conditions, so that the stability and reliability of power supply are enhanced, and the energy consumption is reduced. And on-site efficient consumption of rural renewable energy sources is promoted.

The invention provides an off-grid synthetic ammonia park electrolytic bath column level-energy storage-hydrogen storage collaborative optimization method based on rolling optimization, and relates to the technical field of energy storage and hydrogen storage collaboration. The method comprises the following steps: constructing an off-grid system architecture comprising wind-solar power generation, a plurality of rows of electrolytic cells, energy and hydrogen storage equipment and a synthesis ammonia device; a multi-device collaborative optimization strategy based on an eight-hour rolling time domain is designed, the system operation state is divided into high, medium and low working conditions through a working condition recognition mechanism, a current device operation scheme is actively adjusted according to wind and light power information of a next scheduling period, and collaborative regulation and control of energy storage and hydrogen storage are achieved. Compared with a traditional scheduling strategy, the collaborative optimization strategy provided by the invention improves the consumption rate of renewable energy sources of the system, reduces abandoned wind and light, improves the yield of synthetic ammonia, and verifies the effectiveness of the strategy.

The invention discloses a green ecological energy-saving irrigation roof system and a using method thereof, and relates to the technical field of building roofs. A green ecological energy-saving irrigation roof system comprises a root blocking waterproof layer, a blind ditch structure layer, a non-woven fabric filter layer, a planting layer and a vegetation layer which are arranged on a roof from bottom to top, a rainwater collecting device is arranged in the blind ditch structure layer, an irrigation device is arranged on the planting layer, the rainwater collecting device is communicated with a water storage tank, and the water storage tank is communicated with the irrigation device through a water suction pump; a soil humidity sensor is arranged in the planting layer, the soil humidity sensor and the water suction pump are both connected with the controller, and the solar power supply device is used for supplying power to the water suction pump, the soil humidity sensor and the controller. The solar power supply device is arranged on the roof and used for supplying power to electric equipment in the whole roof system, power supply depending on mains supply is avoided, near-zero-energy-consumption operation is achieved, the building capacity and energy consumption self-balance requirements are met, and the purposes of environment friendliness and energy conservation are achieved.

The invention discloses an adjustable solar power generation device for an expressway, and relates to the technical field of photovoltaic energy power generation. The device comprises a base frame, two symmetrically-distributed transverse plates are stably installed on the two sides of the outer wall of the base frame through bolts, a side plate is stably installed on one side of the outer wall of the base frame through bolts, a shell is stably installed on the side, close to the side plate, of the end of the base frame through bolts, photovoltaic folding storage assemblies are arranged on the transverse plates, and wind power dust removal assemblies are arranged on the outer sides of the side plates. A filtering and cleaning assembly is arranged on the wind power dust removal assembly, and the photovoltaic folding and storing assembly comprises four sliding blocks distributed in a rectangular array and two symmetrically distributed driving blocks; by arranging the wind power dust removal assembly, an impeller in the wind power dust removal assembly is driven by a driving shaft to generate high-speed airflow, after impurities of the high-speed airflow are filtered out through a filter bin and a filter drum, the clean high-speed airflow is precisely guided to a folded photovoltaic panel area through an exhaust pipe and an exhaust frame, and dust on the surface of a photovoltaic panel is treated.

The invention provides an energy-saving compressor intelligent self-adaptive control system based on multi-sensor fusion, which belongs to the technical field of industrial compressor intelligent control and comprises a data acquisition module, a signal conditioning module, a multi-sensor information fusion module, an intelligent control decision module, an execution driving module and a system power supply management module. A state display alarm and remote communication module can be additionally arranged. Multiple sensors collect operation and environment parameters of the compressor, and after conditioning, a comprehensive state evaluation result is generated through D-S evidence theory or fuzzy logic fusion; the intelligent module generates a control instruction based on a load prediction algorithm and a fuzzy PID self-tuning strategy, and the execution module drives the compressor to act; the power supply module supports solar power supply and multi-power supply switching. The system overcomes the limitation that a traditional compressor is single in sensing, rigid in control and the like, comprehensive sensing, accurate evaluation and self-adaptive energy-saving control are achieved, the operation stability is improved, and the energy consumption and the operation and maintenance cost are reduced.

The invention relates to the technical field of control and adjustment, in particular to an energy storage configuration point-based power consumption cost calculation method, which comprises the following steps of: acquiring power supply data, renewable energy output fluctuation data and computing power load fluctuation data, and generating a coupling influence feature vector; splicing the electricity price features and the coupling features to form configuration optimization input features; the input features are processed through a dual-objective optimization model, and robustness configuration parameters and economical efficiency operation parameters are output; calculating the reserve cost compensation amount of the extreme scene based on the robustness parameter, and calculating the power purchase cost and maintenance cost of the power grid based on the economical efficiency parameter; and aggregating the cost component and outputting a power consumption cost calculation result. According to the method, the interactive influence of wind-light fluctuation and load mutation is quantified through coupling features, the target conflict between robustness and economy is coordinated by adopting the Pareto algorithm, the risk compensation amount is generated in combination with a pressure test, a feature updating mechanism is fed back in a closed loop mode, and the problem that the operation cost deviates from expectation due to quantization deviation of an existing model is solved.

The present invention belongs to the field of multi-energy complementary coordinated dispatching. Disclosed is a meteorological-downscaling-coupled dispatching method for the power generation and consumption of a hydro-wind-solar system. The method comprises: using a support vector machine regression algorithm to identify different hydrometeorological variable data, and establishing a statistical relationship between observation data and a meteorological factor to implement high-resolution spatial downscaling; using a wind-solar power-generation empirical formula to calculate a wind-solar output process; and introducing a series of time-series peak regulation modes to determine a regulated peak and a hydro-wind-solar power consumption linkage equation, thereby avoiding overestimation of energy consumption caused by neglecting climate change impacts and short-term power generation rules. By means of the analysis of engineering examples consisting of Yunnan Lancang River Basin and surrounding wind-solar power stations thereof, the result shows that the present invention can effectively reduce hydrometeorological downscaling errors, and more accurately describe hydro-wind-solar energy power generation rules by means of a hydro-wind-solar power consumption linkage equation, thereby making the dispatching result show better accuracy and reliability.

The invention provides a hydrogen production rate-based dynamic adjustment method for an alkaline electrolytic cell, which comprises the following steps of: constructing a function model of electric power and hydrogen production rate of the alkaline electrolytic cell, optimizing the array configuration of the electrolytic cell in combination with historical wind and light data, dividing the operating state of a single electrolytic cell, and dynamically distributing the operating state in a value rotation mode. And the matching between the wind-solar power and the hydrogen production requirement is realized. The method comprises the following specific steps: constructing a power-hydrogen production rate mapping model to predict power consumption demands; determining the capacity of the electrolytic cell array based on the wind-solar power peak; distributing the number of the electrolytic cells in each state through a circular queue rotation strategy; and adjusting the operation power instruction according to the hydrogen production rate working condition. The system does not need an energy storage device, the wind and light fluctuation is absorbed through the self-state combination of the electrolytic cell array, and the problems of high cost, non-uniform equipment loss, high electrolytic cell monomer loss difference and the like caused by energy storage dependence in the traditional technology are solved.

The invention relates to the technical field of high-voltage switch equipment, and discloses a primary and secondary fusion pole-mounted circuit breaker which comprises a base, a front plate is arranged on the front side of the base, the base and the front plate are connected through a connecting plate, a first solid-sealed polar pole is arranged on the top of the base, and a second solid-sealed polar pole is arranged on the top of the front plate. A high-voltage input plate is arranged at the top of the solid-sealed polar pole I, a high-voltage output plate is arranged on one side wall of the solid-sealed polar pole I, the connecting frame is fixedly connected between the solid-sealed polar poles I, the bird repelling mechanism is arranged at the top of the connecting frame and used for repelling birds to prevent the birds from stopping, and the shielding mechanism is arranged at the top of the solid-sealed polar pole I. By means of the bird repelling mechanism, the all-weather and intelligent active bird repelling function is achieved, stable equipment operation is guaranteed, a dual-drive mode combining wind power and solar power is adopted, it is guaranteed that the bird repelling function is uninterrupted, pollution flashover or short circuit faults caused by bird activities to high-voltage insulation parts are effectively avoided, and the equipment operation reliability is improved.

The invention provides a wind-solar-storage integrated scheduling method based on a GNN platform, and the method comprises the steps: collecting wind-solar-storage historical and real-time data, constructing a static and dynamic graph structure, training a multi-task GNN model fusing an attention mechanism, achieving the wind-solar power prediction and joint optimization scheduling, controlling the rolling output of a scheduling instruction based on the model, and carrying out the execution after the safety verification. And if not, triggering the correction mechanism to be issued again. According to the invention, accurate prediction and efficient scheduling of the wind and light storage system can be realized, and the economical efficiency, safety and stability of system operation are improved.

The invention discloses a solar power generation prediction method, device and equipment. The method comprises the following steps: acquiring current irradiance data of a meteorological station in a current irradiation period; the current irradiance data are input into an irradiance prediction model, next irradiance data of the next irradiation period output by the irradiance prediction model is obtained, and the irradiance prediction model is obtained through model optimization based on a land assimilation model and a numerical weather prediction model in combination with machine learning optimization adjustment logic; and according to the next irradiance data, the weather forecast data and the ambient air data, predicting the power generation output power of solar power generation. Through the method, the irradiance prediction model obtained by combining the land assimilation model and the numerical weather prediction model with the machine learning optimization adjustment logic optimization model is used for irradiance prediction, the accuracy of irradiance prediction is improved, and the power generation output power of solar power generation can be predicted more accurately.

The invention relates to the technical field of solar lighting, and discloses an LED outdoor landscape lamp control system based on solar power supply. The system comprises a solar power supply management module, an energy storage scheduling and state management module, an intelligent sensing and environment identification module, a light control decision module and a self-adaptive feedback and system optimization module. The method comprises the following steps: acquiring voltage, current and irradiance data of a solar module, and combining a maximum power point tracking algorithm to generate power supply data; outputting scheduling parameters based on the dynamic scheduling model, acquiring environment data by using a multi-modal sensor and an image recognition technology, and calculating an illumination control factor; fusing the scheduling parameter, the illumination factor and the time factor, and calculating a target control matrix; and monitoring an execution feedback signal, and iteratively optimizing the control model based on historical control effect data to realize closed-loop optimization control. According to the invention, multi-source data fusion and adaptive control are realized, and the energy efficiency and intelligent level of the LED landscape lamp in a complex environment are improved.

The invention relates to the technical field of wind and light power prediction, and discloses a wind and light power prediction system and method based on artificial intelligence, and the system comprises a data collection and processing module, a feature extraction module, an intelligent prediction module, a dynamic correction module, a block chain evidence storage module, and a man-machine interaction module. Before a wind-solar power prediction model is trained, original data is cleaned and filled by adopting an abnormal data detection algorithm based on the combination of a 3 sigma criterion and box plot analysis and an improved KNN missing data filling algorithm, noise and errors in the data can be identified and corrected, the quality of a generated standardized wind-solar power training sample set is ensured, and the accuracy of the wind-solar power prediction model is improved. The prediction deviation is reduced, and a reliable data foundation is laid for generating a high-precision prediction result.

The invention discloses a reinforcement learning-consistency theory combined wind-solar-hydrogen storage micro-grid regulation and control method, and belongs to the technical field of new energy and micro-grid regulation and control. The method comprises the following steps: firstly, establishing a micro-grid model covering electrochemistry, thermodynamics and mass transfer processes, wherein the micro-grid model comprises wind-solar power generation equipment, an electrolytic cell and the like; designing an optimization regulation and control model by taking operation cost minimization and hydrogen production maximization as targets and combining with equipment safety constraints; the power of the electrolytic cell is dynamically distributed through an improved consistency algorithm based on gradient compensation, the state of a hydrogen storage tank is balanced, and a layered regulation and control framework is formed by adopting a deep reinforcement learning algorithm with improved TD3 to cooperate with multiple devices. According to the invention, the new energy consumption rate and the system reliability and economy are improved, and intelligent regulation and control support is provided for a green electricity hydrogen production project.

The invention belongs to the technical field of energy management and power system optimization, and particularly discloses a port microgrid optimization scheduling method, device and equipment, a storage medium and a product. According to the application, the microgrid operation optimization model is constructed according to the predicted load demand, the predicted wind power generation power and the predicted solar power generation power; solving a target scheduling strategy according to the power grid operation optimization model and the multi-dimensional microgrid operation constraint conditions; and performing optimal scheduling on the port microgrid according to the target scheduling strategy. Through the above mode, comprehensive optimization of microgrid operation is realized by using the microgrid operation optimization model on the basis of considering the operation cost and the environment cost, the operation stability is ensured according to the multi-dimensional microgrid operation constraint condition, and then optimization scheduling is performed on the port microgrid according to the target scheduling strategy. Therefore, the accuracy of dispatching the port micro-grid can be effectively improved, the operation economy and the energy utilization efficiency of the micro-grid are improved, and carbon emission is reduced.

The invention relates to the technical field of renewable energy source and process industrial intelligent control, and discloses a full-process optimization method and system for synthesizing ammonia through wind-solar hydrogen production, which can realize full-process collaboration and self-adaption to wind-solar fluctuation, and can guarantee system safety and economy in long-term operation. According to the scheme, the method comprises the steps that running state data of a wind-solar power generation system, a hydrogen production system, a hydrogen storage system and a synthetic ammonia system are collected in real time, and the collected data are preprocessed; establishing a device-level adaptive boundary model, and calculating a dynamic safe operation boundary of the key device; inputting wind-solar power prediction of a future time domain, performing rolling optimization based on the multi-objective optimization model according to constraint conditions, and generating load setting instructions of each system; and executing the load setting instruction, collecting real response data of the system, comparing a deviation between a real response and a predicted response, calculating a multi-dimensional deviation index, and when the deviation exceeds a set threshold value, performing feedback calibration on the equipment-level adaptive boundary model.