299 results about "Renewable power generation" patented technology

The invention provides a multi-data center computing power-electric power cooperative scheduling and demand response declaration capacity optimization method, which comprises the following steps of: firstly, acquiring multi-dimensional historical time sequence data of a data center; a machine learning algorithm is used to predict the workload of each data center in each time period of a future single day in a future scheduling period and the power market price of the place where each data center is located, and then a space-time coupling-oriented multi-data center computing power-power cooperation model considering uncertainty is constructed; the collaborative model comprises a joint optimization framework of computing power scheduling and power scheduling, and takes actual profit maximization as a target, then the established collaborative model is converted into a mixed integer linear programming problem and solved, and the optimal declaration capacity of each data center participating in demand response is obtained; and each data center carries out scheduling according to the task load of space migration and time migration, the charging and discharging power of an energy storage system and the power generation amount of renewable energy sources, so that overall optimization of demand response declaration capacity of the multiple data centers is realized.

Disclosed in the present invention is a deep learning-based power distribution network load prediction method, comprising: acquiring regional load data and renewable energy power generation data to form a data set, and preprocessing the data set to obtain a first data set; using a convolutional neural network to extract a time series feature in the first data set, and converting the time series feature into a data form of a deep learning model by means of an embedding layer to obtain one-dimensional time series data; performing fast Fourier transform on the one-dimensional time series data to obtain a frequency curve, extracting amplitude values on the frequency curve to calculate corresponding periods, and selecting the corresponding periods to slice the one-dimensional time series data and form same into two-dimensional matrixes; using a two-dimensional convolutional network to perform feature extraction, reshaping the two-dimensional matrixes that have undergone feature extraction into one-dimensional arrays, and performing adaptive fusion on the one-dimensional arrays to obtain a first time series feature; and inputting the first time series feature into a fully connected layer for weight calculation and linear transformation to obtain a power distribution network load prediction result, thereby improving the stability and reliability of electric power supply.

The invention relates to the technical field of data processing, and particularly provides a low-altitude aircraft power supply facility cooperative control method, system and device and a medium, and the method comprises the steps: predicting the renewable energy power generation power of a power supply facility and the charging load power of a low-altitude aircraft based on obtained multi-source information, and generating a prediction scene set representing uncertainty; based on the prediction scene set, through a multi-time scale optimization strategy, solving a scheduling model with optimal operation cost as a target, and successively obtaining a pre-scheduling plan of a day-ahead stage and a real-time control instruction of an intra-day stage; the multi-time scale optimization strategy comprises random optimization based on a scene and feedback optimization based on a rolling time domain; according to the real-time control instruction, power distribution is conducted on the hybrid energy storage system, and a power type energy storage unit preferentially responds to the transient power requirement for charging of the low-altitude aircraft. The comprehensive operation cost is effectively reduced, and particularly, the service life of equipment is prolonged through quantitative energy storage degradation.

The invention discloses an industrial park comprehensive energy management method and system based on a hierarchical system, and belongs to the technical field of energy management and automatic control. The method comprises the following steps: integrating external data, and predicting load and renewable energy power generation power by using a machine learning algorithm; making a start-stop and output plan of each energy device in the park through an MILP model; and based on short-term prediction and an intra-day scheduling plan, establishing an MPC model, solving a real-time control instruction of each energy device, and controlling operation of various energy production, conversion and storage devices. According to the method, an algorithm combining reinforcement learning and model prediction control is creatively applied, the prediction model and the cost function of MPC are adaptively adjusted on line through reinforcement learning, the equipment power is dynamically adjusted in combination with short-term rolling prediction, uncertainty is effectively dealt with, more accurate second-level power balance is achieved, and the reliability of the system is improved. And the adaptability and the operation economy of the system to high-proportion renewable energy sources are effectively improved through hierarchical collaborative optimization.

The invention relates to the technical field of system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

The invention provides a micro-grid management method and system based on source grid load storage, and relates to the technical field of micro-grids, and the method comprises the steps: S1, obtaining renewable energy power generation data in a micro-grid, the state of charge (SOC) of an energy storage device, a load demand, and power grid operation state information; and S2, performing real-time prediction on the load demand by using an intelligent algorithm and generating a load scheduling plan. According to the micro-grid management method and system based on source grid load storage, load prediction is carried out by introducing an intelligent algorithm, power scheduling between renewable energy sources and an energy storage device is optimized by a dynamic coordination mechanism, and resources are allocated by a multi-objective optimization algorithm, so that efficient management of the micro-grid is successfully realized. By acquiring various data in the micro-grid in real time and combining with a dynamic adjustment scheduling strategy, the method can effectively deal with the uncertainty of load fluctuation and renewable energy output, optimize the operation efficiency of the power grid, and ensure the stability and economy of the system.

A dynamic frequency coordination control method for asynchronous regional power grids during wet and dry seasons is provided. By using frequency synchronous control in VSC-HVDC, frequency consistency and synchronization between the sending-end and receiving-end grids can be ensured within the range of power adjustment, enabling real-time and automatic sharing of frequency regulation resources between the two grids. Through the use of bilateral frequency limiting control in LCC-HVDC, the frequency regulation effect is enhanced, balancing frequency fluctuations between the sending-end and receiving-end grids. VSC-HVDC adaptive reactive power support control is employed to provide reactive power support to nearby LCC-HVDC, avoiding frequent operations of LCC-HVDC converter transformers and filters during frequency limiting control actions, thereby extending equipment lifespan. Furthermore, by utilizing grid-following and grid-forming control in renewable energy grid integration with additional frequency control, the frequency support capacity of renewable energy generation is improved.

The invention discloses an intelligent street lamp system based on renewable energy and a control method, the system comprises a street lamp, a renewable energy power generation module, an energy storage module and an intelligent control unit, and the intelligent control unit comprises an intelligent sensing layer, an intelligent application layer and a cloud platform management layer; the intelligent sensing layer comprises a high-precision environment sensor, a human body / traffic flow detection sensor, an equipment state detection module and a controller; the cloud platform management layer comprises an adaptive dimming control module, an equipment management module, a data analysis module, an AI decision module and a visual monitoring module; the intelligent application layer comprises an intelligent operation and maintenance module, a multi-energy coupling module and a city data service module. By the adoption of the system, the management efficiency, the energy utilization rate and the operation and maintenance intelligent level of urban lighting facilities are improved, renewable energy sources such as solar energy and wind energy are combined, energy is collected through multi-energy coupling, regional cooperative control is optimized, and passive power utilization is achieved in the environment with sufficient natural energy.

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 an electricity-hydrogen-ammonia coupling multi-energy collaborative optimization system, and belongs to the technical field of comprehensive energy systems and clean energy conversion. According to the invention, links of renewable energy power generation (photovoltaic and wind power), electrolytic hydrogen production, hydrogen storage and transportation, hydrogen energy power generation, hydrogen-based chemical production and the like are deeply coupled to construct an electricity-hydrogen-ammonia coupled multi-energy collaborative optimization system, and a'source-storage-use 'integrated zero-carbon energy supply system is formed; therefore, the function boundary and the application scene of the existing electro-hydrogen coupling system are expanded. According to the invention, multi-module operation of wind-solar power generation, power grid interaction, electrolytic hydrogen production / hydrogen fuel cell power generation, green ammonia synthesis and the like is coordinated through an intelligent scheduling mechanism, so that the system is ensured to participate in multi-dimensional transaction of the power market and the hydrogen energy / chemical product market at the same time; the comprehensive benefits of full consumption of renewable energy sources, peak regulation income maximization of the power grid, zero carbonization of chemical production and value-added utilization of by-products are achieved.

A Surface-affixed, Storm-Resistant Containment Unit involves a shelter structure, with internally-mounted photovoltaic solar panels, and movable doors which may be ‘closed’ to protect the photovoltaic solar panels from storm-related damage, e.g. hail, extreme wind and airborne debris. When weather conditions improve, the movable doors may be ‘opened’, allowing sunlight to strike the undamaged photovoltaic solar panels, and renewable energy production to resume. These Storm-Resistant Containment Units may be installed, and electrically connected in multiples to comprise a storm-resistant, commercially-sized, renewable power generating station (or ‘Micro-Grid’) for use in geographic areas prone to severe storms and hurricanes. Such storm-resistant, commercially-sized, power generation station may be advantageously applied at existing ‘Brown-Field’ industrial sites that have existing, unused electrical-grid infrastructure.

The present disclosure relates generally to infrastructure for renewable energy power generation, and is directed more particularly to infrastructures for thermal cycles for continuous and / or modulated power generation based, in whole or in part, on gravitational force, including infrastructures for lower grade heat recovery.

The invention discloses a control method and a control system for a hybrid power supply system, and relates to the technical field of communication technology and electric power, and the method comprises the steps: obtaining the current operation data and environment forecast data of the hybrid power supply system; generating a renewable energy power generation power prediction curve and a load demand power prediction curve in a preset time window in a rolling manner by using a machine learning prediction model based on the current operation data and the environment prediction data; calculating an energy adequacy index based on the current energy storage state of the energy storage unit, the renewable energy power generation power prediction curve and the load demand power prediction curve; according to the energy adequacy index, dynamically selecting a corresponding target working mode from a preset working mode library; and according to the cooperative operation rule corresponding to the selected target working mode, generating and executing a control instruction corresponding to the selected target working mode so as to adjust the power output of each unit and / or the access state of the load. According to the scheme, the power supply reliability of the system is improved.

The invention specifically discloses a micro-grid low-carbon optimization scheduling method based on demand response, and relates to the field of energy optimization scheduling, and the method specifically comprises the steps: carrying out the modeling based on the structural characteristics of a renewable energy micro-grid; comprising the steps of renewable energy power generation system modeling, compressed air energy storage system CAES modeling, storage battery energy storage system BESS modeling, hydrogen production and storage system modeling and demand uncertainty modeling. The method comprises the following steps: constructing operation constraint conditions for renewable energy power generation system modeling, compressed air energy storage system modeling, storage battery energy storage system modeling, hydrogen production and storage system modeling and demand uncertainty modeling, constructing an objective function of comprehensive scheduling optimization, and constructing a comprehensive scheduling optimization model on the premise of meeting the system operation constraint conditions. The total operation cost and the pollutant discharge amount of the system are minimized, demand side response is considered, and a water bear optimization algorithm is adopted for scheduling strategy optimization. According to the invention, the economical efficiency and green level of renewable energy microgrid operation can be effectively improved.

The invention relates to the field of photoelectric detection and remote sensing monitoring, and provides an intelligent forest fire identification method. The method comprises the steps that image data of a monitoring area are acquired in real time through a multispectral data acquisition module, and the image data comprise thermal imaging data and visible light data; an embedded processing unit is used for processing image data in real time, and automatic identification and positioning of fire points are achieved through a multispectral data fusion algorithm; the power output of a power supply system is dynamically adjusted by adopting an intelligent energy management strategy to support all-weather operation of equipment, and the power supply system comprises a renewable energy power generation unit and an energy storage unit; based on the topographic data, adjusting the spatial attitude of the intelligent forest fire identification equipment through an adjustable supporting structure; after a fire point is identified, alarm information is transmitted to a monitoring center through a communication module, and an emergency response mechanism is triggered. According to the application, high accuracy and all-weather stable operation of forest fire monitoring are realized through multispectral collaborative identification and intelligent energy management.

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.

When establishing a work stop plan in a power system, it is difficult to consider whether it is possible to simultaneously stop all combinations of work, and reduction of arbitrary combinations reduces the explainability and index in the work stop plan. In order to solve this problem, provided in a power system is a work stop plan creation assistance system that comprises at least a processing unit and a storage unit and receives, as inputs, work list data including one or more tasks, system configuration data, and future prediction scenario data including future demand prediction or renewable energy output prediction. The processing unit: uses data from the storage unit to extract a facility in which a power flow changes by a prescribed amount when the facility is stopped due to work; calculates flow sensitivity for the extracted facility; uses the flow sensitivity to extract the most severe condition of an objective function or a constraint function for a work stop plan; calculates the value of the objective function or the constraint function when the work was performed in accordance with the most severe condition; and determines the importance from the calculated value when the work was performed.

A method for managing communication of instructions to a plurality of controlled assets (4), eg. wind turbines, arranged within a private communication network of a renewable power plant (3) is disclosed. One or more requesting assets (5), arranged within the private communication network, contacts (6) a secure data centre (1) arranged externally with respect to the private communication network, on behalf of one or more controlled assets (4) being associated with that specific requesting asset (5). The secure data centre (1) generates a database (8) comprising a registry of controlled assets (4) for which instructions were requested, and representing a portfolio of controlled assets (4) being managed by the secure data centre (1). The secure data centre (1) subsequently manages communication of instructions originating from an external control centre (2) to each of the registered controlled assets (4) of the portfolio of the secure data centre (1), upon request from the requesting assets (5).

The application discloses an off-grid renewable energy hydrogen storage and target compound synthesis system, method and electronic device, relates to the technical field of renewable energy, and comprises a renewable energy power generation unit, a water electrolysis hydrogen production unit, a fuel cell unit, a hydrogen storage unit, a target compound synthesis unit and a comprehensive energy scheduling unit which are connected with each other. When the corresponding relationship between power generation power and time is less than or equal to the rated power, the fuel cell unit is controlled to be in a starting state, the water electrolysis hydrogen production unit is controlled to produce hydrogen by being turned on, and the target compound synthesis unit is controlled to synthesize target compounds. When the stability of the comprehensive energy scheduling unit does not satisfy a preset stability condition, the fuel cell unit is controlled to be in the starting state, and the corresponding device in the comprehensive energy scheduling unit which does not satisfy the preset stability condition is in a closed state.

Provided is a power control device capable of avoiding instability due to a sudden change in renewable energy generated power. A power control device capable of controlling a plurality of power conversion devices for supplying power generated by renewable energy power generation to a power system, the power control device comprising: a power conversion device that performs first control for using a part of the power generated by power generation for inertial supply and second control for not using the power generated by power generation for inertial supply; a residual inertia calculation unit that obtains a residual amount of inertia supplied to the power system; a control determination unit that determines a first control and a second control for each of the power conversion devices on the basis of the remaining inertia amount obtained by the remaining inertia calculation unit; and a control transmission unit that transmits the operation control determined by the control determination unit to each of the power conversion devices.

The utility model relates to the technical field of wharfs, in particular to a novel zero-carbon wharf which comprises a wind driven generator, an energy storage device, a wave energy power generation device, a distributed photovoltaic panel and production and living electric equipment. The wind driven generator, the wave energy power generation device and the distributed photovoltaic panel convert wind energy, wave energy and solar energy into electric energy and store the electric energy in the energy storage device. The energy storage device supplies power to wharf production and living electric equipment; according to the zero-carbon wharf, renewable power generation facilities are adopted for collecting clean energy and converting the clean energy into electric energy to be supplied to the wharf, the clean energy is efficiently utilized, dependence on traditional energy is reduced, and self-sufficient and self-use of the wharf energy is achieved; power equipment such as wharf loading and unloading equipment and transportation machinery is adopted, energy is supplied to ships berthing to the harbor through the shore power system, the problem of tail gas emission is solved, meanwhile, the environmental noise of the wharf is reduced, and zero carbon emission of the wharf in the operation process is achieved.

The invention relates to the technical field of renewable energy utilization and heat supply systems, in particular to a heat pump and energy storage combined heat supply system with renewable energy consumption, which comprises a renewable energy power generation unit, an energy storage unit, a low-temperature efficient heat pump unit, a heat supply pipe network unit and an intelligent management and control unit, the energy storage unit and a power grid are connected to the main power supply switching cabinet through an electrical link, and the main power supply switching cabinet supplies power to each power utilization unit through the power distribution unit; the energy storage unit is connected with the low-temperature efficient heat pump unit and the heat supply pipe network unit through heat energy links. The intelligent management and control unit establishes data interaction and control links with the renewable energy power generation unit, the energy storage unit, the low-temperature efficient heat pump unit and the heat supply pipe network unit. The technical problems that in the prior art, the renewable energy consumption rate is low, the heat pump heating efficiency in the cold region is poor, and the system operation stability is insufficient are mainly solved.

The invention belongs to the technical field of energy storage system scheduling, and provides an energy storage system dynamic scheduling method and system based on multi-objective adaptive optimization, and the method comprises the steps: constructing a multi-objective optimization scheduling model of an energy storage system, and dynamically adjusting a weight coefficient through an adaptive mechanism; on the basis of a model prediction control framework, according to newest load prediction data and renewable energy power generation prediction data, in each rolling optimization period, the MILP is solved again, the SOC track and the power instruction are continuously corrected, and an optimal charging and discharging power instruction sequence of the energy storage system in the current rolling time domain is obtained; and issuing the first instruction of the optimal charging and discharging power instruction sequence to the energy storage system for execution, updating the system state, and entering the next rolling optimization period. The method can achieve the balance among multiple targets, carries out the real-time correction of a prediction error, also gives consideration to the prolonging of the service life of an energy storage system and the reduction of the maintenance cost, and improves the scheduling accuracy and flexibility.

A device (1) for rapidly transferring thermal energy from a thermal energy source (A) to a destination point (B) at a rate higher than the convection and heat transfer capacity of adjacent means 2 and for capturing said thermal energy point or surface, wherein a thermoelectric conversion means located at the destination point B can convert the thermal energy into electrical energy with zero emissions harmful to the environment and living things. The thermal energy is transferred by a coating 4 composed of a plurality of nanometric layers with atoms forming a regular geometric structure (Figure 1). The present invention also relates to a device for the transfer of thermal energy having multiple layers of carbonaceous material on a planar or non-planar (three-dimensional shape), opaque, transparent or translucent, rigid or semi-rigid substrate of fabric, metallic or non-metallic or flexible material, having flexible but not opaque, transparent or translucent natural or synthetic fibers. The present invention also includes a method for manufacturing a device (10 or 10a) for the rapid transfer of thermal energy. The method comprises at least one deposition step of at least one layer (12, 12a-12b-12c-12d, etc.) of a carbonaceous material having a regular geometric structure on a support substrate (11 or 11a) in an environment (110) of a deposition machine (100), the environment being vacuum-packed under controlled temperature and pressure conditions and isolated from the external environment, the deposition being performed along a direction perpendicular or locally radial to a plane or shape substantially defined by the support substrate (11 or 11a). The present invention also relates to an integrated system for generating electrical energy using said device coupled to a possible generator other than a renewable energy source of thermoelectric generator, photovoltaic and / or thermoelectric-photovoltaic and / or motive power type, all used jointly for the supply of an electrical load.

The invention relates to the technical field of smart energy and zero-carbon power generation, in particular to an operation control method and device for an ammonia gas turbine power generation system.The method comprises the steps that actual operation data, actual environment data and actual power grid data of a target ammonia gas turbine power generation system in the current state are collected; predicting predicted operation data and predicted power grid data of the target ammonia gas turbine power generation system in a preset time period; and outputting a control instruction of the target ammonia gas turbine power generation system by using the multi-target optimization model so as to control the operation of the target ammonia gas turbine power generation system. Therefore, the problems that in related technologies, renewable energy power generation does not relate to power-hydrogen-ammonia-power full-chain cooperative control, power grid dispatching and market environment factors are not considered, prediction and decision-making capabilities are lacked, and operation efficiency is low are solved; during combustion of an ammonia fuel gas turbine, fuel supply of the ammonia gas turbine and upstream hydrogen production and ammonia synthesis links are lack of a dynamic matching mechanism, and complex operation scenes are difficult to deal with.

The invention discloses a control instruction determination method and system of a water electrolysis hydrogen production system and electronic equipment. The method comprises the following steps: acquiring a first power generation amount of renewable energy power generation equipment of the water electrolysis hydrogen production system, a first charge state of energy storage equipment of the water electrolysis hydrogen production system, and a first operation parameter and a first degradation characteristic parameter of an electrolytic bath of the water electrolysis hydrogen production system in a current data acquisition period; determining a first predicted remaining life of the electrolytic cell based on the first operating parameter and the first degradation characteristic parameter; based on the first generating capacity, the first state of charge and the first predicted remaining life, a prediction control instruction of the water electrolysis hydrogen production system is determined, and the prediction control instruction comprises the target operation current of the electrolytic cell and the target charging and discharging power of the energy storage equipment. The technical problem that the prediction control instruction determination result of the water electrolysis hydrogen production system is inaccurate in the prior art is solved.

The present invention relates to a free-standing, transportable renewable energy generation unit. The unit comprises an enclosure housing an electrical system and a solar panel mounted to the enclosure by a support structure. The support structure comprises an angular adjustment mechanism for the solar panel, wherein the unit comprises a controller for the angular adjustment mechanism arranged to automatically adjust the angular orientation of the solar panel, e.g. relative to the unit.

The invention discloses a green ammonia synthesis system based on calcium-based thermochemical energy storage and high-temperature electrolysis coupling. Comprising a renewable energy power generation system, a heat exchange working medium pump, a thermochemical energy storage unit, an air separator, a high-temperature electrolytic hydrogen production unit, a nitrogen storage tank, a hydrogen storage tank, a first steam storage tank, a third steam storage tank, an ammonia synthesis unit, a second heat exchanger, a second steam storage tank, a first heat exchanger and a water feeding pump, the system can effectively solve the problem of intermittency of renewable energy sources, and is low in cost and high in flexibility.

According to an aspect of the present disclosure, a system-level low voltage ride-through (LVRT) control system for a renewable power plant (RPP) connecting to a weak grid is provided. The system includes a voltage boundary vector trajectory model that captures geometric relationships of system-side responses to determine voltage controllable boundaries. The system includes a discrete and clustering matrix-based calculation algorithm that computes optimal current commands within the constructed boundaries.