43 results about "Renewable energy supply" patented technology

The invention discloses a dynamic resource allocation system and method for smart travel. The system comprises a multi-source data acquisition module, a data fusion module, a prediction module, a framework construction module, an algorithm optimization module, a feedback module and a resource allocation module. According to the method, environment data, energy consumption data, renewable energy supply data and tourist flow data in a plurality of sub-regions of the tourist attraction are collected, and fusion and deep learning prediction are carried out on the data, so that future energy consumption, energy supply and flow data are obtained. And a reinforcement learning scheduling framework is constructed, and intelligent scheduling of the charging pile, the electric sightseeing vehicle, the lighting equipment and the monitoring equipment is realized. And carrying out global optimization on the resource scheduling scheme by adopting a speed pause particle swarm optimization algorithm so as to output a resource allocation scheme with optimal energy consumption. The scheduling scheme is further optimized based on user feedback data, and the dynamic adaptability of resource configuration is ensured. According to the invention, the energy utilization efficiency in the smart travel scene is improved, and the operation cost is reduced.

A power converter includes: a power conversion unit configured to convert power input from a bus, output the converted power to a power element, convert power input from the power element, and output the converted power to the bus; a measurement unit configured to measure an electrical characteristic value of power input to and from the power conversion unit; a storage unit configured to store a first reference function and a second reference function; a setting unit configured to set a power conversion characteristic of the power conversion unit based on an electrical characteristic value; and a management unit configured to manage a renewable energy charge amount and manage an amount of power derived from renewable energy supplied from the power element.

This application relates to the field of data processing technology, and discloses a power distribution method and an intelligent power distribution cabinet based on AI artificial intelligence. The method includes: real-time data collection of key nodes of the power distribution system through an intelligent sensor network to obtain the original power distribution system operation data, and performing cleaning and standardization processing on the data to obtain a standardized data set; analyzing and modeling the standardized data set through multi-level hybrid model training to obtain an AI analysis model of the power distribution system; processing and analyzing the real-time collected power distribution data to obtain a load prediction result and a dynamic balance strategy; performing abnormal pattern recognition and multi-path reasoning on the system operation parameters to obtain an equipment health status assessment and maintenance suggestions; based on the equipment health status assessment and maintenance suggestions, performing multi-objective optimization calculation on the renewable energy supply and electricity demand to obtain an intelligent energy scheduling scheme. This application improves the efficiency and accuracy of the power distribution method based on AI artificial intelligence.

The invention relates to the technical field of data processing, and discloses an intelligent computing center energy consumption optimization method and system based on the Internet of Things. The method comprises the steps of collecting storage medium energy consumption parameters and data block access behavior parameters to generate an original data set, calculating a weighted access characteristic value and a cold and hot state transition probability, screening candidate data blocks and calculating an energy consumption benefit evaluation index, matching a renewable energy source supply state to construct a migration task sequence, and obtaining a new energy consumption benefit evaluation index. And executing migration operation and dynamically adjusting the prediction parameters. The problems that in the prior art, data cold and hot state conversion cannot be intelligently predicted, energy consumption benefit quantitative evaluation is lacked, cooperation of data migration and renewable energy source supply is insufficient, and prediction model parameters cannot be adaptively adjusted are solved.

The invention discloses an all-weather negative carbon stable operation methanol preparation system. The system comprises a methanol synthesis device, a hydrogen acquisition device, a carbon dioxide acquisition device, a heat collection device, a power supply device and a methanol storage device. The methanol synthesis device is used for synthesizing methanol and comprises a reaction tank, the hydrogen obtaining device comprises a water electrolysis hydrogen production module, the carbon dioxide obtaining device is used for obtaining carbon dioxide and supplying the carbon dioxide to the reaction tank, and the energy source of the heat collection device is renewable energy and is used for supplying heat to the reaction tank; the energy source of the power supply device is renewable energy and is used for supplying power to the water electrolysis hydrogen production device. The methanol storage device is used for storing methanol generated by the methanol synthesis device and supplying heat to the reaction tank in an auxiliary manner. According to the all-weather negative carbon stable operation methanol preparation system provided by the embodiment of the invention, a methanol production process is green and environment-friendly, so that methanol can be stably produced under the condition of renewable energy source supply fluctuation, and the yield of methanol is increased.

The invention belongs to the technical field of power system control, and provides a source-grid-load interactive renewable energy supply flexibility control method and system, and the method comprises the steps: obtaining a power grid state deviation according to related physical information; generating and broadcasting synthetic pheromones according to the power grid state deviation to obtain a pheromone gradient field; secondly, extracting field features of a position pheromone gradient field where the distributed flexible resources are located; the field features comprise pheromone concentration and pheromone concentration gradient; according to the field feature and the state of the flexible resource, calculating a power regulation amount through a preset response vector graph; and finally, according to the power regulation quantity, controlling the flexible resource to carry out power output regulation. According to the method, the communication and calculation bottlenecks of centralized control can be avoided, and the limitation of global coordination deficiency of distributed control can be overcome, so that rapid, efficient and stable cooperative control of massive distributed flexible resources is realized.

The disclosure pertains to a plant for the production of ammonia. The ammonia is produced from hydrogen obtained by electrolysis of water. The electrolysis is powered by a renewable source of energy, complemented with power obtained from the plant during periods of low or no availability of the renewable energy. To this end, the plant is configured such that it can be operated in a charge configuration (obtaining and storing power) and a discharge configuration (employing said power).

The present invention discloses an energy supply method and system for nearly zero - energy buildings based on multi - objective optimization, which relates to the technical field of building energy efficiency and renewable energy applications. The method includes collecting energy consumption data in a building and constructing a multi - objective evaluation system according to the energy consumption data; optimizing the weights of the multi - objective evaluation system to obtain the optimal weight coefficients; combining the optimal weight coefficients with a solar photovoltaic system and a ground - source heat pump system to establish a renewable energy supply strategy model; and based on the renewable energy supply strategy model, outputting energy supply scheduling instructions for each time period of the building to adjust the operating parameters of the solar photovoltaic system and the ground - source heat pump system. The present invention ensures the balance between energy efficiency and comfort by real - time adjusting the equipment operation mode, avoiding the problems of common energy efficiency waste or insufficient comfort in traditional methods. Through intelligent scheduling and optimization, it can effectively reduce the energy consumption of buildings and improve the sustainability of their energy utilization.

The invention discloses a renewable energy supply source management system and a method thereof, which are used for supplying power to at least one power generation end by at least one power utilization end through at least one power purchase protocol so as to calculate a plurality of green energy indexes required by management. The system comprises an electric quantity data module; a scene data module; the green power index calculation module is used for calculating various green energy indexes for a specified time interval based on the corresponding electric quantity data, the corresponding scene data and a green energy transfer formula corresponding to the time interval; and the report module is used for presenting various green power indexes, scene data or charts related to the power generation end / protocol / power utilization end and the like.

The application provides a renewable energy supply-distribution-demand-storage system space-time coordination configuration method, relates to the technical field of intelligent energy, and comprises the following steps: acquiring data of multiple regions; calculating time mismatch degrees, space mismatch degrees and space-time coupling mismatch degrees of the regions; decomposing an optimization problem into a long-term planning layer, a medium-term scheduling layer and a short-term real-time layer in a time dimension; constructing multi-objective optimization functions of the time layers; decomposing the optimization problems of the time layers in a space dimension; alternately solving local optimization sub-problems and global coordination problems of the regions by using a distributed iteration method; outputting a configuration result of a current time layer when the algorithm converges; executing a decision of a first time period by each time layer and taking the decision as a constraint condition of a next time layer to obtain power generation installed capacities, power transmission line capacities, energy storage capacities and operation strategies of the regions. The application can improve a renewable energy consumption rate and reduce system operation costs.

The primary energy sources for low / zero carbon intensity (green) hydrogen production, such as sunlight and wind, are inherently intermittent in duration and variable in strength. An integrated, dynamically controlled production process is needed for the optimization of continuous green hydrogen production. The process needs to manage this dynamic state on a frequent basis within a green hydrogen production process to assess impacts from incoming renewable energy through to the outgoing continuous (e.g., 24 hours per day and up to 365 days per year) production of both gaseous and liquid hydrogen. The process needs to manage operational performance and metrics continuously using the production facility configuration, renewable energy supply profiles and operational safety requirements together with the capability to adapt to a variety of external constraints, including weather variation, water supply variation and offtake requirements.

The invention discloses a renewable energy source supply system capable of responding to demands. The renewable energy source supply system comprises a renewable energy source collection device, an intelligent control and monitoring system, an energy storage device, a demand response device, a power grid interaction device and a heat energy conversion and utilization device. The renewable energy source collecting equipment comprises a photovoltaic panel, a wind driven generator, a tidal power generator and an air source heat pump; the intelligent control and monitoring system comprises an energy management system, an intelligent inverter and an Internet of Things sensor. The energy storage equipment comprises electrochemical energy storage equipment, mechanical energy storage equipment and thermal energy storage equipment. According to the renewable energy source supply system capable of responding to the requirements, the wind driven generator is installed, the radar monitoring and noise reduction technology is adopted, the tidal power generator is provided with the ecological flow rate and the fishway, and then the operation noise of the wind driven generator is reduced, so that the influence of the wind driven generator on birds is reduced, and the influence on bird flocks is avoided.

The invention relates to the technical field of energy management, in particular to an automatic energy management strategy optimization method based on a stochastic optimization algorithm, and the method comprises the following steps: S1, collecting data including renewable energy output, traditional energy consumption, prediction demands and environmental parameters; s2, performing cleaning, normalization and feature extraction on the data acquired in the S1; s3, optimizing the energy management strategy; s4, adjusting an energy distribution and utilization plan; s5, predicting future energy demands and renewable energy supply conditions; s6, displaying the implementation effect of the energy management strategy through a user interface; and S7, regularly adjusting parameters of a random optimization algorithm and an energy management strategy according to a prediction result of S5 and implementation feedback of the energy management strategy. According to the invention, by dynamically adjusting and optimizing the energy management strategy, the energy utilization efficiency is improved, the energy cost is reduced, and the environmental influence is reduced.

It is the objective of the present invention to provide a method for negotiating and assigning data processing tasks among a plurality of participating data centers. This objective is achieved according to the present invention a method for negotiating and assigning data processing tasks among a plurality of data centers; said method comprising the steps of: a) providing a framework for a dynamic allocation of the data processing tasks and connecting a plurality of geographically distributed data centers participating via computing nodes to said framework; b) providing with the dynamic task allocation framework a task allocation instance, c) said task allocation instance is receiving bids and / or offers coming from the participating data centers wherein the bids and / or offers for data processing tasks reflect the share of real-time renewable energy supply and the remaining share of non-CO2-neutral energy supply as compared to a defined CO2-budget; and d) said task allocation instance is allocating the data processing tasks in the dependency of the received bids and / or offers to preferred data centers in the sense of applying one or more of the following allocation criteria: i) at least a majority of the participating data centers does not exceed the maximum share of non-renewable electricity allowable under the defined CO2-budget for the respective data center. ii) the data centers with the most advantageous share of renewable energy are loaded with data processing tasks first; iii) the remaining data processing tasks are allocated to the remaining data centers in the priority of the decreasing share of renewable energy generation and / or supply. Thus, the data centers participating via the computing nodes can achieve significant energy cost savings by offloading some or all of their excess workload during periods of high energy prices and leveraging surplus renewable energy supply at distant locations. Additionally, the computing nodes can maximize their self-consumption of renewable energy, thereby reducing reliance on external energy sources, promoting sustainability and observing the existing political directives.

The primary energy sources for low / zero carbon intensity (green) hydrogen production, such as sunlight and wind, are inherently intermittent in duration and variable in strength. An integrated, dynamically controlled production process is needed for the optimization of continuous green hydrogen production. The process needs to manage this dynamic state on a frequent basis within a green hydrogen production process to assess impacts from incoming renewable energy through to the outgoing continuous (e.g., 24 hours per day and up to 365 days per year) production of both gaseous and liquid hydrogen. The process needs to manage operational performance and metrics continuously using the production facility configuration, renewable energy supply profiles and operational safety requirements together with the capability to adapt to a variety of external constraints, including weather variation, water supply variation and offtake requirements.

The application discloses a kind of carbon emission reduction portrait determination method and device for building, it is related to building energy saving and emission reduction technical field.The method comprises: obtaining the target data of target building in historical time period;According to the target data of target building, the maximum installed capacity of target building, energy-saving energy of energy consumption system, renewable energy supply energy;According to the maximum installed capacity of target building, energy-saving energy of energy consumption system, renewable energy supply energy, determine the carbon emission reduction proportion value of target building;According to carbon emission reduction proportion value, determine the carbon emission reduction portrait of target building, wherein, carbon emission reduction portrait is used to represent at least one implementation mode to achieve carbon emission reduction proportion value.The present application solves the technical problem that the existing technology only analyzes carbon dioxide emission reduction of building from single emission reduction means, leading to poor carbon dioxide emission reduction effect for building.

To provide a system capable of improving efficiency of energy consumption and reducing an environmental load.SOLUTION: The system includes means for collecting household or business power consumption data in real time, means for acquiring weather data, means for acquiring renewable energy supply prediction data, means for analyzing a power consumption pattern based on the collected data, means for analyzing fluctuations in renewable energy supply due to weather fluctuations, means for generating a consumption prediction model, means for integrating consumption prediction and supply prediction and simulating a supply-demand balance, means for creating an optimal supply plan, means for notifying a household or business of the supply plan, and means for adjusting a supply amount.SELECTED DRAWING: Figure 1

The present invention provides a gas-fired power generation system and power generation method that utilizes efficient coupling of renewable energy. The gas-fired power generation system comprises: a renewable energy supply unit, a heat storage and exchange unit, a fuel gas supply unit, and a power generation unit. The heat storage and exchange unit stores heat from the renewable energy and exchanges heat with the fuel gas supply unit and / or the power generation unit. The fuel gas supply unit produces and stores fuel gas using renewable energy. The power generation unit comprises a SOFC cell and an induction coil. The SOFC cell receives the fuel gas and reacts to generate electricity. The induction coil is arranged around the SOFC cell and, at least when the SOFC cell is activated, supplies power to the induction coil, causing the SOFC cell to quickly heat up and start. This system can improve energy utilization efficiency and enhance the stability and continuity of the system's external power supply, thereby meeting future demands for efficient utilization of renewable and clean energy.

An energy management system and method designed to analyze the energy consumption of a building or cluster of buildings is provided. The system includes a user device and a controller. The controller includes a building energy audit analysis level, an energy demand-supply management level, and a heat and mass balance simulation level. The system integrates energy consumer-type users, energy server-type users, and energy developer-type users on one single platform. The energy management system provides a single platform for the sustainable management of energy data, integrates the users, inputs energy data, analyzes the data, and outputs energy performance and energy efficiency data based on the analyzed data.

The present invention discloses an electric power sharing energy docking method taking into account the expected contribution value deviation and the supply-demand ratio, comprising: each electric power sharing participant calculates the net surplus energy in the current period, determines the role, and calculates the expected contribution value; calculates the average expected contribution value of all electric power sharing participants with the same role as its own in the current period; calculates the expected contribution value deviation in its electric power sharing in the current period; calculates the supply-demand ratio in its electric power sharing in the current period; calculates the renewable energy supply adjustment coefficient and the energy demand adjustment coefficient in the electric power sharing in the next period; each electric power sharing participant calculates the renewable energy supply and energy demand in the electric power sharing in the next period; each electric power sharing participant reports its participation information in the electric power sharing in the next period to complete its energy docking with the electric power sharing platform; the use of the method of the present invention can significantly improve the cumulative contribution value of the electric power sharing participants in electric power sharing and improve the utilization rate of renewable energy.

To provide a hub management device and a hub management method which allow electric power from renewable energy to be used more efficiently.SOLUTION: A workload migration planning program 2470 migrates an execution hub where a calculation load is executed, in accordance with a migration plan made by using a hub power management table 2410. Further, the workload migration planning program 2470 acquires error information indicating an amount of deviation and a deviation occurrence time being a time when the deviation occurs, the amount of deviation being the deviation between a first predictive value being a value shown by the hub power management table 2410 used for making a migration plan of an object amount being at least one of a power demand and a renewable energy supply and a second predictive value predicted after the first predictive value of the object amount. Then, the workload migration planning program 2470 makes a corrected migration plan obtained by correcting the migration plan on the basis of the error information and load related information (2420 to 2460).SELECTED DRAWING: Figure 1

This invention relates to the field of flexible work shop scheduling technology, and discloses a multi-objective dynamic flexible work shop scheduling optimization method and apparatus. The method includes: constructing a flexible work shop scheduling model integrating multiple agent scheduling units; constructing a deep reinforcement learning objective function for the multiple agent scheduling units, and transforming scheduling rules into constraints and weight coefficients; acquiring the microgrid energy status, dynamic work queues, and real-time equipment status, defining flexible work shop state characteristic variables based on constraints, and embedding scheduling rules to construct a unified state space; based on an improved near-end strategy optimization algorithm, jointly training the multiple agent scheduling units using the state space, and setting a multi-dimensional composite reward mechanism to guide the multiple agent scheduling units to achieve optimized scheduling in a dynamic environment. This invention can achieve autonomous, intelligent, low-carbon, and efficient scheduling of flexible work shops in environments with intermittent renewable energy supply and frequent dynamic events within the work shop.

This invention belongs to the field of energy system optimization technology, and relates to a two-layer optimization method for a petrochemical park integrated energy system based on nuclear small modular reactors (SMRs). The method includes: 1. Obtaining the data required for optimization; 2. Constructing the configuration of the integrated energy system based on SMRs; 3. Designing a SMR heat load following strategy; 4. Selecting net present cost, renewable energy supply ratio, and lifecycle carbon emissions as optimization objective functions; 5. Obtaining the optimal equipment capacity of the system through a multi-objective cat swarm algorithm and the advantage-disadvantage distance method; 6. Performing operational optimization based on the optimal solution obtained from capacity optimization, operational optimization constraints, and objective functions. This invention achieves complementary utilization of multiple energy forms by synergistically coupling nuclear energy with renewable energy sources such as wind and solar power, as well as traditional energy systems, thereby improving the overall utilization efficiency of the energy system and enhancing the stability and reliability of energy supply.

The invention discloses an energy unit collaborative optimization method and system based on a small park, relates to the technical field of energy management, and solves the problems that non-renewable energy equipment is frequently started and stopped and the power consumption is low due to a collaborative power supply method of non-renewable power supply equipment and renewable energy equipment in the prior art. And aging of the non-renewable energy equipment is accelerated. The method comprises the following steps: acquiring productivity data of each renewable energy supply device and energy consumption data of an electricity consumption area; correcting a set power supply adjustment period according to the productivity data to obtain a current power supply adjustment period; setting pre-capacity data of the non-renewable energy supply equipment according to the power supply adjustment period, the capacity data and the energy consumption data; performing energy optimization distribution according to the pre-capacity data; by analyzing the stability of the productivity data of the renewable energy supply equipment in a period of time in the future, the power supply adjustment period is dynamically set according to the analysis result, and energy optimization distribution is performed in the power supply adjustment period, so that the aging speed of the non-renewable energy equipment is slowed down.

This application relates to the field of data processing technology and discloses a method and system for optimizing energy consumption in an intelligent computing center based on the Internet of Things (IoT). The method includes: collecting energy consumption parameters of storage media and data block access behavior parameters to generate a raw dataset; calculating weighted access feature values ​​and the probability of hot / cold state transitions; screening candidate data blocks and calculating energy efficiency evaluation indicators; matching renewable energy supply status to construct a migration task sequence; executing migration operations; and dynamically adjusting prediction parameters. This application solves the problems in existing technologies such as the inability to intelligently predict data hot / cold state transitions, the lack of quantitative assessment of energy efficiency, insufficient coordination between data migration and renewable energy supply, and the inability to adaptively adjust prediction model parameters.

A workload replacement planning program migrates an execution site that executes a workload by a migration plan created using a site energy management table. Also, the workload replacement planning program acquires error information indicating a deviation amount, which is the magnitude of a deviation between a first forecast value, which is a value shown in the site energy management table used to create a migration plan for a target amount, which is at least one of a renewable energy supply amount or an electric power demand amount, and a second forecast value of the target amount predicted after the first forecast value, and the deviation occurrence time point, which is the time point at which the deviation occurs. Then, the workload replacement planning program creates a corrected migration plan, in which the migration plan is corrected, based on the error information and the load-related information.

The invention relates to the technical field of building energy consumption optimization, and discloses a building energy consumption optimization method and system based on a green industrial building standard, and the method comprises the steps: determining the regulation and control parameters of a fresh air system based on the indoor carbon dioxide concentration change, so as to achieve the balance of air quality and energy consumption; the operation strategy of the wall comparison heat adjusting device is adjusted according to the sunlight radiation intensity change so as to avoid the increase of the air conditioner load, and the power utilization priority of the equipment in the building is dynamically regulated and controlled according to the real-time power pricing data so as to reduce the cost caused by the peak-valley electricity price difference. And optimizing the lighting, socket load and renewable energy supply proportion based on the personnel distribution heat density change and the cold and heat demand prediction result to improve the energy matching precision. Through the scheme of the embodiment of the invention, the problem of how to regulate and control the fresh air system according to the indoor carbon dioxide concentration change so as to achieve the balance between the air quality and the energy consumption can be solved.

The invention provides a renewable energy supply-transmission-demand-storage system space-time collaborative configuration method, and relates to the technical field of smart energy, and the method comprises the steps: obtaining the data of a plurality of regions; calculating a time mismatch degree, a space mismatch degree and a space-time coupling mismatch degree of each region; decomposing the optimization problem into a long-term planning layer, a medium-term scheduling layer and a short-term real-time layer in a time dimension; constructing a multi-objective optimization function of each time layer; the optimization problem of each time layer is decomposed in the spatial dimension; alternately solving the local optimization sub-problem and the global coordination problem of each region by adopting a distributed iteration method; when the algorithm converges, outputting a configuration result of the current time layer; and executing the decision of the first time period by each time layer and taking the decision as a constraint condition of the next time layer to obtain the power generation installed capacity, the power transmission line capacity, the energy storage capacity and the operation strategy of each region. The renewable energy consumption rate can be improved, and the system operation cost can be reduced.

The application discloses a project multi-stage-oriented building energy system carbon emission simulation method and system, which carries out dynamic simulation of energy consumption and carbon emission of building subsystems, energy consumption subsystems and renewable energy supply subsystems in four stages of planning and preliminary design, construction drawing design, construction installation and commissioning and operation and maintenance of a construction project. The application can establish building energy system models with different degrees of precision in a Modelica simulation environment according to the granularity of input data at different stages of the project cycle; through the construction of a component model library and the establishment of a dynamic updating mechanism of the system simulation model, the construction project multi-stage data source is connected, and the current operation carbon emission calculation tool is supplemented in the aspect of assisting multi-professional low-carbon design; based on the FMI standard, a three-dimensional building heat transfer model and a device control model are coupled, the building operation and regulation strategy can be flexibly constructed for a real operation and maintenance scene, and the problem that the current operation carbon emission calculation tool is difficult to reflect the actual operation condition of the system is solved.