Nothing Special   »   [go: up one dir, main page]

Shendryk et al., 2022 - Google Patents

Short-term Solar Power Generation Forecasting for Microgrid

Shendryk et al., 2022

Document ID
2628284398797518
Author
Shendryk V
Parfenenko Y
Kholiavka Y
Pavlenko P
Shendryk O
Bratushka L
Publication year
Publication venue
2022 IEEE 3rd International Conference on System Analysis & Intelligent Computing (SAIC)

External Links

Snippet

Nowadays, the world's energy consumption is growing, and solving the problem of replacing traditional sources with alternative ones is urgent. The solution to this problem is impossible without prior data analysis and further forecasting of energy production from alternative …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/54Management of operational aspects, e.g. planning, load or production forecast, maintenance, construction, extension
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00Communication or information technology specific aspects supporting electrical power generation, transmission, distribution or end-user application management
    • Y04S40/20Information technology specific aspects
    • Y04S40/22Computer aided design [CAD]; Simulation; Modelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Madhukumar et al. Regression model-based short-term load forecasting for university campus load
Behera et al. Solar photovoltaic power forecasting using optimized modified extreme learning machine technique
Mahmoud et al. An advanced approach for optimal wind power generation prediction intervals by using self-adaptive evolutionary extreme learning machine
Du et al. Multi-step ahead forecasting in electrical power system using a hybrid forecasting system
Chang et al. An improved neural network-based approach for short-term wind speed and power forecast
Marín et al. Prediction interval methodology based on fuzzy numbers and its extension to fuzzy systems and neural networks
Bassey Hybrid renewable energy systems modeling
Raza et al. Multivariate ensemble forecast framework for demand prediction of anomalous days
Zhu et al. Short‐Term Electricity Consumption Forecasting Based on the EMD‐Fbprophet‐LSTM Method
Jurj et al. Overview of electrical energy forecasting methods and models in renewable energy
Zhao et al. Short-term wind electric power forecasting using a novel multi-stage intelligent algorithm
Cruz et al. Neural network prediction interval based on joint supervision
Ahmad et al. Efficient energy planning with decomposition-based evolutionary neural networks
Alharbi et al. Short-term wind speed and temperature forecasting model based on gated recurrent unit neural networks
Pandu et al. Artificial Intelligence Based Solar Radiation Predictive Model Using Weather Forecasts.
Eseye et al. Short-term forecasting of electricity consumption in buildings for efficient and optimal distributed energy management
Zahraoui et al. ANN-LSTM Based Tool For Photovoltaic Power Forecasting.
Famoso et al. A Dependability Neural Network Approach for Short-Term Production Estimation of a Wind Power Plant
Almeida et al. Hierarchical time series forecast in electrical grids
Shendryk et al. Short-term Solar Power Generation Forecasting for Microgrid
Baltputnis et al. ANN-based city heat demand forecast
Bahij et al. A review on the prediction of energy consumption in the industry sector based on machine learning approaches
Neudakhina et al. An ANN-based intelligent system for forecasting monthly electric energy consumption
Ding et al. A statistical upscaling approach of region wind power forecasting based on combination model
Gilbert et al. A hierarchical approach to probabilistic wind power forecasting