[go: up one dir, main page]

Okoye et al., 2016 - Google Patents

A theoretical framework for enhanced forecasting of electrical loads

Okoye et al., 2016

View PDF
Document ID
17545582099867138724
Author
Okoye A
Madueme T
Publication year
Publication venue
International Journal of Scientific and Research Publications

External Links

Snippet

Forecasting of electrical load is vital in electrical sector; it helps in the process of planning periodical operations and facility expansion. In the deregulated economy, it has many applications which include energy purchasing, and generation, load switching, contract …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202—Market predictions or demand forecasting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA 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
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive 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
    • G05B13/027—Adaptive 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

Similar Documents

Publication Publication Date Title
Feinberg et al. Load forecasting
Park et al. Hybrid load forecasting for mixed-use complex based on the characteristic load decomposition by pilot signals
Fan et al. Short-term load forecasting based on an adaptive hybrid method
Osman et al. Neural network based approach for short-term load forecasting
Meng et al. A profit maximization approach to demand response management with customers behavior learning in smart grid
Islam Comparison of conventional and modern load forecasting techniques based on artificial intelligence and expert systems
Acakpovi et al. Time Series Prediction of Electricity Demand Using Adaptive Neuro‐Fuzzy Inference Systems
Ruan et al. Estimating demand flexibility using Siamese LSTM neural networks
Campbell et al. Methodologies for load forecasting
Perçuku et al. Big data and time series use in short term load forecasting in power transmission system
Hojjatinia et al. Peak shaving impact on load forecasting: A strategy for mitigation
Aggarwal et al. Short term price forecasting in deregulated electricity markets: A review of statistical models and key issues
Abrishami et al. Using real-world store data for foot traffic forecasting
Almeida et al. Hierarchical time series forecast in electrical grids
Bareth et al. Load forecasting model using LSTM for Indian state load dispatch centre
Hassan et al. Electricity load and price forecasting with influential factors in a deregulated power industry
Öztürk et al. Short term load forecasting for Turkey energy distribution system with artificial neural networks
Minhas et al. Short term load forecasting using hybrid adaptive fuzzy neural system: The performance evaluation
Okoye et al. A theoretical framework for enhanced forecasting of electrical loads
Akasiadis et al. Predicting agent performance in large-scale electricity demand shifting
Teferra et al. Fuzzy‐Swarm Intelligence‐Based Short‐Term Load Forecasting Model as a Solution to Power Quality Issues Existing in Microgrid System
Konica et al. Forecasting next-day the electricity demand based on fuzzy logic method case for Albania
Brierley et al. Data mining with neural networks-an applied example in understanding electricity consumption patterns
Daraghmi et al. Accurate and time‐efficient negative binomial linear model for electric load forecasting in IoE
Yuill et al. Application of Adaptive Neuro Fuzzy Inference System (ANFIS) based short term load forecasting in South African power networks