Solar/Wind Forecasting to Increase the Reliability of the RE System

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Details

Solar and wind energy are the most widely used renewable energy resources. Its availability varies from season to season, day to day, and even within a day itself. Due to this variability, forecasting large solar PV power and wind power plants becomes necessary. A reasonably reliable forecast is an important input to the state load dispatch centers for scheduling power generation by various sources of energy. Solar forecasting is used to minimize the uncertainty in a solar-based power generation system as solar energy is dependent on weather data (i.e. temperature and irradiance) as well as the day/night cycle. Wind forecasting of variable wind resources helps in generation scheduling and results in an increased and reliable generation.

Autorentext
Rejo Roy and Albert John Varghese are academicians in Electrical Engineering. They have been contributing to engineering education for over a decade. Their areas of interest majorly include the use of Artificial Intelligence in the field of Electrical Engineering and also Renewable Energy.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786205640319
    • Genre Electrical Engineering
    • Sprache Englisch
    • Anzahl Seiten 140
    • Herausgeber LAP LAMBERT Academic Publishing
    • Größe H220mm x B150mm x T9mm
    • Jahr 2023
    • EAN 9786205640319
    • Format Kartonierter Einband
    • ISBN 6205640317
    • Veröffentlichung 24.01.2023
    • Titel Solar/Wind Forecasting to Increase the Reliability of the RE System
    • Autor Rejo Roy , Albert John Varghese
    • Untertitel Approach using Artificial Neural Networks based on Heuristic Algorithm
    • Gewicht 227g

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