Short-Term Load Forecasting by Artificial Intelligent Technologies

Short-Term Load Forecasting by Artificial Intelligent Technologies

In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency...

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Detalles Bibliográficos
Otros Autores: Wei-Chiang Hong (Ed.) (auth), Guo-Feng Fan (Ed.), Ming-Wei Li (Ed.)
Formato: Libro electrónico
Idioma:Inglés
Publicado: MDPI - Multidisciplinary Digital Publishing Institute 2019
Materias:
meta-heuristic algorithms
artificial neural networks (ANNs)
knowledge-based expert systems
statistical forecasting models
evolutionary algorithms
short term load forecasting
novel intelligent technologies
support vector regression/support vector machines
seasonal mechanism
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009430903806719

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