A Review of Soft Computing Techniques in Short-Term Load Forecasting
نویسنده
چکیده
Load forecasting plays a significant role in power systems and smart buildings in efficient planning, distribution and management of power. Various exogenous and meteorological factors, gave made accurate load forecasting complex making it a challenging task. In recent years, the research on shortterm power load forecasting has become inevitable for the reliable and efficient functioning of power systems. This paper discusses different soft computing techniques such as neural network, fuzzy logic and genetic algorithms for the short term load forecasting.
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