Long-term Forecasting of Electrical Load using Gustafson-Kessel clustering algorithm on Takagi-Sugeno type MISO Neuro- Fuzzy network
نویسنده
چکیده
1.1. Problem definition: Neuro-Fuzzy Approach in Electrical Load Forecasting Modeling and identification of electrical load processes are essential for the operation and also planning of a utility either for a company or for a country. Electrical load forecasting is needed because people intend to make important decision on generating power generators, load switching, purchasing strategy and also infrastructure development. Furthermore, load forecasts are extremely important for energy suppliers, transmission, distribution and markets. In other words, load forecasts play a fundamental role in the formulation of economic, reliable and secure operating strategies for the power system.
منابع مشابه
Neuro-Fuzzy Approaches for Forecasting Electrical Load Using Additional Moving Average Window Data Filter on Takagi-Sugeno Type MISO Networks
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