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Power grid operation optimization and forecasting using a combined forecasting system
Authors:Lifang Zhang  Jianzhou Wang  Zhenkun Liu
Affiliation:School of Statistics, Dongbei University of Finance and Economics, Dalian, China
Abstract:Reliable photovoltaic and wind power generation forecasts are essential for efficient power systems operations. A combined forecasting system is developed, which integrates a data preprocessing method, a sub-predictor selection rule, and a multi-objective optimization to integrate various forecasting models. The proposed system effectively aggregates the advantages of all algorithms involved, facilitating greater prediction precision and stability. Experiments indicated that the proposed system can achieve higher quality point and interval forecasting performance relative to the comparative approaches.
Keywords:artificial intelligence  combined forecasting  multi-objective chimp optimization algorithm  photovoltaic and wind power generation forecasting
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