Neuro-fuzzy short-term forecasting model for PV plants optimized with genetic algorithm
نویسنده
چکیده
This paper presents a short-term forecasting model designed to forecast the hourly power production in a grid-connected photovoltaic plant. The model is based on neuro-fuzzy systems optimized with the use of a genetic algorithm. The model uses as inputs forecasted weather variables obtained with a meso-scale numerical weather prediction model. The model was applied to forecast the hourly production of a real-life photovoltaic plant for all the following day. The model can be applied to provide forecast to be use to prepare energy sale bids to the electricity market, and to select the hours to take place maintenance tasks in the PV plant. Key-Words: Solar power, photovoltaic plant, power generation, short-term forecasting
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