Neural network based estimation of maximum power generation from PV module using environmental information
- Kumamoto Univ. (Japan). Dept. of Electrical Engineering and Computer Science
This paper presents an application of artificial neural network for the estimation of maximum power generation from the PV module. The output power from the PV module depends on the environmental factors such as irradiation, and cell temperature. For the operation planning of power systems, the prediction of the power generation is inevitable for the PV systems. For this purpose, irradiation, temperature, and wind velocity are utilized as the input information to the proposed neural network. The output is the predicted maximum power generation under the condition given by those environmental factors. Efficiency of the proposed estimation scheme is evaluated by using the actual data on daily, monthly, and yearly bases. The proposed method gives highly accurate prediction compared with the prediction by using the conventional multiple regression model.
- OSTI ID:
- 533096
- Journal Information:
- IEEE Transactions on Energy Conversion, Vol. 12, Issue 3; Other Information: DN: Paper presented at the IEEE/PES Summer Meeting, July 28--August 1, 1996, Denver, CO (US); PBD: Sep 1997
- Country of Publication:
- United States
- Language:
- English
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