Distributed PV power forecasting using genetic algorithm based neural network approach

• Published in: International Conference on Advanced Mechatronic Systems pp. 557 - 560
• Main Authors: Tao, Yuqi, Chen, Yuguo
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.08.2014
• Subjects: Biological neural networks; Computer simulation; Conferences; Distributed PV power forecasting; Electric power distribution; Forecasting; genetic algorithm; Genetic algorithms; neural network; Neural networks; Photovoltaic cells; Photovoltaic systems; Predictive models; Solar cells; Strategy
• ISSN: 2325-0682; 2325-0690
• DOI: 10.1109/ICAMechS.2014.6911608

In this paper, a distributed photovoltaic (PV) power forecasting method is proposed by using genetic algorithm based neural network approach. With the large-scale application of PV power generation in the applications of society, and the characteristic of volatility and intermittent, and power forecasting of PV distributed have played a more important role in research of control strategies for microgrid and the dispatch of grid power and improvement of power quality. This paper mainly use genetic algorithm to optimize the weights and thresholds of BP Neural Network, which improves the forecasting accuracy of BP Neural Network of forecasting model. The effectiveness of the proposed method is confirmed by the simulation results of distributed PV power forecasting.