Predicting Short-Term Photovoltaic Power Station Output Using Combination of Fruit Fly Optimization Algorithm and an Improved Adaptive Genetic Algorithm
Author:
Affiliation:
1. North China Electric Power University,Department of Electrical Engineering,Baoding,China
2. State Grid Zhumadian Power Supply Company,Department of Huancheng Power Supply,Zhumadian,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593251.pdf?arnumber=10593251
Reference13 articles.
1. Global prospects, progress, policies, and environmental impact of solar photovoltaic power generation
2. An intelligent optimization method of motion management system based on BP neural network
3. Review on Photovoltaic Power and Solar Resource Forecasting: Current Status and Trends
4. Predict the effect of meteorological factors on haze using BP neural network
5. PV power conversion and short-term forecasting in a tropical, densely-built environment in Singapore
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