Title :
Dispatch distributed generation and load forecasting by GSO algorithm and natural network optimized by genetic
Author :
Li Xintong ; Teng Fei ; Li Yushuai ; He Zhiqiang ; Wang Yingnan
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
This paper mainly discuss a problem that how to optimize the ways on electric system dispatching. The GSO algorithm and natural network optimized by genetic are used to solve the problem. The distributed generations and the loads can be seen as producer, requester and random dispersion members which is in the nature. Due to the electric system is a dynamic system, the load forecasting must be done by the natural network. This algorithm is optimized by genetic algorithm to solve the problem that need lots of data. Through previous algorithm can solve the electric system dispatching problem.
Keywords :
distributed power generation; genetic algorithms; load forecasting; power generation dispatch; GSO algorithm; dispatch distributed generation; electric system dispatching; genetic algorithm; load forecasting; natural network; producer members; random dispersion members; requester members; Distributed power generation; Genetic algorithms; Genetics; Heuristic algorithms; Linear programming; Sociology; Statistics; dispatch; distributed generation; electric system; genetic algorithm; natural network;
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
DOI :
10.1109/CAC.2013.6775847
