FELM based Intelligent Optimal Switching Capacitor Placement
Minimizing the total active power loss and voltage drop are the two important challenges for power transmission and distribution in an unbalanced power flow problem for any power distribution system. This can be achieved by installing the proper sized switching capacitor at proper place in a power distribution system. This paper deals with the design of distributed power systems and optimal switching capacitor placements based on the Fuzzy-Extreme Learning Machine (FELM). The intelligent power automation system requires fast determination of site and size of the switchable capacitors in the system bus through the centralized control units based on the system load. But in case of conventional, ANN and other models available on the literature they are time consuming and less performing under a dynamic environment To overcome this problem, we propose FELM mechanism to obtain an optimal switching capacitor placement in power distributed system. Fuzzy logic and its inference systems are used in ELM and the resultant FELM is to be used to find the site and size dynamically. Finally, the results are compared with a standard 34-bus test system with other models, with respect to the capacitor placement on the networks, savings and the computational time.
Fuzzy Logic Extreme Learning Machine Artificial Neural Networks (ANN) Power Flow Problem Intelligent power automation system component
K.S.Ravichandran Salem Saleh Saeed Alsheyuhi
School of Computing SASTRA University, Thanjavur-613401, India University of Aden, Republic of Yemen
国际会议
上海
英文
370-375
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）