Title :
Reconfiguration and Capacitor Placement Simultaneously for Energy Loss Reduction Based on an Improved Reconfiguration Method
Author :
Farahani, Vahid ; Vahidi, Behrooz ; Abyaneh, Hossein Askarian
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
fDate :
5/1/2012 12:00:00 AM
Abstract :
Network reconfiguration and capacitor placement have been widely employed to reduce power losses and maintain voltage profiles within permissible limits in distribution systems. Reconfiguration method proposed in this paper is based on a simple branch exchange method of single loop. In this simple method of branch exchange, loops selection sequence affects the optimal configuration and the network loss. Therefore, this method has been improved by optimizing the sequence of loops selection for minimizing the energy losses in this paper. Also, a joint optimization algorithm is proposed for combining this improved method of reconfiguration and capacitor placement and therefore maximum loss reduction. For more practical application of the proposed method, different load patterns are considered and a fast method of total energy loss calculation is employed for the economic optimization of energy losses during the planning horizon. Discrete genetic algorithm (GA) is used to optimize the location and size of capacitors and the sequence of loops selection. In fact, the capacitor sizes have been considered as discrete variables. Simulated annealing (SA) is also applied to compare the performance of convergence. The proposed algorithm is effectively tested on a real life 77-bus distribution system with four different kinds of load patterns.
Keywords :
genetic algorithms; power capacitors; power distribution economics; power distribution planning; simulated annealing; 77-bus distribution system; SA; capacitor placement; discrete GA; discrete genetic algorithm; economic optimization algorithm; energy loss calculation; energy loss reduction; improved network reconfiguration method; loops selection sequence; power loss reduction; simulated annealing; single loop branch exchange method; Biological cells; Capacitors; Energy loss; Genetic algorithms; Joints; Optimization; Planning; Capacitor placement; discrete genetic algorithm; distribution network optimization; energy loss reduction; reconfiguration;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2011.2167688