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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mori, H. Yamada, Y. |
| Copyright Year | 2007 |
| Description | Author affiliation: Dept. of Electron. & Bioinf., Meiji Univ., Kawasaki (Mori, H.) |
| Abstract | This paper proposes a new method for distribution network expansion planning. The proposed method is based on SPEA2 (strength Pareto evolutionary algorithm 2) of multi-objective meta-heuristics. As power systems are deregulated, the power market becomes more competitive. Hence, the cost minimization has been recognized as one of the most important factors in distribution systems. Apart from the cost minimization, the network loss minimization and the power quality are also important. This paper focuses on distribution network expansion planning under new environment with distribution generations (DG). It needs to deal with multi-objective optimization. In this paper, SPEA2 that is effective for evaluating the Pareto solution set is used to solve the multi-objective network expansion planning problem. It has advantage in finding out a set of Pareto solutions with the strategies of using both the archives and the evaluated solution set. The proposed method is successfully applied to the 69-node distribution system with DG units. |
| Starting Page | 374 |
| Ending Page | 379 |
| File Size | 403918 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424421893 |
| DOI | 10.1109/PCT.2007.4538346 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-01 |
| Publisher Place | Switzerland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Power system planning Costs Optimization methods Evolutionary computation Power system security Constraint optimization Pareto optimization Power markets Power quality Substations Strength Pareto Evolutionary Algorithm 2 Multi-objective optimization Distribution network expansion planning |
| Content Type | Text |
| Resource Type | Article |
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