Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty
详细信息 查看全文
- 作者：Mobin Esmaeilia ; Mostafa Sedighizadeha ; Masoud Esmailib ; msdesmaili@gmail.com" class="auth_mail" title="E-mail the corresponding author ; esmaili.m@wtiau.ac.ir" class="auth_mail" title="E-mail the corresponding author
- 关键词：Distribution system reconfiguration ; Distributed generation ; Multi-objective optimization ; Multi-objective Hybrid Big Bang-Big Crunch algorithm ; Loads fuzzy modeling ; Pareto optimal solution
- 刊名：Energy
- 出版年：2016
- 出版时间：15 May 2016
- 年：2016
- 卷：103
- 期：Complete
- 页码：86-99
- 全文大小：1268 K
文摘
- •
Pareto solutions of MOHBB-BC have higher quality and more diversified than MOPSO.
- •
Load uncertainty leads to more realistic solution but with 4.5% more losses.
- •
Mutation in HBB-BC makes it have better exploration and speed than fuzzy BA and HAS.