期刊
APPLIED SOFT COMPUTING
卷 68, 期 -, 页码 322-342出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.asoc.2018.04.006
关键词
Multi-objective dimension-based firefly algorithm (MODFA); Multi-objective optimal power flow (MOOPF) problem; Constrained Pareto-dominant approach (CPA); Dimension-based technology (DT); Performance metrics
资金
- Innovation Team Program of Chongqing Education Committee [CXTDX201601019]
- Chongqing University [KJTD201312]
- Foundation of Chongqing University of Posts and Telecommunications [A2017-15, A2017-74]
- National Natural Science Foundation of China [51207064, 61773083, 61463014]
In this paper, a new multi-objective dimension-based firefly algorithm (MODFA) is proposed for solving the constrained multi-objective optimal power flow (MOOPF) problem with multiple and contradictory objectives in power systems. In our suggested MODFA algorithm, a constrained Pareto-dominant approach (CPA) is offered for guaranteeing zero violations of various inequality constraints on state variables in the constrained MOOPF problem. In addition to that, the CPA and the dimension-based technology (DT) are federated together to update the information of the non-dominant firefly to speed up the convergence of multiple target search. Crowding distance and non-dominated sorting based on the violation of constraints are also regarded as measures to sustain well-distributed Pareto optimal solution (POS) set. Furthermore, a fuzzy affiliation is utilized to pick the best compromise solution (BCS) from the obtained POS. The IEEE30-bus system, the IEEE57-bus system, and the IEEE118-bus system with nine cases are implemented to validate the performance of the proposed MODFA by considering the active power losses, the emission, and the total fuel cost. The numerous simulation results optimized by the MODFA, which are compared with frequently-used NSGA-III, NSGA-II, and MOPSO algorithm, show the capability of the MODFA for obtaining POS with uniform distribution and high quality. Additionally, three performance metrics are considered to evaluate approximation, distribution, and diversity of POS found by MODFA. (C) 2018 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据