Research on Improved Bat Algorithm for Multi-objective Optimal Power Flow Problem

被引：0
|
作者：
Chen, Gonggui [1 ]
Qian, Jie [1 ]
Zhang, Zhizhong [2 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Key Lab Commun Network & Testing Technol, Chongqing, Peoples R China
来源：
2018 CHINESE AUTOMATION CONGRESS (CAC) | 2018年
关键词：
MOIBA algorithm; MOOPF problem; PDM; DISPATCH;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To handle multi-objective optimal power flow (MOOPF) problem while satisfying various system constraints, a new multi-objective improved bat algorithm (MOIBA) is proposed. MOIBA algorithm can improve the shortcoming of basic bat algorithm which has weak global exploration and unsatisfactory diversity. To validate the performance of MOIBA algorithm, IEEE30 bus system is implemented on MATLAB software to optimize, respectively, power loss and fuel cost concurrently, emission and fuel cost concurrently, power loss and emission concurrently. A Pareto-dominant Method with constraint (PDM) is employed to satisfy inequality constraints of state variables. The results obtained by MOIBA algorithm, compared with MOPSO algorithm, show the effectiveness and superiority of proposed MOIBA algorithm in solving MOOPF problem.
引用
收藏
页码：1263 / 1268
页数：6
相关论文
共 50 条
  • [1] Improved multi-objective artificial bee colony algorithm for optimal power flow problem
    马连博
    胡琨元
    朱云龙
    陈瀚宁
    [J]. Journal of Central South University, 2014, 21 (11) : 4220 - 4227
  • [2] Improved Differential Evolution Algorithm to solve multi-objective of optimal power flow problem
    Al-Kaabi, Murtadha
    Al Hasheme, Jaleel
    Al-Bahrani, Layth
    [J]. ARCHIVES OF ELECTRICAL ENGINEERING, 2022, 71 (03) : 641 - 657
  • [3] Improved multi-objective artificial bee colony algorithm for optimal power flow problem
    Lian-bo Ma
    Kun-yuan Hu
    Yun-long Zhu
    Han-ning Chen
    [J]. Journal of Central South University, 2014, 21 : 4220 - 4227
  • [4] Improved multi-objective artificial bee colony algorithm for optimal power flow problem
    Ma Lian-bo
    Hu Kun-yuan
    Zhu Yun-long
    Chen Han-ning
    [J]. JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2014, 21 (11) : 4220 - 4227
  • [5] An Improved MOEA/D Algorithm for the Solution of the Multi-Objective Optimal Power Flow Problem
    Wu, Zhitao
    Liu, Hao
    Zhao, Jian
    Li, Zhiwu
    [J]. PROCESSES, 2023, 11 (02)
  • [6] Multi-objective harmony search algorithm for optimal power flow problem
    Sivasubramani, S.
    Swarup, K. S.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2011, 33 (03) : 745 - 752
  • [7] Multi-Objective Optimal Power Flow Solutions Using Improved Multi-Objective Mayfly Algorithm (IMOMA)
    Bhaskar, K. Vijaya
    Ramesh, S.
    Karunanithi, K.
    Raja, S. P.
    [J]. JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2023, 32 (12)
  • [8] A New Multi-objective Jaya Algorithm for Solving the Optimal Power Flow Problem
    Berrouk, F.
    Bouchekara, H. R. E. H.
    Chaib, A. E.
    Abido, M. A.
    Bounaya, K.
    Javaid, M. S.
    [J]. JOURNAL OF ELECTRICAL SYSTEMS, 2018, 14 (03) : 165 - 181
  • [9] Differential search algorithm for solving multi-objective optimal power flow problem
    Abaci, Kadir
    Yamacli, Volkan
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 79 : 1 - 10
  • [10] Application of improved bat algorithm in optimal power flow problem
    Yanbin Yuan
    Xiaotao Wu
    Pengtao Wang
    Xiaohui Yuan
    [J]. Applied Intelligence, 2018, 48 : 2304 - 2314
12345