Multi-objective Shark Smell Optimization for Solving the Reactive Power Dispatch Problem

被引:0
|
作者
Bagheri, Mehdi [1 ]
Sultanbek, Adilet [1 ]
Abedinia, Oveis [2 ]
Naderi, Mohammad Salay [3 ]
Naderi, Mehdi Salay [4 ]
Ghadimi, Noradin [5 ]
机构
[1] Nazarbayev Univ, Elect & Comp Engn Dept, Astana 010000, Kazakhstan
[2] Budapest Univ Technol & Econ, Dept Elect Power Engn, Budapest, Hungary
[3] Islamic Azad Univ, Tehran North Branch, Elect & Comp Engn Dept, Tehran, Iran
[4] Amirkabir Univ Technol, Iran Grid Secure Operat Res Ctr, Tehran, Iran
[5] Islamic Azad Univ, Young Researchers & Elite Club, Ardabil Branch, Ardebil, Iran
关键词
Reactive power dispatch; Strength Pareto; MOSSO; generation unit constraints; FLOW;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a new multi-objective shark smell optimization (MOSSO) algorithm is proposed for solving the reactive power dispatch problem based on operational constraints of the generators. This multi-objective problem applied to discovery the settings of continuous as well as discrete control parameters i.e., tap location of tap changing transformers, voltage of generator, and the reactive compensation devices value to solve three objectives at the same time as: voltage deviation, the total voltage stability and real power loss. To improve the abilities of proposed optimization algorithm a Pareto dominance is considered to provide and sort the dominated and non-dominated solutions. Effectiveness of the proposed approach is applied on different test cases and demonstrated through comparing its performance with other algorithms. The results confirm the proposed algorithm great potential in handling the multi objective problems in power systems.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] A Multi-objective Optimization Method for Power System Reactive Power Dispatch
    Zhang, Congyu
    Chen, Minyou
    Luo, Ciyong
    2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2010, : 6 - 10
  • [2] Improved genetic algorithm for multi-objective reactive power dispatch problem
    Devaraj, D.
    EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, 2007, 17 (06): : 569 - 581
  • [3] Multi-objective optimization of reactive power dispatch problem using fuzzy tuned mayfly algorithm
    Gangil, Gaurav
    Goyal, Sunil Kumar
    Saraswat, Amit
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 249
  • [4] A New Multi-objective Particle Swarm Optimization for Reactive Power Dispatch
    Bilil, Hasnae
    Ellaia, Rachid
    Maaroufi, Mohamed
    2012 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS), 2012, : 1119 - 1124
  • [5] Multi-objective ant lion optimization algorithm to solve large-scale multi-objective optimal reactive power dispatch problem
    Mouassa, Souhil
    Bouktir, Tarek
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2019, 38 (01) : 304 - 324
  • [6] A multi-objective optimization for power economic dispatch
    Chiang, Chao-Lung
    Chai, Chang-Wei
    2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, : 1587 - +
  • [7] Multi-objective Optimization of Reactive Power Dispatch in Power Systems via SPMGSO Algorithm
    Etehad, Mohammad Mohsen
    Siahkali, Hassan
    2017 SMART GRID CONFERENCE (SGC), 2017,
  • [8] Multi-objective optimization of reactive power dispatch using a bacterial swarming algorithm
    Lu Zhen
    Li Mengshi
    Tang Wenjia
    Wu, Q. H.
    PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 3, 2007, : 460 - +
  • [9] Multi-objective optimal reactive power dispatch using multi-objective differential evolution
    Basu, M.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 82 : 213 - 224
  • [10] Pareto Front of Multi-objective Optimal Reactive Power Dispatch
    Zhang, Cong
    Chen, Haoyong
    Xu, Xuanhao
    Cai, Runqing
    2014 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (IEEE PES APPEEC), 2014,