Optimal reactive power flow using multi-objective mathematical programming

被引:42
|
作者
Ara, A. Lashkar [1 ]
Kazemi, A. [2 ]
Gahramani, S. [1 ]
Behshad, M. [1 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Dezful Branch, Dezful, Iran
[2] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
关键词
Optimal reactive power flow (ORPF); Multi-objective optimization; MINLP; OA/ER/AP algorithm; PARTICLE SWARM OPTIMIZATION; INTERIOR-POINT METHOD; GENETIC ALGORITHM; DIFFERENTIAL EVOLUTION; VOLTAGE SECURITY; DISPATCH; DECOMPOSITION; DEVICES; SYSTEMS;
D O I
10.1016/j.scient.2012.07.010
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a multi-objective optimization methodology to solve the Optimal Reactive Power Flow (ORPF) problem. The epsilon-constraint approach is implemented for the Multi-objective Mathematical Programming (MMP) formulation. The solution procedure uses Mixed Integer Non-Linear Programming (MINLP) model due to discrete variables, such as the tap settings of transformers and the reactive power output of capacitor banks. The optimum tap settings of transformers are directly determined in terms of the admittance matrix of the network since the admittance matrix is constructed in the optimization framework as additional equality constraints. The optimization problem is modeled in General Algebraic Modeling System (GAMS) software and solved using DICOPT solver. Simulation results are implemented on the IEEE 14-, 30-, and 118-bus test systems to simultaneously optimize the total fuel cost, power losses and the system loadability as objective functions. The simulation results show that the proposed algorithm is suitable and effective for the reactive power planning. (C) 2012 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.
引用
收藏
页码:1829 / 1836
页数:8
相关论文
共 50 条
  • [21] Multi-objective optimization of reactive power flow using demand profile classification
    He, R
    Taylor, GA
    Song, YH
    [J]. 2005 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS, 1-3, 2005, : 363 - 369
  • [22] Optimal stochastic power flow using enhanced multi-objective mayfly algorithm
    Zhu, Jianjun
    Zhou, Yongquan
    Wei, Yuanfei
    Luo, Qifang
    Huang, Huajuan
    [J]. HELIYON, 2024, 10 (05)
  • [23] Multi-objective Optimal Power Flow Using Biogeography-based Optimization
    Roy, P. K.
    Ghoshal, S. P.
    Thakur, S. S.
    [J]. ELECTRIC POWER COMPONENTS AND SYSTEMS, 2010, 38 (12) : 1406 - 1426
  • [24] Solution of multi-objective optimal power flow using gravitational search algorithm
    Bhattacharya, A.
    Roy, P. K.
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2012, 6 (08) : 751 - 763
  • [25] Multi-objective Optimal Power Flow Using Fuzzy Satisfactory Stochastic Optimization
    Muangkhiew, Prakaipetch
    Chayakulkheeree, Keerati
    [J]. INTERNATIONAL ENERGY JOURNAL, 2022, 22 (03): : 281 - 290
  • [26] Multi-objective optimisation of reactive power flow in balancing market
    He, R
    Bie, ZH
    Song, YH
    Nakanishi, Y
    Nakazawa, C
    [J]. UPEC 2004: 39TH INTERNATIONAL UNIVERSITITIES POWER ENGINEERING CONFERENCE, VOLS 1-3, CONFERENCE PROCEEDINGS, 2005, : 1125 - 1129
  • [27] Multi-objective optimal reactive power flow including voltage security and demand profile classification
    He, R.
    Taylor, G. A.
    Song, Y. H.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (05) : 327 - 336
  • [28] Multi-objective fuzzy chance constrained optimal reactive power flow based on credibility theory
    Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan
    250061, China
    不详
    210019, China
    [J]. Diangong Jishu Xuebao, 21 (82-89):
  • [29] Multi-objective optimal power flow with stochastic wind and solar power
    Li, Shuijia
    Gong, Wenyin
    Wang, Ling
    Gu, Qiong
    [J]. APPLIED SOFT COMPUTING, 2022, 114
  • [30] Optimal Allocation of FACTS Devices by Using Multi-Objective Optimal Power Flow and Genetic Algorithms
    Ippolito, Lucio
    La Cortiglia, Antonio
    Petrocelli, Michele
    [J]. INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2006, 7 (02): : 1 - 19