Multi-objective optimal power flow model for power system operation dispatching

被引:0
|
作者
Tan, Shuwen [1 ]
Lin, Shunjiang [1 ]
Yang, Liuqing [1 ]
Zhang, Anqi [1 ]
Shi, Weiwei [1 ]
Feng, Hanzhong [1 ]
机构
[1] S China Univ Technol, Sch Elect Power Engn, Guangzhou 510641, Guangdong, Peoples R China
来源
2013 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2013年
关键词
Multi-objective optimal power flow; Pareto frontier; Normal Boundary Intersection method; optimal dispatching; Power system; OPTIMIZATION; ALGORITHM; SECURITY;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
For the basic requirements of power system operation of security, high quality, economy, environmental protection, a multi-objective optimal power flow(MOPF) model is established to minimize three objective functions of load buses voltage deviations, network active power loss, pollution gas emissions and meanwhile to satisfy the security constraints of power transmission limits in lines. The normal boundary intersection method (NBI) is adopted to transform three-objective optimal power flow model into a series of single-objective optimization model, and then the interior point method is used to obtain the evenly distributed Pareto frontier in objective functions space. According to fuzzy membership and entropy weight of various targets, the comprehensive compromise optimal solution can be identified from the Pareto frontier surface, which is employed as the operation dispatching scheme of the system. By the multi-objective optimization calculation of the IEEE 9-buses system and the IEEE 39-buses system, the results validate the effectiveness of the proposed model and algorithm, and indicate that the comprehensive compromised optimal solution can be used as an optimal dispatching scheme of power system operation.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] An efficient covexified SDP model for multi-objective optimal power flow
    Davoodi, Elnaz
    Babaei, Ebrahim
    Mohammadi-ivatloo, Behnam
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2018, 102 : 254 - 264
  • [2] Multi-objective optimal power flow model with TCSC for practical power networks
    Abdel-Moamen, MA
    Padhy, NP
    2004 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1 AND 2, 2004, : 686 - 690
  • [3] Multi-Objective Optimal Dispatching and Operation Control of a Grid Connected Microgrid Considering Power Loss of Conversion Devices
    Lagouir, Marouane
    Badri, Abdelmajid
    Sayouti, Yassine
    JOURNAL OF SUSTAINABLE DEVELOPMENT OF ENERGY WATER AND ENVIRONMENT SYSTEMS-JSDEWES, 2022, 10 (03):
  • [4] The Power System Multi-objective Optimization Dispatching Containing Virtual Power Plant
    Cheng, Huaxin
    Gao, Yajing
    Zhang, Jing
    Li, Ruihuan
    Liang, Haifeng
    2014 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2014, : 3316 - 3321
  • [5] Multi-objective Optimal Operation Incorporating Wind Power
    Shi, L. B.
    Wang, C.
    Yao, L. Z.
    Ni, Y. X.
    Masoud, B.
    2011 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2011,
  • [6] Optimal power flow solutions through multi-objective programming
    Salgado, R. S.
    Rangel, E. L., Jr.
    ENERGY, 2012, 42 (01) : 35 - 45
  • [7] Fuzzy optimal power flow with multi-objective based on artificial bee colony algorithm in power system
    He, Xuanhu
    Wang, Wei
    Wang, Yingnan
    Kong, Jun
    Geng, Jing
    Fan, Shengbin
    RENEWABLE ENERGY AND ENVIRONMENTAL TECHNOLOGY, PTS 1-6, 2014, 448-453 : 2473 - 2477
  • [8] Multi-objective Optimal Power Flow with Transient Stability Constraints
    Lu, Jin-ling
    Zhang, Qiang
    MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY, 2014, 556-562 : 2067 - 2071
  • [9] Multi-objective optimal power flow considering the system transient stability
    Abido, Mohamed Ali
    Ahmed, Muhammad Waqar
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2016, 10 (16) : 4213 - 4221
  • [10] Multi-objective optimal power flow with stochastic wind and solar power
    Li, Shuijia
    Gong, Wenyin
    Wang, Ling
    Gu, Qiong
    APPLIED SOFT COMPUTING, 2022, 114