A Computationally Efficient Evolutionary Algorithm for Stochastic D-FACTS Optimization

被引:0
|
作者
Fatule, Eduardo J. Castillo [1 ]
Espiritu, Jose F. [1 ]
Taboada, Heidi [1 ]
Sang, Yuanrui [2 ]
机构
[1] Univ Texas El Paso, Ind Mfg & Syst Engn Dept, El Paso, TX 79968 USA
[2] Univ Texas El Paso, Elect & Comp Engn Dept, El Paso, TX 79968 USA
关键词
Distributed flexible AC transmission systems (D-FACTS); evolutionary algorithm; metaheuristics; optimal allocation; stochastic optimization; DISTRIBUTED FACTS; PERFORMANCE;
D O I
10.1109/NAPS50074.2021.9449797
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
Flexible AC transmission systems (FACTS) are important contributors to smart transmission systems. They can offer a level of power flow control and improve transfer capability of an existing network which can be used to mitigate congestion and integrate renewable energies into a grid. Distributed FACTS is a lightweight version of FACTS which can be redeployed conveniently. It has become a more attractive power flow control technology due to its lower cost and ease of installation. This paper proposes a novel evolutionary algorithm to solve a stochastic model for D-FACTS allocation, studying their impacts on operating costs and the computational efficiency of the model. The results are presented are compared against a previously developed linear programming model and show a positive economic impact from the use of D-FACTS, as well as a significant reduction in computational time for this type of model.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] An Adaptive D-FACTS for Power Quality Enhancement in an Isolated Microgrid
    Elmetwaly, Ahmed Hussain
    Eldesouky, Azza Ahmed
    Sallam, Abdelhay Ahmed
    [J]. IEEE ACCESS, 2020, 8 : 57923 - 57942
  • [22] Implementation of distributed compensation in the transmission lines design (D-FACTS)
    Santander-Hernandez, Laura J.
    Angeles-Camacho, Cesar
    [J]. 2015 IEEE THIRTY FIFTH CENTRAL AMERICAN AND PANAMA CONVENTION (CONCAPAN XXXV), 2015,
  • [23] A stochastic framework for computationally efficient fail-safe topology optimization
    Zhang, Yiming
    Zhang, Hongyi
    Qiu, Lemiao
    Wang, Zili
    Zhang, Shuyou
    Qiu, Na
    Fang, Jianguang
    [J]. ENGINEERING STRUCTURES, 2023, 283
  • [24] D-FACTS技术及电能质量的改善
    翁利民
    陈允平
    刘琨
    [J]. 电力电容器与无功补偿, 2005, (02) : 1 - 5
  • [25] Using D-FACTS in Microgrids for Power Quality Improvement: A Review
    Urquizo, Javier
    Singh, Pritpal
    Kondrath, Nisha
    Hidalgo-Leon, Ruben
    Soriano, Guillermo
    [J]. 2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [26] AN EFFICIENT EVOLUTIONARY ALGORITHM FOR A SHAPE OPTIMIZATION PROBLEM
    Nachaoui, M.
    Chakib, A.
    Nachaoui, A.
    [J]. APPLIED AND COMPUTATIONAL MATHEMATICS, 2020, 19 (02) : 220 - 244
  • [27] A high efficient evolutionary algorithm for function optimization
    Xie, Datong
    Kang, Lishan
    Li, Chengjun
    Du, Xin
    [J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 634 - 639
  • [28] AN ALGORITHM FOR EVOLUTIONARY STOCHASTIC PORTFOLIO OPTIMIZATION WITH PROBABILISTIC CONSTRAINTS
    Hochreiter, Ronald
    [J]. 16TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MENDEL 2010, 2010, : 1 - 6
  • [29] An efficient evolutionary algorithm for multiobjective optimization problems
    Chen, Wei-Mei
    Lee, Wei-Ting
    [J]. 2007 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING, VOLS 1 AND 2, 2007, : 30 - 33
  • [30] An efficient dynamical evolutionary algorithm for global optimization
    Zou, XF
    Li, YX
    Kang, LS
    Wu, ZJ
    [J]. INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2003, 80 (11) : 1429 - 1436