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
  • [1] Antenna Optimization With a Computationally Efficient Multiobjective Evolutionary Algorithm
    John, Matthias
    Ammann, Max J.
    [J]. IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2009, 57 (01) : 260 - 263
  • [2] A computationally efficient evolutionary algorithm for real-parameter optimization
    Deb, K
    Anand, A
    Joshi, D
    [J]. EVOLUTIONARY COMPUTATION, 2002, 10 (04) : 371 - 395
  • [3] A Computationally Efficient Evolutionary Algorithm for Multiobjective Network Robustness Optimization
    Wang, Shuai
    Liu, Jing
    Jin, Yaochu
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2021, 25 (03) : 419 - 432
  • [4] A Summary of Applications of D-FACTS on Microgrid
    Wang, Jing
    Wang, Zhiqi
    Xu, Lingling
    Wang, Zongli
    [J]. 2012 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2012,
  • [5] Multi-area distribution grids optimization using D-FACTS devices by M-PSO algorithm
    Zanganeh, Mohsen
    Moghaddam, Mahmoud Samiei
    Azarfar, Azita
    Vahedi, Mojtaba
    Salehi, Nasrin
    [J]. ENERGY REPORTS, 2023, 9 : 133 - 147
  • [6] Computationally Efficient Algorithm in Cluster Geometry Optimization
    Sarkar, Kanchan
    Bhattacharyya, S. P.
    [J]. SOLID STATE PHYSICS, VOL 57, 2013, 1512 : 162 - 163
  • [7] Computationally efficient stochastic optimization using multiple realizations
    Bayer, P.
    Buerger, C. M.
    Finkel, M.
    [J]. ADVANCES IN WATER RESOURCES, 2008, 31 (02) : 399 - 417
  • [8] Economic Benefit Comparison of D-FACTS and FACTS in Transmission Networks with Uncertainties
    Sang, Yuanrui
    Sahraei-Ardakani, Mostafa
    [J]. 2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2018,
  • [9] Interaction Analysis of Multi-Function FACTS and D-FACTS Controllers by MRGA
    Mokhtari, Maghsood
    Khazaie, Javad
    Nazarpour, Daryoush
    Farsadi, Morteza
    [J]. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2013, 21 (06) : 1685 - 1702
  • [10] Incorporation of D-FACTS devices in the Mexican equivalent network
    Santander-Hernandez, Laura J.
    Fuerte-Esquivel, Claudio R.
    Angeles-Camacho, Cesar
    [J]. PROCEEDINGS OF THE XXII 2020 IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC 2020), VOL 4, 2020,