A new evolutionary-analytical two-step optimization method for optimal wind turbine allocation considering maximum capacity

被引:9
|
作者
Nematollahi, A. Foroughi [1 ]
Rahiminejad, A. [2 ]
Vahidi, B. [1 ]
Askarian, H. [1 ]
Safaei, A. [1 ]
机构
[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran 1591634311, Iran
[2] Esfarayen Univ Technol, Dept Elect & Comp Sci, Esfarayen 9661998195, North Khorasan, Iran
关键词
DISTRIBUTED GENERATION PLACEMENT; PARTICLE SWARM OPTIMIZATION; OPTIMAL DG PLACEMENT; DISTRIBUTION NETWORKS; DISTRIBUTION-SYSTEMS; ELECTRICITY MARKET; ALGORITHM; ENERGY; UNITS; RESOURCES;
D O I
10.1063/1.5043403
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this paper, a new two-step optimization algorithm is introduced for optimal placement of a Wind Turbine Generator (WTG) in a distribution network. The locations and the maximum capacities of WTGs, as well as their optimum power factor, are determined simultaneously in two different steps. In the first step, the locations and power factors of the WTGs are considered as solutions of a metaheuristic optimization algorithm and in the next step, the optimal capacities of the WTGs are determined analytically. A recently introduced optimization algorithm known as the Lightning Attachment Procedure Optimization algorithm is employed for the first step, and a fast analytical method is used for the second one. The objective function of the optimization problem is considered for annual energy loss minimization. The proposed approach is applied on 85-bus test system, and the results are discussed. Fast convergence, best global answer finding, and robustness are the characteristics of the proposed method, which are concluded from the results and discussion. Published by AIP Publishing.
引用
收藏
页数:18
相关论文
共 24 条
  • [1] A two step optimization algorithm for wind turbine generator placement considering maximum allowable capacity
    Safaei, A.
    Vahidi, B.
    Askarian-Abyaneh, H.
    Azad-Farsani, E.
    Ahadi, S. M.
    [J]. RENEWABLE ENERGY, 2016, 92 : 75 - 82
  • [2] Two-Step Optimization for Wind Turbine Blade With Probability Approach
    Lee, Ki-Hak
    Kim, Kyu-Hong
    Lee, Dong-Ho
    Lee, Kyung-Tae
    Park, Jong-Po
    [J]. JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2010, 132 (03): : 0345031 - 0345035
  • [3] Installed capacity optimization of wind turbine generators considering maximum economic benefit of wind farm
    Zhang, Xu
    Luo, Xianjue
    Zhao, Zheng
    Wang, Kaiyan
    [J]. Dianwang Jishu/Power System Technology, 2012, 36 (01): : 237 - 240
  • [4] A Two-Step Method for Nonlinear Polynomial Model Identification Based on Evolutionary Optimization
    Cheng, Yu
    Wang, Lan
    Hu, Jinglu
    [J]. 2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 612 - 617
  • [5] Optimal Evolutionary Wind Turbine Placement in Wind Farms Considering New Models of Shape, Orography and Wind Speed Simulation
    Saavedra-Moreno, B.
    Salcedo-Sanz, S.
    Paniagua-Tineo, A.
    Gascon-Moreno, J.
    Portilla-Figueras, J. A.
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2011, PT I, 2011, 6691 : 25 - 32
  • [6] Zonotope-based method for optimal allocation of wind capacity in microgrids considering generation uncertainty
    Gao, Jianing
    Han, Bei
    Zhang, Lijun
    Xu, Chenbo
    Li, Guojie
    Feng, Lin
    Wang, Keyou
    [J]. IET RENEWABLE POWER GENERATION, 2019, 13 (16) : 2994 - 3001
  • [7] A two-step multi-objectivization method for improved evolutionary optimization of industrial problems
    Syberfeldt, Anna
    Rogstrom, Joel
    [J]. APPLIED SOFT COMPUTING, 2018, 64 : 331 - 340
  • [8] A new two-step iterative method for optimal reduction of linear SISO systems
    Hwang, CY
    Hwang, JH
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 1996, 333B (05): : 631 - 645
  • [9] Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil
    Sunwoong Yang
    Sanga Lee
    Kwanjung Yee
    [J]. Engineering with Computers, 2023, 39 : 2239 - 2255
  • [10] Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil
    Yang, Sunwoong
    Lee, Sanga
    Yee, Kwanjung
    [J]. ENGINEERING WITH COMPUTERS, 2023, 39 (03) : 2239 - 2255