Optimal Placement of FACTS Devices Using Modified Whale Optimization Algorithm for Minimization of Transmission Losses

被引:1
|
作者
Kar, Manoj Kumar [1 ]
Kanungo, Sanjeet [2 ]
Alsaif, Faisal [3 ]
Ustun, Taha Selim [4 ]
机构
[1] Tolani Maritime Inst, Dept Elect & Elect, Pune 410507, Maharashtra, India
[2] Tolani Maritime Inst, Marine Engn Dept, Pune 410507, Maharashtra, India
[3] King Saud Univ, Coll Engn, Dept Elect Engn, Riyadh 11421, Saudi Arabia
[4] AIST FREA, Fukushima Renewable Energy Inst, Koriyama 9630298, Japan
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Optimization; Mathematical models; Power system stability; Reactive power; Whale optimization algorithms; Propagation losses; Thyristors; Active power loss; load flow analysis; modified whale optimization algorithm; optimal placement; SVC; TCSC; REACTIVE POWER DISPATCH;
D O I
10.1109/ACCESS.2024.3458039
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel modified whale optimization algorithm (MWOA) is presented in this study to minimize transmission losses. The proposed method is used to determine the best control variables, such as reactive power generation, transformer tap settings, and reactive power sources. First, the power flow analysis method is used to determine where the flexible AC transmission system (FACTS) devices should be placed. To achieve the intended objectives, the suggested MWOA approach is applied on multiple IEEE standard test bus systems (IEEE-30, -57, and-118) at different active and reactive loading conditions. The shunt compensation was handled by a Static VAR compensator (SVC) while the series compensation was handled by a thyristor-controlled series compensator (TCSC). The results of applying the MWOA approach are shown and contrasted with those of other promising optimization techniques, including the sine cosine algorithm (SCA), whale optimization algorithm (WOA), moth flame optimization (MFO), grey wolf optimization (GWO), and particle swarm optimization (PSO). The proposed method significantly reduces the active power loss, i.e., 11.11 % in IEEE 30, 50.32 % in IEEE 57 and 15.17% in IEEE 118 bus system at base loading. Ultimately, a comprehensive study of the statistical data was conducted to validate the precision and robustness of the suggested methodology.
引用
收藏
页码:130816 / 130831
页数:16
相关论文
共 50 条
  • [41] Optimal Rescheduling of Generators to Alleviate Congestion in Transmission System: A Novel Modified Whale Optimization Approach
    Paul, Kaushik
    Dalapati, Poulami
    Kumar, Niranjan
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2022, 47 (03) : 3255 - 3279
  • [42] Optimal Rescheduling of Generators to Alleviate Congestion in Transmission System: A Novel Modified Whale Optimization Approach
    Kaushik Paul
    Poulami Dalapati
    Niranjan Kumar
    Arabian Journal for Science and Engineering, 2022, 47 : 3255 - 3279
  • [43] Optimal Location of FACTS Devices for Loadability Enhancement using Gravitational Search Algorithm
    Kumar, Lalit
    Kumar, Sanjay
    Gupta, Sushil Kumar
    Raw, Brijesh Kumar
    2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2019,
  • [44] Optimal power flow with FACTS devices using a Novel Grey Wolf Algorithm
    Singh, Madhu
    Dutta, Susanta
    Roy, Provas Kumar
    2017 THIRD INTERNATIONAL CONFERENCE ON SCIENCE TECHNOLOGY ENGINEERING & MANAGEMENT (ICONSTEM), 2017, : 501 - 506
  • [45] Optimal parameter estimation of 1-phase and 3-phase transmission line for various bundle conductor's using modified whale optimization algorithm
    Shaikh, Muhammad Suhail
    Hua, Changchun
    Raj, Saurav
    Kumar, Shubash
    Hassan, Mannan
    Ansari, Muhammad Mohsin
    Jatoi, Munsif Ali
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 138
  • [46] FACTS Devices Optimization for Optimal Power Flow Using Particle Swarm Optimization In Sulselrabar System
    Saini, Makmur
    Djalal, Muhammad Ruswandi
    Yunus, A. M. Shiddiq
    Pangkung, Andareas
    PRZEGLAD ELEKTROTECHNICZNY, 2024, 100 (04): : 67 - 71
  • [47] Optimal network reconfiguration and DG allocation using adaptive modified whale optimization algorithm considering probabilistic load flow
    Uniyal, Ankit
    Sarangi, Saumendra
    ELECTRIC POWER SYSTEMS RESEARCH, 2021, 192
  • [48] Temperature dependent optimal power flow using chaotic whale optimization algorithm
    Prasad, Dharmbir
    Mukherjee, Aparajita
    Mukherjee, Vivekananda
    EXPERT SYSTEMS, 2021, 38 (04)
  • [49] Using the Whale Optimization Algorithm to Solve the Optimal Reactive Power Dispatch Problem
    Zhang, Jinzhong
    Zhang, Tan
    Zhang, Gang
    Wang, Duansong
    Kong, Min
    PROCESSES, 2023, 11 (05)
  • [50] Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm
    Paz-Rodriguez, Alejandra
    Felipe Castro-Ordonez, Juan
    Danilo Montoya, Oscar
    Armando Giral-Ramirez, Diego
    APPLIED SCIENCES-BASEL, 2021, 11 (10):