Horse herd optimization algorithm for economic dispatch problems

被引:5
|
作者
Basu, Subhamay [1 ]
Kumar, Sajjan [2 ]
Basu, Mousumi [3 ]
机构
[1] Maulana Abul Kalam Azad Univ Technol, Dept Elect & Commun Engn, Techno Main Salt Lake, Kolkata, India
[2] Aditya Engn Coll A, Dept Elect & Elect Engn, Surampalem, India
[3] Jadavpur Univ, Dept Power Engn, Kolkata, India
关键词
Horse herd optimization algorithm; economic dispatch; disallowed feasible area; ramp rate limits; valve-point effect; PARTICLE SWARM OPTIMIZATION; CHAOTIC DIFFERENTIAL EVOLUTION; LOAD DISPATCH; SEARCH ALGORITHM; GENETIC ALGORITHM; DETAILED SURVEY; STRATEGY; SOLVE; UNITS;
D O I
10.1080/0305215X.2022.2035378
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article applies the horse herd optimization (HHO) algorithm to convoluted economic dispatch (ED) problems. HHO mimics the social behaviour of horses of different ages using six significant traits: grazing, hierarchy, sociability, imitation, defence mechanism and roam. The efficacy of the HHO method is demonstrated on five different ED problems, namely, valve-point effects, prohibited feasible area, ramp rate limits and multiple fuels. The simulated outcomes of the recommended method are comparable to those obtained by established artificial intelligence methods. Comparative and statistical analyses demonstrate that the proposed HHO algorithm performs well and can produce superior results to some other well-known and established algorithms, namely, differential evolution (DE), success-history based adaptive differential evolution with linear population size reduction (L-SHADE) and covariance matrix adaptation-evolution strategy (CMA-ES).
引用
收藏
页码:806 / 822
页数:17
相关论文
共 50 条
  • [41] Economic dispatch using stochastic whale optimization algorithm
    Mohamed, FatmaAlzahra
    Abdel-Nasser, Mohamed
    Mahmoud, Karar
    Kamel, Salah
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN COMPUTER ENGINEERING (ITCE' 2018), 2018, : 19 - 24
  • [42] An Elitist Transposon Quantum-Based Particle Swarm Optimization Algorithm for Economic Dispatch Problems
    Wu, Angus
    Yang, Zhen-Lun
    COMPLEXITY, 2018,
  • [43] Novel Heuristic Optimization Technique to Solve Economic Load Dispatch and Economic Emission Load Dispatch Problems
    Singh, Nagendra
    Chakrabarti, Tulika
    Chakrabarti, Prasun
    Margala, Martin
    Gupta, Amit
    Praveen, S. Phani
    Krishnan, Sivaneasan Bala
    Unhelkar, Bhuvan
    ELECTRONICS, 2023, 12 (13)
  • [44] Krill herd technique for dynamic economic dispatch problems with the integration of wind power generation
    Pulluri, Harish
    Nadakuditi, Gouthamkumar
    Vedik, B.
    Srikanth Goud, B.
    Reddy, Ch. Rami
    Kotb, Hossam
    AboRas, Kareem M.
    Emara, Ahmed
    FRONTIERS IN ENERGY RESEARCH, 2023, 11
  • [45] Krill Herd Algorithm Solution for the Economic Emission Load Dispatch in Power System Operations
    Ghosh, Bratati
    Chakraborty, Ajoy Kumar
    Bhowmik, Arup Ratan
    Bhattacharya, Aniruddha
    2017 7TH INTERNATIONAL CONFERENCE ON POWER SYSTEMS (ICPS), 2017, : 737 - 742
  • [46] Opposition-based krill herd algorithm applied to economic load dispatch problem
    Bulbul, Sk Md Ali
    Pradhan, Moumita
    Roy, Provas Kumar
    Pal, Tandra
    AIN SHAMS ENGINEERING JOURNAL, 2018, 9 (03) : 423 - 440
  • [47] Constrained Static/Dynamic Economic Emission Load Dispatch Using Elephant Herd Optimization
    Peesapati, Rajagopal
    Nayak, Yogesh Kumar
    Warungase, Swati K.
    Salkuti, Surender Reddy
    INFORMATION, 2023, 14 (06)
  • [48] Dragonfly Algorithm for solving probabilistic Economic Load Dispatch problems
    Das, Diptanu
    Bhattacharya, Aniruddha
    Ray, Rup Narayan
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (08): : 3029 - 3045
  • [49] An immune algorithm with power redistribution for solving economic dispatch problems
    Aragon, V. S.
    Esquivel, S. C.
    Coello Coello, C. A.
    INFORMATION SCIENCES, 2015, 295 : 609 - 632
  • [50] Seeker optimisation algorithm for the solution of economic load dispatch problems
    Shaw, Binod
    Ghoshal, S. P.
    Mukherjee, V.
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2011, 3 (05) : 275 - 285