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Hybrid Bio-Inspired Computational Heuristic Paradigm for Integrated Load Dispatch Problems Involving Stochastic Wind

Author

Listed:
  • Raheela Jamal

    (Beijing Key Laboratory of Energy Safety and Clean Utilization, North China Electric Power University, Renewable Energy School, Beijing 102206, China)

  • Baohui Men

    (Beijing Key Laboratory of Energy Safety and Clean Utilization, North China Electric Power University, Renewable Energy School, Beijing 102206, China)

  • Noor Habib Khan

    (Beijing Key Laboratory of Energy Safety and Clean Utilization, North China Electric Power University, Renewable Energy School, Beijing 102206, China)

  • Muhammad Asif Zahoor Raja

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan)

Abstract
In this research work, bio-inspired computational heuristic algorithms (BCHAs) integrated with active-set algorithms (ASA) were designed to study integrated economics load dispatch problems with valve point effects involving stochastic wind power. These BCHAs are developed through variants of genetic algorithms based on a different set of routines for reproduction operators in order to make exploration and exploitation in the entire search space for finding the global optima, while the ASA is used for rapid local refinements of the results. The designed schemes are estimated on different load dispatch systems consisting of a combination of thermal generating units and wind power plants with and without valve point loading effects. The accuracy, convergence, robustness and complexity of the proposed schemes has been examined through comparative studies based on a sufficiently large number of independent trails and their statistical observations in terms of different performance indices.

Suggested Citation

  • Raheela Jamal & Baohui Men & Noor Habib Khan & Muhammad Asif Zahoor Raja, 2019. "Hybrid Bio-Inspired Computational Heuristic Paradigm for Integrated Load Dispatch Problems Involving Stochastic Wind," Energies, MDPI, vol. 12(13), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2568-:d:245460
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    References listed on IDEAS

    as
    1. Chen, Xu & Xu, Bin & Mei, Congli & Ding, Yuhan & Li, Kangji, 2018. "Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation," Applied Energy, Elsevier, vol. 212(C), pages 1578-1588.
    2. Alfredo Alcayde & Raul Baños & Francisco M. Arrabal-Campos & Francisco G. Montoya, 2019. "Optimization of the Contracted Electric Power by Means of Genetic Algorithms," Energies, MDPI, vol. 12(7), pages 1-13, April.
    3. Li, M.S. & Lin, Z.J. & Ji, T.Y. & Wu, Q.H., 2018. "Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula," Applied Energy, Elsevier, vol. 226(C), pages 967-978.
    4. Zou, Dexuan & Li, Steven & Wang, Gai-Ge & Li, Zongyan & Ouyang, Haibin, 2016. "An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects," Applied Energy, Elsevier, vol. 181(C), pages 375-390.
    5. Chen, Wei-Hsin & Wu, Po-Hua & Lin, Yu-Li, 2018. "Performance optimization of thermoelectric generators designed by multi-objective genetic algorithm," Applied Energy, Elsevier, vol. 209(C), pages 211-223.
    6. Azizipanah-Abarghooee, Rasoul & Niknam, Taher & Roosta, Alireza & Malekpour, Ahmad Reza & Zare, Mohsen, 2012. "Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method," Energy, Elsevier, vol. 37(1), pages 322-335.
    7. Jaber Valinejad & Mousa Marzband & Mudathir Funsho Akorede & Ian D Elliott & Radu Godina & João Carlos de Oliveira Matias & Edris Pouresmaeil, 2018. "Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market," Sustainability, MDPI, vol. 10(10), pages 1-19, October.
    8. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    9. Abdelaziz, A.Y. & Ali, E.S. & Abd Elazim, S.M., 2016. "Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems," Energy, Elsevier, vol. 101(C), pages 506-518.
    10. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    11. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
    12. Adarsh, B.R. & Raghunathan, T. & Jayabarathi, T. & Yang, Xin-She, 2016. "Economic dispatch using chaotic bat algorithm," Energy, Elsevier, vol. 96(C), pages 666-675.
    13. Joanna Ferdyn-Grygierek & Krzysztof Grygierek, 2017. "Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms," Energies, MDPI, vol. 10(10), pages 1-20, October.
    14. Jebaraj, Luke & Venkatesan, Chakkaravarthy & Soubache, Irisappane & Rajan, Charles Christober Asir, 2017. "Application of differential evolution algorithm in static and dynamic economic or emission dispatch problem: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1206-1220.
    15. Gonggui Chen & Zhengmei Lu & Zhizhong Zhang, 2018. "Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems," Energies, MDPI, vol. 11(1), pages 1-27, January.
    16. Masoumeh Javadi & Mousa Marzband & Mudathir Funsho Akorede & Radu Godina & Ameena Saad Al-Sumaiti & Edris Pouresmaeil, 2018. "A Centralized Smart Decision-Making Hierarchical Interactive Architecture for Multiple Home Microgrids in Retail Electricity Market," Energies, MDPI, vol. 11(11), pages 1-22, November.
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    Cited by:

    1. Yue Cao & Tao Li & Tianyu He & Yuwei Wei & Ming Li & Fengqi Si, 2022. "Multiobjective Load Dispatch for Coal-Fired Power Plants under Renewable-Energy Accommodation Based on a Nondominated-Sorting Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 15(8), pages 1-19, April.
    2. Mehmood, Ammara & Raja, Muhammad Asif Zahoor & Ninness, Brett, 2024. "Design of fractional-order hammerstein control auto-regressive model for heat exchanger system identification: Treatise on fuzzy-evolutionary computing," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    3. Sabir, Zulqurnain & Raja, Muhammad Asif Zahoor & Khalique, Chaudry Masood & Unlu, Canan, 2021. "Neuro-evolution computing for nonlinear multi-singular system of third order Emden–Fowler equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 799-812.
    4. Sabir, Zulqurnain & Saoud, Sahar & Raja, Muhammad Asif Zahoor & Wahab, Hafiz Abdul & Arbi, Adnène, 2020. "Heuristic computing technique for numerical solutions of nonlinear fourth order Emden–Fowler equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 534-548.
    5. Mehmood, Ammara & Raja, Muhammad Asif Zahoor & Jalili, Mahdi, 2023. "Optimization of integrated load dispatch in multi-fueled renewable rich power systems using fractal firefly algorithm," Energy, Elsevier, vol. 278(PA).
    6. Umar, Muhammad & Sabir, Zulqurnain & Raja, Muhammad Asif Zahoor & Aguilar, J.F. Gómez & Amin, Fazli & Shoaib, Muhammad, 2021. "Neuro-swarm intelligent computing paradigm for nonlinear HIV infection model with CD4+ T-cells," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 241-253.
    7. Xue Lin & Lixia Sun & Ping Ju & Hongyu Li, 2019. "Stochastic Control for Intra-Region Probability Maximization of Multi-Machine Power Systems Based on the Quasi-Generalized Hamiltonian Theory," Energies, MDPI, vol. 13(1), pages 1-16, December.
    8. Mehmood, Ammara & Raja, Muhammad Asif Zahoor, 2022. "Fuzzy-weighted differential evolution computing paradigm for fractional order nonlinear wiener systems," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

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