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A holistic review on optimization strategies for combined economic emission dispatch problem

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  • Mahdi, Fahad Parvez
  • Vasant, Pandian
  • Kallimani, Vish
  • Watada, Junzo
  • Fai, Patrick Yeoh Siew
  • Abdullah-Al-Wadud, M.
Abstract
Power generation system largely depends on fossil fuels to generate electricity. Due to various reasons, the reserves of fossil fuels are declining and will become too expensive in near future. At the same time, generation of power from fossil fuels causes hazardous gases and particulates to emit, which pollutes the air and causes significant and long term damages on the environment. For this reason, extensive research works have been conducted for last few decades from different perspectives to reduce both the fuel cost as well as the emission of hazardous gases in power generation system. This power generation problem is commonly referred to as the combined economic emission dispatch (CEED) problem. This paper provides a comprehensive review on the uses of different optimization techniques to solve CEED problem. Authors have found advanced nature-inspired methods as the most suitable and successful, and have concluded combinational hybrid methods as the most prospective methods to solve CEED problem.

Suggested Citation

  • Mahdi, Fahad Parvez & Vasant, Pandian & Kallimani, Vish & Watada, Junzo & Fai, Patrick Yeoh Siew & Abdullah-Al-Wadud, M., 2018. "A holistic review on optimization strategies for combined economic emission dispatch problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3006-3020.
    • Handle: RePEc:eee:rensus:v:81:y:2018:i:p2:p:3006-3020
    DOI: 10.1016/j.rser.2017.06.111
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    References listed on IDEAS

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    2. Lai, Wenhao & Zheng, Xiaoliang & Song, Qi & Hu, Feng & Tao, Qiong & Chen, Hualiang, 2022. "Multi-objective membrane search algorithm: A new solution for economic emission dispatch," Applied Energy, Elsevier, vol. 326(C).
    3. Yu, Xiaobing & Duan, Yuchen & Luo, Wenguan, 2022. "A knee-guided algorithm to solve multi-objective economic emission dispatch problem," Energy, Elsevier, vol. 259(C).
    4. Shahbaz Hussain & Mohammed Al-Hitmi & Salman Khaliq & Asif Hussain & Muhammad Asghar Saqib, 2019. "Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant," Energies, MDPI, vol. 12(11), pages 1-15, May.
    5. Mbuli, N. & Ngaha, W.S., 2022. "A survey of big bang big crunch optimisation in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    6. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    7. Lai, Wenhao & Song, Qi & Zheng, Xiaoliang & Tao, Qiong & Chen, Hualiang, 2023. "A new version of membrane search algorithm for hybrid renewable energy systems dynamic scheduling," Renewable Energy, Elsevier, vol. 209(C), pages 262-276.
    8. Mellouk, Lamyae & Ghazi, M. & Aaroud, A. & Boulmalf, M. & Benhaddou, D. & Zine-Dine, K., 2019. "Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region," Renewable Energy, Elsevier, vol. 139(C), pages 621-634.
    9. Qingbin Yu & Yuliang Dong & Yanjun Du & Jiahai Yuan & Fang Fang, 2022. "Optimizing Operation Strategy in a Simulated High-Proportion Wind Power Wind–Coal Combined Base Load Power Generation System under Multiple Scenes," Energies, MDPI, vol. 15(21), pages 1-21, October.
    10. Amiri, M. & Khanmohammadi, S. & Badamchizadeh, M.A., 2018. "Floating search space: A new idea for efficient solving the Economic and emission dispatch problem," Energy, Elsevier, vol. 158(C), pages 564-579.
    11. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    12. Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.

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