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Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II

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  • Basu, M.

Abstract

This paper presents nondominated sorting genetic algorithm-II for solving fuel constrained economic emission dispatch problem of thermal generating units. This is a multi-objective optimization problem which includes the standard load constraints as well as the fuel constraints. The generation schedule is compared to that which would result if fuel constraints are ignored. The comparison shows that fuel consumed can be adequately controlled by adjusting the power output of various generating units so that the power system operates within its fuel limitations and within contractual constraints. It has been found that one of the two objectives (i.e. fuel cost and emission level) may be increased while other may be decreased to serve the same power demand but this may well compensate for the penalty that might be otherwise imposed for not maintaining the fuel contract. Numerical results for two test systems have been presented and the test results are compared with those obtained from strength pareto evolutionary algorithm 2.

Suggested Citation

  • Basu, M., 2014. "Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II," Energy, Elsevier, vol. 78(C), pages 649-664.
  • Handle: RePEc:eee:energy:v:78:y:2014:i:c:p:649-664
    DOI: 10.1016/j.energy.2014.10.052
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    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Roosta, Alireza & Amiri, Babak, 2012. "A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch," Energy, Elsevier, vol. 42(1), pages 530-545.
    2. Panigrahi, B.K. & Ravikumar Pandi, V. & Das, Sanjoy & Das, Swagatam, 2010. "Multiobjective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem," Energy, Elsevier, vol. 35(12), pages 4761-4770.
    3. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Azizipanah-Abarghooee, Rasoul, 2013. "An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties," Energy, Elsevier, vol. 50(C), pages 232-244.
    4. Younes, Mimoun & Khodja, Fouad & Kherfane, Riad Lakhdar, 2014. "Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration," Energy, Elsevier, vol. 67(C), pages 595-606.
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    1. Singh, Nirbhow Jap & Dhillon, J.S. & Kothari, D.P., 2017. "Surrogate worth trade-off method for multi-objective thermal power load dispatch," Energy, Elsevier, vol. 138(C), pages 1112-1123.
    2. Nwulu, Nnamdi I. & Xia, Xiaohua, 2015. "Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs," Energy, Elsevier, vol. 91(C), pages 404-419.
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    6. Gherbi, Yamina Ahlem & Bouzeboudja, Hamid & Gherbi, Fatima Zohra, 2016. "The combined economic environmental dispatch using new hybrid metaheuristic," Energy, Elsevier, vol. 115(P1), pages 468-477.
    7. Mingcong Liu & Shaobo Yang & Hongyu Li & Jiayi Xu & Xingfei Li, 2019. "Energy Consumption Analysis and Optimization of the Deep-Sea Self-Sustaining Profile Buoy," Energies, MDPI, vol. 12(12), pages 1-26, June.
    8. Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    9. Jin, Jingliang & Zhou, Peng & Li, Chenyu & Bai, Yang & Wen, Qinglan, 2020. "Optimization of power dispatching strategies integrating management attitudes with low carbon factors," Renewable Energy, Elsevier, vol. 155(C), pages 555-568.
    10. Panpan Mei & Lianghong Wu & Hongqiang Zhang & Zhenzu Liu, 2019. "A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration," Energies, MDPI, vol. 12(20), pages 1-21, October.
    11. Salil Madhav Dubey & Hari Mohan Dubey & Manjaree Pandit & Surender Reddy Salkuti, 2021. "Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization," Energies, MDPI, vol. 14(19), pages 1-20, October.
    12. Jingliang Jin & Qinglan Wen & Xianyue Zhang & Siqi Cheng & Xiaojun Guo, 2021. "Economic Emission Dispatch for Wind Power Integrated System with Carbon Trading Mechanism," Energies, MDPI, vol. 14(7), pages 1-17, March.
    13. Wang, Yajun & Wang, Jidong & Cao, Man & Kong, Xiangyu & Abderrahim, Bouchedjira & Yuan, Long & Vartosh, Aris, 2023. "Dynamic emission dispatch considering the probabilistic model with multiple smart energy system players based on a developed fuzzy theory-based harmony search algorithm," Energy, Elsevier, vol. 269(C).
    14. Li Yan & Zhengyu Zhu & Xiaopeng Kang & Boyang Qu & Baihao Qiao & Jiajia Huan & Xuzhao Chai, 2022. "Multi-Objective Dynamic Economic Emission Dispatch with Electric Vehicle–Wind Power Interaction Based on a Self-Adaptive Multiple-Learning Harmony-Search Algorithm," Energies, MDPI, vol. 15(14), pages 1-22, July.
    15. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    16. Jin, Jingliang & Zhou, Peng & Zhang, Mingming & Yu, Xianyu & Din, Hao, 2018. "Balancing low-carbon power dispatching strategy for wind power integrated system," Energy, Elsevier, vol. 149(C), pages 914-924.

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