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Optimization of emission/economic dispatch using euclidean affine flower pollination algorithm (eFPA) and binary FPA (BFPA) in solar photo voltaic generation

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  • Shilaja, C.
  • Ravi, K.

Abstract

Economic dispatch is the optimal output for a number of electricity generating units, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The different Economic Dispatch (ED) methods have been developed in order to deal with the challenge of continuous and sustainable power at an improved cost. The increase in cost depletion of non-renewable sources has forced us to use the renewable energy resource as an alternative energy source. For optimizing the Economic Dispatch problem, a new algorithm is proposed based on Combined Emission Economic Dispatch (CEED) for Photo Voltaic (PV) plants and thermal power generation units. In CEED approach for improvising the Economic Dispatch Euclidean Affine Flower Pollination Algorithm (eFPA) and Binary Flower Pollination Algorithm (BFPA) has been used for solving the optimization problem for twenty PV and five thermal generators are done with full solar radiations and with reduced solar radiation. Power demand data has been taken from India in the district of Tuticorin Thermal Power Station (TTPS). Simulation results are tested with IEEE 30 bus and IEEE 57 bus systems and the comparison has been made with existing algorithm to provide better results.

Suggested Citation

  • Shilaja, C. & Ravi, K., 2017. "Optimization of emission/economic dispatch using euclidean affine flower pollination algorithm (eFPA) and binary FPA (BFPA) in solar photo voltaic generation," Renewable Energy, Elsevier, vol. 107(C), pages 550-566.
    • Handle: RePEc:eee:renene:v:107:y:2017:i:c:p:550-566
    DOI: 10.1016/j.renene.2017.02.021
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    References listed on IDEAS

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    1. Rajesh, K. & Bhuvanesh, A. & Kannan, S. & Thangaraj, C., 2016. "Least cost generation expansion planning with solar power plant using Differential Evolution algorithm," Renewable Energy, Elsevier, vol. 85(C), pages 677-686.
    2. Modiri-Delshad, Mostafa & Rahim, Nasrudin Abd, 2014. "Solving non-convex economic dispatch problem via backtracking search algorithm," Energy, Elsevier, vol. 77(C), pages 372-381.
    3. Izadbakhsh, Maziar & Gandomkar, Majid & Rezvani, Alireza & Ahmadi, Abdollah, 2015. "Short-term resource scheduling of a renewable energy based micro grid," Renewable Energy, Elsevier, vol. 75(C), pages 598-606.
    4. Secui, Dinu Calin, 2015. "The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch," Energy, Elsevier, vol. 93(P2), pages 2518-2545.
    5. Sivasubramani, S. & Swarup, K.S., 2010. "Hybrid SOA–SQP algorithm for dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 35(12), pages 5031-5036.
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    Cited by:

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    4. Basu, Mousumi, 2022. "Fuel constrained short-term hydrothermal generation scheduling," Energy, Elsevier, vol. 239(PD).
    5. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
    6. Chen, Min-Rong & Zeng, Guo-Qiang & Lu, Kang-Di, 2019. "Constrained multi-objective population extremal optimization based economic-emission dispatch incorporating renewable energy resources," Renewable Energy, Elsevier, vol. 143(C), pages 277-294.
    7. Basu, M., 2022. "Fuel constrained combined heat and power dynamic dispatch using horse herd optimization algorithm," Energy, Elsevier, vol. 246(C).
    8. Qun Niu & Ming You & Zhile Yang & Yang Zhang, 2021. "Economic Emission Dispatch Considering Renewable Energy Resources—A Multi-Objective Cross Entropy Optimization Approach," Sustainability, MDPI, vol. 13(10), pages 1-33, May.
    9. Basu, M., 2021. "Heat and power generation augmentation planning of isolated microgrid," Energy, Elsevier, vol. 223(C).
    10. Basu, M., 2021. "Fuel constrained dynamic economic dispatch with demand side management," Energy, Elsevier, vol. 223(C).
    11. Basu, Mousumi, 2023. "Fuel constrained commitment scheduling for combined heat and power dispatch incorporating electric vehicle parking lot," Energy, Elsevier, vol. 276(C).
    12. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    13. Gurpreet Kaur & Mohit Kumar & J. S. Dhillon, 2025. "Dynamic Multi-area Generation Scheduling with Renewable Energy Sources Exploiting Optimistic Sine–Cosine Algorithm," SN Operations Research Forum, Springer, vol. 6(2), pages 1-53, June.
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