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Fuel constrained dynamic economic dispatch with demand side management

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  • Basu, M.

Abstract

Owing to slowly reduction of fossil fuel, the cost-effective use of available fuel for electric power generation has turn out to be a very important concern of electric power utilities. Thermal power plants have to operate within their fuel confines and contractual constraints. This work recommends social group entropy optimization (SGEO) technique to solve fuel constrained dynamic economic dispatch (FCDED) with demand side management (DSM) integrating renewable energy sources and pumped hydro storage plant. Here the dynamic economic dispatch (DED) problem is solved with and without fuel constrained. The effectiveness of the recommended technique is revealed on two test systems. Simulation results of two test systems have been compared with those acquired from self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC), fast convergence evolutionary programming (FCEP) and differential evolution (DE). Test results show that fuel consumption can be sufficiently controlled for fulfilling constraints imposed by suppliers. It has been observed from the comparison that the suggested SGEO has the capability to confer with superior-quality solution.

Suggested Citation

  • Basu, M., 2021. "Fuel constrained dynamic economic dispatch with demand side management," Energy, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:energy:v:223:y:2021:i:c:s0360544221003170
    DOI: 10.1016/j.energy.2021.120068
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    References listed on IDEAS

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    1. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2018. "Solving the dynamic economic dispatch by a memory-based global differential evolution and a repair technique of constraint handling," Energy, Elsevier, vol. 147(C), pages 59-80.
    2. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.
    3. Alham, M.H. & Elshahed, M. & Ibrahim, Doaa Khalil & Abo El Zahab, Essam El Din, 2016. "A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management," Renewable Energy, Elsevier, vol. 96(PA), pages 800-811.
    4. Pérez-Díaz, Juan I. & Jiménez, Javier, 2016. "Contribution of a pumped-storage hydropower plant to reduce the scheduling costs of an isolated power system with high wind power penetration," Energy, Elsevier, vol. 109(C), pages 92-104.
    5. 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.
    6. Mohammad Rasoul Narimani & Maigha & Jhi-Young Joo & Mariesa Crow, 2017. "Multi-Objective Dynamic Economic Dispatch with Demand Side Management of Residential Loads and Electric Vehicles," Energies, MDPI, vol. 10(5), pages 1-18, May.
    7. Xiong, Guojiang & Shi, Dongyuan, 2018. "Hybrid biogeography-based optimization with brain storm optimization for non-convex dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 157(C), pages 424-435.
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    Cited by:

    1. Ahmed, Ijaz & Rehan, Muhammad & Basit, Abdul & Malik, Saddam Hussain & Alvi, Um-E-Habiba & Hong, Keum-Shik, 2022. "Multi-area economic emission dispatch for large-scale multi-fueled power plants contemplating inter-connected grid tie-lines power flow limitations," Energy, Elsevier, vol. 261(PB).

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