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Optimal generation scheduling of hydrothermal system with demand side management considering uncertainty and outage of renewable energy sources

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  • Basu, M.

Abstract

Due to escalating permeation of renewable energy sources, it becomes essential to investigate its brunt on the optimal power generation scheduling. But, highly intermittent nature of renewable energy sources and their higher rate of outages may have detrimental effect on the entire grid. This work recommends chaotic fast convergence evolutionary programming (CFCEP) rooted in Tent equation to solve hydrothermal generation scheduling incorporating pumped-storage-hydraulic (PSH) unit with demand side management (DSM) considering uncertainty and outage of renewable energy sources. Chaotic sequences increase the exploitation ability in the searching space and enhance the convergence property. In the recommended technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). Simulation outcomes of the test system have been matched up to those acquired by FCEP, differential evolution (DE) and particle swarm optimization (PSO). It has been observed from the comparison that the recommended CFCEP technique has the capability to bestow with superior-quality solution.

Suggested Citation

  • Basu, M., 2020. "Optimal generation scheduling of hydrothermal system with demand side management considering uncertainty and outage of renewable energy sources," Renewable Energy, Elsevier, vol. 146(C), pages 530-542.
    • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:530-542
    DOI: 10.1016/j.renene.2019.06.069
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    References listed on IDEAS

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    1. Ma, Tao & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2015. "Pumped storage-based standalone photovoltaic power generation system: Modeling and techno-economic optimization," Applied Energy, Elsevier, vol. 137(C), pages 649-659.
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    2. 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.
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    5. Rosane Santos & André Luiz Diniz & Bruno Borba, 2022. "Assessment of the Modeling of Demand Response as a Dispatchable Resource in Day-Ahead Hydrothermal Unit Commitment Problems: The Brazilian Case," Energies, MDPI, vol. 15(11), pages 1-15, May.
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    7. Yin, Hao & Wu, Fei & Meng, Xin & Lin, Yicheng & Fan, Jingmin & Meng, Anbo, 2020. "Crisscross optimization based short-term hydrothermal generation scheduling with cascaded reservoirs," Energy, Elsevier, vol. 203(C).
    8. Mohseni, Soheil & Khalid, Roomana & Brent, Alan C., 2023. "Stochastic, resilience-oriented optimal sizing of off-grid microgrids considering EV-charging demand response: An efficiency comparison of state-of-the-art metaheuristics," Applied Energy, Elsevier, vol. 341(C).

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