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Stochastic optimization for generation scheduling in a local energy community under renewable energy uncertainty

Abstract : In electrical systems, the unit commitment (UC) and power scheduling plans the operating of generating units over a short-term planning horizon in order to satisfy the load demand under system operating constraints. Nowadays, energy communities have emerged with individual community energy requirements and increasing capacity deployment of distributed energy resources. The high penetration of renewable energy sources (RES) increases power system uncertainty while the load demand is growing. Hence, traditional deterministic approaches for UC should evolve to stochastic optimization. The main goal of this thesis is to propose probability-based and stochastic optimization methodology for optimal generation and operating reserve (OR) scheduling decisions in an urban microgrid with the wish to address the minimization of operating costs and emissions. Power supply and reserve provision must take into account the uncertainty due to RES and the load demand forecasting errors, while considering the trade-off between security and economic operation. Finally, a user-friendly Supervisory Control And Data Acquisition (SCADA) system is developed with the Matlab GUI to integrate and visualize the energy management operation.
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Submitted on : Thursday, June 24, 2021 - 10:44:10 AM
Last modification on : Friday, June 25, 2021 - 3:31:29 AM

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  • HAL Id : tel-03269581, version 1

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Xin Wen. Stochastic optimization for generation scheduling in a local energy community under renewable energy uncertainty. Electric power. Ecole Centrale de Lille, 2020. English. ⟨NNT : 2020ECLI0017⟩. ⟨tel-03269581⟩

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