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Techno-economic modeling and robust optimization of power systems planning under a high share of renewable energy sources and extreme weather events

Abstract : Recent objectives for power systems sustainability and mitigation of climate change threats are modifying the breadth of power systems planning requirements. On one hand, sustainable low carbon power systems which have a high share of intermittent renewable energy sources (IRES) are characterized by a sharp increase in inter-temporal variability and require flexible systems able to cope and ensure the security of electricity supply. On the other hand, the increased frequency and severity of extreme weather events threatens the reliability of power systems operation and require resilient systems able to withstand those potential impacts. All of which while ensuring that the inherent system uncertainties are adequately accounted for directly at the issuance of the long-term planning decisions. In this context, the present thesis aims at developing a techno-economic modeling and robust optimization framework for multi-period power systems planning considering a high share of IRES and resilience against extreme weather events. The specific planning problem considered is that of selecting the technology choice, size and commissioning schedule of conventional and renewable generation units under technical, economic, environmental and operational constraints. Within this problem, key research questions to be addressed are: (i) the proper integration and assessment of the operational flexibility needs due to the increased variability of the high shares of IRES production, (ii) the appropriate modeling and incorporation of the resilience requirements against extreme weather events within the power system planning problem and (iii) the representation and treatment of the inherent uncertainties in the system supply and demand within this planning context. In summary, the original contributions of this thesis are: - Proposing a computationally efficient multiperiod integrated generation expansion planning and unit commitment model that accounts for key short-term constraints and chronological system representation to derive the planning decisions under a high share of renewable energy penetration. - Introducing the expected flexibility shortfall metric for operational flexibility assessment. - Proposing a set of piece-wise linear models to quantify the impact of extreme heat waves and water availability on the derating of thermal and nuclear power generation units, renewable generation production and system load. - Presenting a method for explicitly incorporating the impact of the extreme weather events in a modified power system planning model. - Treating the inherent uncertainties in the electric power system planning parameters via a novel implementation of a multi-stage adaptive robust optimization model. - Proposing a novel solution method based on ``information basis'' approximation for the linear decision rules of the affinely adjustable robust planning model. - Applying the framework proposed to a practical size case studies based on realistic climate projections and under several scenarios of renewable penetration levels and carbon limits to validate the relevance of the overall modeling for real applications.
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Submitted on : Saturday, January 2, 2021 - 1:35:43 AM
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  • HAL Id : tel-03092308, version 1



Adam Abdin. Techno-economic modeling and robust optimization of power systems planning under a high share of renewable energy sources and extreme weather events. Electric power. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLC046⟩. ⟨tel-03092308⟩



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