Techno-economic modeling and robust optimization of power systems planning under a high share of renewable energy sources and extreme weather events Adam Abdin To cite this version: 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 HAL Id: tel-03092308 https://tel.archives-ouvertes.fr/tel-03092308 Submitted on 2 Jan 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Techno-economic modeling and robust optimization of power systems planning under a high share of renewable 2019SACLC046 energy sources and extreme weather : events NNT Thèse de doctorat de l'Université Paris-Saclay préparée à CentraleSupélec École doctorale n°573 Interfaces : Approches Interdisciplinaires / Fondements, Application et Innovation (Interfaces) Spécialité de doctorat: Ingénierie des Systèmes Complexes Thèse présentée et soutenue à Gif-sur-Yvette, le 23/07/2019, par ISLAM F. ABDIN Composition du Jury : Guillaume Sandou Professor, CentraleSupélec, Control Department President Jay Apt Professor, Carnegie Mellon University, College of Engineering Rapporteur Antonio Conejo Professor, Ohio State University, College of Engineering Rapporteur Michel-Alexandre Cardin Associate Professor, Imperial College London, Faculty of Engineering Rapporteur Paola Girdinio Professeur, Universita degli Studi di Genova Department of Electrical Engineering Examinateur Yi Ding Professor, Zhejiang University, College of Electrical Engineering Examinateur Wim van Ackooij Ingénieur de Recherche (HDR), Electricité De France R&D Examinateur Enrico Zio Professor, Mines Paristech, PSL Research University Politecnico di Milano, Department of Energy Directeur de thèse CENTRALESUPELEC,UNIVERSITÉ PARIS-SACLAY DOCTORAL THESIS Techno-economic modeling and robust optimization of power systems planning under a high share of renewable energy sources and extreme weather events Author: Supervisor: Islam F. ABDIN Prof. Enrico ZIO August 02, 2019 To M. F. Abdin (Prof. Dr.-Ing.) my dear father v Acknowledgements I would like to express my sincere gratitude to my thesis advisor, Prof. Enrico Zio, for his generous support in developing this research work, for his constant encour- agement and for his significant efforts in ensuring its scientific rigor. Thank you, also, for constantly spreading enthusiasm in our attempts to contribute to scientific research. I extend my appreciation to Dr. Aakil Caunhye and Dr. Yiping Fang for our col- laborations and their contributions to some of the methods developed in this thesis and for the many interesting discussions we had around its themes. I would also like to thank Dr. Sebastien Lepaul from EDF R& D for his support and encourage- ment and for his efforts in organizing the different workshops and seminars where we had the chance to discuss the work with our industrial partners in EDF. My sincere gratitude for Prof. Michel-Alexandre Cardin, Dr. Aakil Caunhye and Dr. Elizaveta Kuznetsova for welcoming me within their team at the Future Resilient Systems laboratory - Singapore-ETH Centre (SEC), National University of Singapore, where I got the chance to expand my knowledge on resilience of complex systems and robust optimization methods. To the honorable jury members: Prof. Jay Apt, Prof. Antonio J. Conejo, Prof. Michel-Alexandre Cardin, Prof. Guillaume Sandou, Prof. Paola Girdinio, Prof. Yi Ding and Dr. Wim van Akooij, my sincere gratitude for your time and considera- tion. It was an absolute privilege having defended this thesis before such excelled academics and professionals who are real references in their domains. I am very grateful for the constructive remarks, comments, suggestions and your kind encour- agement. My warmest feelings to all my colleagues and the supporting staff at the Labo- ratory of Industrial Engineering, CentraleSupelec, Universite Paris-Saclay, where I have started and completed this Ph.D. thesis. Every one of them contributed to my personal and scientific growth and to the amazing time I had during those years. My deepest gratitude to my family. 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 inter- mittent 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 sever- ity 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 model- ing 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 un- der technical, economical, 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 uncer- tainties in the system supply and demand within this planning context. To this end, we first introduce an integrated framework for operational flexibility assessment in power system planning with a significant share of IRES. The frame- work stands on: (i) the formulation of an integrated generation expansion planning (GEP) and unit commitment (UC) model accounting for key short-term technical constraints, (ii) the elaboration of accurate and systematic horizon reduction meth- ods to alleviate the computational burden of the resulting large-sized optimization problem and (iii) the definition of suitable metrics for the operational flexibility as- sessment of the obtained plans. The framework is applied to the multi-annual plan- ning horizon of a realistically sized case study, under several scenarios of IRES pene- tration levels and carbon limits to validate its superiority in accounting for the needs of operational flexibility compared to conventional planning methods. The framework proposed is, then, extended to incorporate the system resilience against extreme weather events. Specifically, a set of piece-wise linear models are developed to calculate the impact of extreme heat waves and drought events on the performance of the power generation units and on the system load. A method for integrating this impact within a resilient planning approach is, then, proposed viii and the results are analyzed for case studies under real future climate projections obtained from the Coupled Model Intercomparison Project phase 5. Finally, to account for the various supply and demand uncertainties, the power system planning model with dynamic constraints is treated within a multi-stage adaptive robust optimization. The uncertainty of electricity demand and renewable power generation is taken into account through distribution-free bounded intervals, with parameters that permit control over the level of conservatism of the solution. A solution method based on linear decision rules and information-level approximation is also presented. The method is, then, applied to the case study and the results con- firm the effectiveness of the proposed approach especially in coping with multi-fold short-term ramping uncertainties in power systems planning. In summary, the original contributions of this thesis are: • Proposing a computationally efficient multi-period integrated generation ex- pansion planning and unit commitment model that accounts for key short- term constraints and chronological system representation to derive the plan- ning 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 pa- rameters via