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L'objectif de cette thèse est la gestion et le dimensionnement optimaux d'un Système de Stockage d'Énergie (SSE) couplé à une production d'électricité issue d'Énergies Renouvelables Intermittentes (EnRI). Dans un premier temps, un modèle technico-économique du système SSE-EnRI est développé, associé à trois scénarios types d'injection de puissance au réseau électrique : lissage horaire basé sur la prévision J-1 (S1), puissance garantie (S2) et combiné (S3). Ce modèle est traduit sous la forme d'un programme d'optimisation non linéaire de grande taille. Dans un deuxième temps, les stratégies heuristiques élaborées conduisent à une gestion optimisée - selon les critères de fiabilité, de productivité, d'efficacité et de profitabilité du système - de la production d'énergie avec stockage, appelée “charge adaptative” (CA). Comparée à un modèle linéaire mixte en nombres entiers (MILP), cette gestion optimisée, applicable en conditions opérationnelles, conduit rapidement à des résultats proches de l'optimum. Enfin, la charge adaptative est utilisée dans le dimensionnement optimisé du SSE - pour chacune des trois sources : éolien, houle, solaire (PV). La capacité minimale permettant de respecter le scénario avec un taux de défaillance et des tarifs de revente de l'énergie viables ainsi que les énergies conformes, perdues, manquantes correspondantes sont déterminées. Une analyse de sensibilité est menée montrant l'importance des rendements, de la qualité de prévision ainsi que la forte influence de l'hybridation des sources sur le dimensionnement technico-économique du SSE. / This thesis aims at presenting an optimal management and sizing of an Energy Storage System (ESS) paired up with Intermittent Renewable Energy Sources (IReN). Firstly, wedeveloped a technico-economic model of the system which is associated with three typical scenarios of utility grid power supply: hourly smoothing based on a one-day-ahead forecast (S1), guaranteed power supply (S2) and combined scenarios (S3). This model takes the form of a large-scale non-linear optimization program. Secondly, four heuristic strategies are assessed and lead to an optimized management of the power output with storage according to the reliability, productivity, efficiency and profitability criteria. This ESS optimized management is called “Adaptive Storage Operation” (ASO). When compared to a mixed integer linear program (MILP), this optimized operation that is practicable under operational conditions gives rapidly near-optimal results. Finally, we use the ASO in ESS optimal sizing for each renewable energy: wind, wave and solar (PV). We determine the minimal sizing that complies with each scenario, by inferring the failure rate, the viable feed-in tariff of the energy, and the corresponding compliant, lost or missing energies. We also perform sensitivity analysis which highlights the importance of the ESS efficiency and of the forecasting accuracy and the strong influence of the hybridization of renewables on ESS technico-economic sizing.

The aim of this thesis is to objectify the discussion regarding the availability of technologies related to the German energy transition. This work describes the state of development of relevant technologies on the basis of Technology Readiness Levels. Further, it points out development potentials and limits as well as the necessary power capacities needed for a certain energy system design that is mainly based on electricity. Thus, the scope is set to renewable energy sources suited to provide electricity in Germany, technologies that convert primary electricity for other energy sectors (heating and mobility) and storage technologies. Additionally, non-conventional technologies for electricity supply and grid technologies are examined. The underlying Technology Readiness Assessment is a method used to determine the maturity of these systems or their essential components. The major criteria for assessment are scale, system fidelity and environment. In order to estimate the relevant magnitudes for certain energy technologies regarding power and storage capacities, a comprehensible simulation model is drafted and implemented. It allows the calculation of a renewable, volatile power supply based on historic data and the display of load and storage characteristics. As a result, the Technology Readiness Level of the different systems examined varies widely. For every step in the direct or indirect usage of renewable intermittent energy sources technologies on megawatt scale are commercially available. The necessary scale for the energy storage capacity is in terawatt hours. Based on the examined storage technologies, only chemical storages potentially provide this magnitude. Further, the required total power capacities for complementary conversion technologies lay in the two-digit gigawatt range.:Abstract 2 Contents 3 1. Introduction 7 2. General remarks on the current state of the German energy system 12 3. Method of Technology Readiness Assessment 16 3.1. Fundamentals of the method 16 3.2. Drawbacks of TRA 19 3.3. Extended Readiness Levels 20 3.4. Conducting the Technology Readiness Assessment 21 3.5. Expert interviews 23 3.6. References 24 4. Preliminary remarks on the TRL assessment 25 4.1. Mission and environment 25 4.2. Simplifications and neglected aspects 26 4.3. References 26 5. Wind power 27 5.1. Technology description 27 5.2. Estimation of potential 32 5.3. Representation of the achieved state of expansion 37 5.4. TRL assessment 39 5.5. References 40 6. Solar energy 44 6.1. Technology description 44 6.2. Solar thermal energy 44 6.3. Photovoltaic technologies 45 6.4. Estimation of potential 48 6.5. Representation of the achieved state of expansion 52 6.6. TRL assessment 53 6.7. References 54 7. Geothermal energy 56 7.1. Technology description 56 7.2. Estimation of potential 59 7.3. Description of the current level of expansion 62 7.4. TRL assessment 63 7.5. References 64 8. Hydropower 66 8.1. Technology description 66 8.2. Estimation of potential 68 8.3. Description of the current level of development 70 8.4. TRL assessment 71 8.5. References 72 9. Biomass 73 9.1. Technology description 73 9.2. Estimation of potential 75 9.3. Representation of the achieved state of expansion 79 9.4. TRL assessment 81 9.5. References 82 10. Transmission and distribution grids 84 10.1. Technology description 84 10.2. Estimation of potential 90 10.3. Representation of the achieved state of expansion 94 10.4. TRL assessment 95 10.5. References 96 11. Power-to-heat 100 11.1. Technology description 100 11.2. Estimation of potential 104 11.3. Representation of the achieved state of expansion 107 11.4. TRL assessment 108 11.5. References 109 12. Power-to-cold 111 12.1. Technology description 111 12.2. Estimation of potential 114 12.3. Representation of the achieved state of expansion 117 12.4. TRL assessment 118 12.5. References 120 13. Power-to-chemicals 122 13.1. Technology description 122 13.2. Estimation of potential 134 13.3. Representation of the achieved state of expansion 137 13.4. TRL assessment 138 13.5. Manufacturer overview for electrolysis systems 140 13.6. References 142 14. Mechanical storage 146 14.1. Technology description 146 14.2. Estimation of potential 148 14.3. Representation of the achieved state of expansion 155 14.4. TRL assessment 155 14.5. References 158 15. Thermal storage 160 15.1. Technology description 160 15.2. Estimation of potential 164 15.3. Representation of the achieved state of expansion 169 15.4. TRL assessment 170 15.5. References 172 16. Chemical storage systems 175 16.1. Technology description 175 16.2. Estimation of potential 180 16.3. Representation of the achieved state of expansion 185 16.4. TRL assessment 186 16.5. References 188 17. Electro-chemical storage systems 191 17.1. Technology description 191 17.2. Estimation of potential 198 17.3. Representation of the achieved state of expansion 202 17.4. TRL assessment 202 17.5. References 204 18. Gas engines/gas turbines for hydrogen combustion 207 18.1. Technology description 207 18.2. Estimation of potential 208 18.3. Representation of the achieved state of expansion 211 18.4. TRL assessment 211 18.5. References 213 19. Chemicals-to-Power – Fuel cells 214 19.1. Technology description 214 19.2. Estimation of potential 218 19.3. Representation of the achieved state of expansion 221 19.4. TRL assessment 223 19.5. References 225 20. Interim conclusion for TRA 227 21. Evaluation of system integration 230 21.1. Modelling approach 230 21.2. Scenarios for a renewable energy supply 238 21.3. Results of the simulation 238 21.4. Consequences 244 21.5. References 245 22. Summary and Outlook 247 23. Abbreviations and symbols 249 24. Indices 254 25. List of Figures 255 26. List of Tables 258 27. Appendix 260 27.1. DOE TRL definition and description 260 27.2. Visualized summary of TRLs 262

Ce travail s’inscrit dans le cadre de l’étude d’un système de stockage et de restitution des surplus d’énergie électrique de sources renouvelables. L’objectif de l’étude est d’évaluer la capacité du concept à absorber l’intermittence de la production électrique à travers l’analyse de la flexibilité des procédés choisis. En phase de stockage, l’unité utilise un procédé d’électrolyse basse température à membrane échangeuse de proton (PEM) pour produire l’équivalent de 200 MW d’hydrogène. Ce gaz sera combiné au dioxyde de carbone dans une série de réacteurs de méthanation pour former l’équivalent de 155 MW de substitut de gaz naturel. La phase de déstockage est réalisée au sein d’un cycle d’oxy-combustion d’une puissance installée de 480 MW. Ce cycle permet de restituer l’énergie contenue dans les gaz stockés et de produire le CO2 requis pour le procédé de méthanation. L’étude énergétique en régime stationnaire de cette installation montre que l’efficacité du procédé d’électrolyse atteint 69,3%, celle du procédé de méthanation 82,2% et celle du cycle d’oxy-combustion 51,8% sur PCS. L’analyse en régime transitoire de la phase Power-to-Gas permet d’identifier les stratégies de contrôle adaptées aux variations temporelles de conditions opératoires. Ces stratégies visent à permettre au système de couvrir des plages de fonctionnement plus larges et d’absorber plus de puissance électrique. Il s’est avéré que la production du méthane de synthèse peut s’étendre sur des plages de fonctionnement allant de 48% à 100% de la puissance nominale sans aucun apport énergétique extérieur. Le cas d’étude réalisé pour le couplage de l’unité avec un parc éolien de 300 MW permet d’évaluer les performances du Power-to-Gas en fonction de la variation de la source électrique. / The present work deals with the conceptual study and process design of a storage and recovery unit for renewable energy. The suggested concept is able to absorb the intermittency of the electrical production as a result of the flexibility of the chosen processes. During the storage phase, the unit uses a Proton Exchange Membrane electrolysis system to produce 200 MW of hydrogen, which will then be combined to carbon dioxide in a series of methanation reactors to generate up to 155 MW of Substitute Natural Gas. The recovery phase is carried out in a 480 MW oxy-combustion cycle which is not only able to restore the electrical energy but also provides the required carbon dioxide for the methanation process. The conducted steady state evaluation as well as the sensitivity analysis for the studied plant showed that the overall efficiency on HHV basis can reach up to 69.3% for the electrolysis process, 82.2% for the methanation process and 51.8% for the oxy-combustion cycle. The follow-up unsteady state analysis of the Power-to-Gas process aimed to identify the necessary control strategies adapted to operating conditions variation over time. Such strategies should enable the system to cover a wider load range and subsequently absorb more electrical power. It was found that, by making the right adjustments, the production of synthetic methane can be fulfilled at ranges between 48% and 100% of the nominal power without any external energy requirement. A case study was carried out where the unit was coupled with a 300 MW wind to assess the performance of the Power-to-Gas process under fluctuating electrical source conditions.

L'objectif de ces travaux de thèse était de concevoir et de développer un outil de simulation et d'optimisation multicritères de centrales couplant des sources d'énergies renouvelables (EnR) et des moyens de stockage. L'optimisation porte sur le dimensionnement de l'installation (taille des unités de production EnR et de stockage) et sur la ou les stratégies de gestion de la centrale EnR-stockage selon des critères technico-économiques évalués par l'outil. L'originalité de l'outil développé réside dans la modularité de définition de l'architecture EnR-stockage, dans la prise en compte de plusieurs niveaux de modélisation (échelle et précision) des différents composants du système et dans l'intégration du vieillissement. L'outil développé est également illustré sur des cas d'études afin d'apprécier sa pertinence. / The objective of this work was to design and develop a simulation and multi-criteria optimization tool of energy systems composed of renewable energy (RE) production and storage units. Optimization concerns the systems sizing (renewable production and storage units) and the systems control strategies based on techno-economic criteria. Originality of the tool resides in the modularity of definition of the RE-storage plant architecture, in taking into account several levels of modeling (scale and accuracy) of the different system components and in the consideration of ageing through performances degradation. The developed tool is also illustrated on application cases to highlight its usefulness.

This thesis is a part of the research work for Azelio TES.POD (Thermal energy storage. power on demand). It is a patented thermal energy storage system developed by Swedish cleantech company Azelio AB. The objective of this thesis work to find an alternative charging technology system that can be validated to be efficient and safe in operation for the charging of TES.POD. Induction heating technology is chosen as an alternative charging solution. Derived design steps to implement induction heater as a charging unit then selection of PCM container compatible with induction heater. Later simulating to evaluate total flux path in Finite Element Method Magnetics (FEMM) simulation tool which proposes the electrical results. The electrical performance of the induction heater indicates almost 9% higher electrical losses than the charging mechanism of the existing TES.POD design. However, from a safety standpoint, the alternate charging approach appears to be safer in operation than the existing system. Additionally, it reflects better intuitiveness from a manufacturing viewpoint.