On the role of energy infrastructure in the energy transition. Case study of an energy independent and CO2 neutral energy system for Switzerland

The transition towards renewable energy is leading to an important strain on the energy grids. The question of designing and deploying renewable energy technologies in symbiosis with existing grids and infrastructure is arising. While current energy system models mainly focus on the energy transformation system or only investigate the effect on one energy vector grid, we present a methodology to characterize different energy vector grids and storage, integrated into the multi-energy and multi-sector modeling framework EnergyScope. The characterization of energy grids is achieved through a traditional energy technology and grid modeling approach, integrating economic and technical parameters. The methodology has been applied to the case study of a country with a high existing transmission infrastructure density, e.g., Switzerland, switching from a fossil fuel-based system to a high share of renewable energy deployment. The results show that the economic optimum with high shares of renewable energy requires the electric distribution grid reinforcement with 2.439 GW (+61%) Low Voltage (LV) and 4.626 GW (+82%) Medium Voltage (MV), with no reinforcement required at transmission level [High Voltage (HV) and Extra High Voltage (EHV)]. The reinforcement is due to high shares of LV-Photovoltaic (PV) (15.4 GW) and MV-wind (20 GW) deployment. Without reinforcement, additional biomass is required for methane production, which is stored in 4.8–5.95 TWh methane storage tanks to compensate for seasonal intermittency using the existing gas infrastructure. In contrast, hydro storage capacity is used at a maximum of 8.9 TWh. Furthermore, the choice of less efficient technologies to avoid reinforcement results in a 8.5%–9.3% cost penalty compared to the cost of the reinforced system. This study considers a geographically averaged and aggregated model, assuming all production and consumption are made in one single spot, not considering the role of future decentralization of the energy system, leading to a possible overestimation of grid reinforcement needs

Assessment of green mobility scenarios on European energy systems

The paradigm shift in the energy policy of the European Union confronts the member states with the task of developing future renewable and fossil-free energy systems. This change involves the installation of intermittent renewable energy sources such as wind and solar, which induce a demand for storage capacity. The modelling of smart cities with electrified mobility allows the optimisation of mobility and renewable energy combination. However, in order to analyse the system as a whole, system-based cross-sectoral energy models have to be used, including intersectoral exchange. Within this thesis the system-based and cross-sectoral energy planning tool EnergyScope will be adapted to mobility, in order to analyse the influence of different vehicle technologies on the energy system of two main agents of the European Union. Historical mobility data was analysed to predict the mobility behaviour of France and Germany for the year 2050. These estimates were integrated into two EnergyScope models with different temporal resolution and optimized according to thermoeconomic criteria. The model with the monthly resolution allowed to estimate the impact of vehicles with batteries, fuel cells, synthetic fuels and biofuels on the whole energy system. The model based on typical days allowed to visualize the influence of smart mobility such as vehicle-to-grid technologies in electric vehicle composition. The efficiency of the monthly model also allowed a Morris and Monte Carlo uncertainty analysis of the estimated parameters. The results show that the vehicle composition strongly depend on the existing renewable energy potential, with electric vehicles being the preferred technology for private passenger transport. Fuel cells are preferably used for road freight transport where electric trains cannot take over. Despite different energy strategies of France and Germany, the optimized energy systems differ mainly in primary energy consumption, with the installed technologies being largely the same. The promotion of synthetic or biofuels leads to an increase in primary energy demand, which pushes up emissions and costs compared to electrically based mobility. Hydrogen benefits from the possibility of energy storage through power-to-gas, although fuel cells for private mobility are not the pareto-optimal solution due to their higher purchase price compared to electric vehicles

EnergyScope Valais - Case study of Regionalisation

This document is the report of my second semester project at IPESE. Its objectives were to validate the energetic strategy 2035 of the “Canton du Valais”. The lecturer will see how the Swiss-Energyscope model has been adapted to the canton of Valais to compare the scenario given by canton of Valais. By modelling the energetic model for the canton of Valais and simulating the outcome 2050, the role of Valais as part of Switzerland had to be considered. The Swiss Energyscope (SES by Stefano Moret [2]) regionalised by cantons has been created. The exchange of ressources (Waste, Wood, Gas and Electricity) has been visualised using a chord diagram. We were able to show the differences when optimising on a more global aspect. In fact, the electricity production in Valais for 2050 7 times higher when optimising Valais as a part of Switzerland compared to the optimisation on Valais only. This higher electricity generation has a 50% higher total cost. We were able to validate the energetic strategy, due to same ressource use and similar cost (8% difference)

Image énergétique de la commune de Sion - une inventarisation des ressources et demande

Le but de ce projet de semestre est de réaliser un inventaire des données concernant le potentiel énergétique de la commune de Sion et les rendus visible dans uns système GIS1 en une première étape. La deuxième partie est dédiée à l’estimation du potentiel disponible et d’analyser les différences entre plaine et la montagne. Les résultats du potentiel seront integrées dans un le modèle Energyscope, qui sera adapté aux caractéristiques du pérmiètre étudié. La simulation de l’image énergétique permettra de modélliser l’image énergétique et, sous contraintes, trouver des solutions renouvelables uniquement

Application of data reconciliation methods for performance monitoring of power-to-gas plants

Power-to-gas plants have recently gained more attraction as these storage systems can be deployed in the European energy grid to ease the integration of renewable energy sources. Most studies in this field address several aspects, from their technical performances to their economic costs and environmental impacts. However, these novel systems are inherently subject to large variations of energy supplies and operating costs, but few works, if none, deal with their real-time monitoring. Deriving consistent and satisfactory results of measurements data is essential and possible only by application of data validation and reconciliation (DVR) methods. In the present study, conventional and advanced DVR techniques were combined with process models and cross-correlation techniques to reconcile the measurement sets, and their outcomes were compared for two case studies. This approach aims at identifying the most relevant measurements and providing a better understanding of the system behaviour under different loads. The results underlined the impact of the number, type and location of redundant measurements on the quality of the reconciled values. For both plants, the measurement uncertainties would be greatly reduced by a better monitoring of the flow and temperature sensors at the inlet and outlet of the methanation reactors/processes. In addition, a net improvement of the model robustness was obtained with the advanced DVR approach, at the expense of a greater resolution time. This computational burden was not deemed critical if measurement datasets were assessed with a timestep in the order of minutes to hours

A modelling framework for assessing the impact of green mobility technologies on energy systems

A successful decarbonisation of the European Union, coupled with a high integration of renewable energy and ambitious targets for energy efficiency, can only be reached with a significant contribution from the transportation sector. It currently represents a quarter of the total greenhouse gas emissions and is shifting from fossil fuels to alternative energy carriers (biofuels, e-hydrogen, electricity) and propulsion systems (hybrid, electric and fuel-cell vehicles). Decarbonising this sector can follow multiple pathways, each having different costs, impacts and implications for the other sectors (industry, residential and services). This paper presents a method to analyse the impact of each decarbonisation pathway in the mobility sector on the overall energy system, using the EnergyScope model. The proposed methods include: (i) an estimation of the hourly demand profiles for short- (local) and long-distance mobility, using annual projections and traffic measurements; (ii) the development of black-box vehicle models of road, rail and aviation technologies; (iii) the modelling of the associated infrastructures, from the fuel conversion processes to the charging stations; and (iv) the use of Monte-Carlo-based tools to account for technical and economic uncertainties. This method allows to assess the effects of mobility decarbonisation pathways on the energy system, from the large-scale deployment of vehicle-to-grid technologies to the integration of biofuel- and hydrogen-based vehicles. France has been taken as case study, considering 2050 as time horizon. The results showed the importance of a holistic approach to suggest cost- and energy-efficient decarbonisation pathways in the transport sector that can affect the overall energy system

Appendix: Regionalisation in high share renewable energy system modelling

This document corresponds to the appendix of the paper Regionalisation in high share renewable energy system modelling by Schnidrig et al. in redaction, and is based on the Master thesis of Amara Slaymaker 2021, giving additional information about the methodology, data used and assumptions made. This Appendix is structured in three parts. First the methodological details of the energy system model EnergyScope are given, followed by (ii) the clustering method details with data source sand results and (iii) additional results and validation of the model