Jonas Schnidrig

Towards Sustainable Energy Futures - Infrastructure and Prosumer Integration, Decentralization and Sustainability in Renewables-based Energy System Modeling

J. Schnidrig / F. Maréchal; M. D. Margni (Dir.)

The global energy sector stands at a critical juncture, with the imperative shift towards renewable energy sources posing challenges and opportunities for existing infrastructure and societal norms. This thesis explores the multifaceted dynamics of transitioning energy systems, mainly focusing on Switzerland as a case study for innovative energy system planning and decentralization methodologies. This thesis addresses the strain on energy infrastructure due to renewable energy integration. It presents a novel methodology to characterize energy vector grids and storage within the multi-energy and multi-sector modeling framework EnergyScope. It shows that optimal integration requires 61-82% reinforcement at local distribution grids, highlighting a strategic pivot towards renewable sources without significant transmission-level enhancements. This finding challenges the prevailing emphasis on transmission grid reinforcement, proposing a more nuanced approach to grid adaptation that balances intermittencies of renewable technologies, compensated by the Hydro Dam storage used at its maximal capacity of 8.9TWh in combination with Methane storage, thus increasing the seasonal Swiss storage capacity by 43-58%. Exploring decentralized energy systems reveals that strategic decentralization can reduce system costs by 10% to annually 1230CHF/cap and enhance self-consumption by up to 68%compared to a centralized model. By juxtaposing decentralized and centralized energy planning models, this thesis illustrates the potential for hybrid models to foster system resilience and efficiency, thereby contributing to a more sustainable energy future, in contrast with traditional models, underscoring the importance of adaptive planning strategies. Further analysis quantifies the roles of various actors in Switzerland's energy system decentralization, identifying the complexities of transitioning to decentralized, renewable energy sources. The emphasis on dynamic interactions among system actors introduces a new perspective on optimizing energy systems for sustainability and equity, challenging conventional approaches by advocating for a strategic balance that accommodates regional variations and actor-specific dynamics. Applying the methodology identifies the tradeoffs between the energy system service providers and the regional prosumers, leading to energy service costs of 2-8CHF/m2 ERA for Alpine districts and at a maximum of 32-125CHF/m2 ERA for urban districts under the assumption of a guaranteed profit of 5% for the energy system service providers. Lastly, the thesis aims at understanding the trade-offs between environmental and economic objectives in energy system planning. By implementing LCA metrics in the energy system modeling, we demonstrate the potential for aligning economic efficiency with environmental sustainability by reducing system costs by 15% to 47% alongside a 31-81% reduction in environmental impacts, cautioning against burden-shifting risks. Using multi-objective optimization and uncertainty analysis, we demonstrate that optimizing for environmental indicators leads, at the same time, to economic and environmental benefits in each area of protection compared to the current system. In contrast, environmental indicators correlate, but compromise at environomic scales needs to be taken. [...]

Internal pricing in integrated energy system design

J. Granacher; J. Schnidrig; A. Chuat; D. Lepour; C. Terrier  et al.

Environmentally sustainable and economically viable process and energy systems are imperative to a successful energy transition. Often, design configurations are derived from a global perspective, in which the individual needs and interests of actors within the system are overlooked. This work proposes an approach for designing a system considering its entire scope and acknowledging the individual actors within the system. System solutions are generated from the perspective of a universal decision-maker who is aware of the whole system, and the obtained solution space is analyzed regarding implications for the individual actors. Thereby, prices of internal exchanges between actors that would allow for the realization of the optimal integrated system solution while granting each actor their economic objectives are derived. The approach is demonstrated in three distinct case studies varying in size: a bio-based industrial site, a renewable energy community, and a national energy system. All case studies yield system configurations allowing the actors to profit from economic benefits emerging from synergies from internal cooperation. Further research must delve into diverse system settings and actor paradigms to enhance the robustness and applicability of the derived insights.

Between green hills and green bills: Unveiling the green shades of sustainability and burden shifting through multi-objective optimization in Swiss energy system planning

J. Schnidrig; M. Souttre; A. Chuat; F. Maréchal; M. D. Margni

The Paris Agreement is the first-ever universally accepted and legally binding agreement on global climate change. It is a bridge between today's and climate-neutrality policies and strategies before the end of the century. Critical to this endeavor is energy system modeling, which, while adept at devising cost-effective carbon-neutral strategies, often overlooks the broader environmental and social implications. This study introduces an innovative methodology that integrates life-cycle impact assessment indicators into energy system modeling, enabling a comprehensive assessment of both economic and environmental outcomes. Focusing on Switzerland's energy system as a case study, the model reveals that optimizing key environomic indicators can lead to significant economic advantages, with system costs potentially decreasing by 15 % to 47 % by minimizing potential impacts from the current system still operating with fossil technologies to an alternative only relying on renewable and where the impact are mainly related to the construction of the infrastructure. However, a system optimized solely for economic efficiency, despite achieving 63 % reduction in carbon footprint compared to 2020, shows a potential risk of burden shift to other environmental issues. The adoption of multi-objective optimization in this approach nuances the exploration of the complex interplay between environomic objectives and technological choices. The results illuminate pathways towards more holistically optimized energy systems, effectively addressing trade-offs across environmental problems and enhancing societal acceptance of the solutions to this century's defining challenge.

Power Shift: Quantifying the Role of Actors in the Multi-Actor Swiss Energy System Decentralization

J. Schnidrig; A. Chuat; J. Granacher; C. Terrier; F. Maréchal  et al.

The global transition to decentralized energy systems signifies a fundamental transformation toward sustainable energy paradigms. This study specifically focuses on the Swiss energy system, analyzing how dynamic pricing influences the strategic decisions of different actors. The main contributions include 1) a detailed examination of pricing models tailored to the Swiss context, 2) an exploration of strategic financial burden shifts among end-users, TSOs, and DSOs, and 3) a comparison of decentralized versus centralized energy models, highlighting their respective efficiencies and resilience. This research differentiates from existing literature by providing an in-depth actor-based analysis within a Swiss context, offering valuable insights into decentralized energy system optimization. This study tackles the problem of how pricing influences strategic decisions across different actors in Switzerland’s evolving decentralized energy landscape. Here we show that a carefully tailored pricing model, designed for the Swiss context, enables optimized strategies that balance local efficiencies with systemic equity and resilience. The analysis reveals that decentralized approaches, in contrast to centralized models, not only accommodate diverse stakeholder preferences but also enhance system robustness against market and operational disruptions. Moreover, the study illustrates the strategic financial burden shifting where end-users compensate for cost shifts, with observed additional costs up to 5200 CHF/year cap when service providers are prioritized as objective actors. Notably, the most frequently selected system configuration in the primal problem, which optimizes the total system costs, aligns with the preferences of TSO and DSO for a 47.1 GW PV deployment. However, end-users demonstrate a preference for increased PV installations, constrained by urban grid capacities. Additionally, the study highlights significant regional disparities across Switzerland, necessitating tailored pricing approaches that reflect varied urban forms. The emergence of prosumers catalyzes new business models, redistributing investments across TSOs (256–261 CHF/cap/year), DSOs (244–413 CHF/cap/year), and prosumers (556–764 CHF/cap/year), showcasing the evolving dynamics of energy system economics.

Identification of typical district configurations: A two-step global sensitivity analysis framework

A. Chuat; C. Terrier; J. Schnidrig; F. Marechal

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the imperative of leveraging renewable indigenous energy sources becomes evident. However, as such technologies are integrated into the existing system, it is necessary to shift from the current centralized infrastructure to a decentralized production strategy. This paper presents a method to identify a panel of technological solutions at the district level, intended to reduce complexity for the integration of decentralized models into a national-scale model. The framework's novelty lies in combining a global sensitivity analysis for solution generation with clustering to identify typical configurations. The global sensitivity analysis is performed on a mixed integer linear programming model, which optimally sizes and operates district energy systems. The sensitivity analysis determines the most influential parameters of the model using the Morris method and provides a representative sampling of the solution space by leveraging the Sobol sampling strategy. The latter is then clustered using a density-based algorithm to identify typical solutions. The framework is applied to a suburban and residential Swiss neighborhood. The first outcome of the research is the high sensitivity of the model to energy carrier prices. As a result, Sobol's sampling space separates itself into two system types: those based on a natural gas boiler and those relying on a combination of electrical heaters and heat pumps. For both types, the electricity demand is either fulfilled by PV panels or electricity imports. The identified configurations showcase that the framework successfully generates a panel of solutions composed of various system configurations and operations being representative of the overall solution space.

Power to the People: On the Role of Districts in Decentralized Energy Systems

J. Schnidrig; A. Chuat; C. Terrier; F. Marechal; M. Margni

Highlights Integration of decentralized models with a centralized national energy system framework. Strategic reduction in photovoltaic (PV) installation requirements and system cost through decentralized approaches. Optimization of self-consumption to minimize grid reinforcement needs. Identification of key trade-offs in PV integration and the importance of energy storage and grid management. Exploration of electrification strategies, power-to-methane technologies, and the use of existing gas grids to bridge decentralized and centralized systems.Abstract The transition towards renewable and decentralized energy systems is propelled by the urgent need to address climate concerns and advance sustainable development globally. This transformation requires innovative methods to integrate stochastic renewable sources such as solar and wind power and challenging traditional energy paradigms rooted in centralized and continuous energy production. The present study focuses on the Swiss energy system to explore the optimization of energy planning strategies that incorporate decentralized energy production within a centralized framework. Here, we show that a strategic approach to decentralization can significantly reduce annual system costs by 10% to CHF 1230 per capita and increase self-consumption to 68% of the decentralized PV production, emphasizing the need for a hybrid energy-planning model that balances centralized and decentralized models for enhanced system resilience, efficiency, and cost-effectiveness. This research underscores the strategic importance of diversifying energy sources, enhancing energy storage, improving grid flexibility, and laying a foundational framework for policy making and strategic planning. It encourages further investigation into climate impacts, technology synergy, and the integration of district heating, aiming to establish a resilient, sustainable, and autonomous energy future.

Closing the balance - on the role of integrating biorefineries in the future energy system (vol 7, pg 4839, 2023)

J. Granacher; R. Castro-Amoedo; J. Schnidrig; F. Marechal

Correction for 'Closing the balance - on the role of integrating biorefineries in the future energy system' by Julia Granacher et al., Sustainable Energy Fuels, 2023, 7, 4839-4854, https://doi.org/10.1039/D3SE00473B.

Closing the balance - on the role of integrating biorefineries in the future energy system

J. Granacher; R. Castro-Amoedo; J. Schnidrig; F. Marechal

Fuels from bio-based resources hold the potential to supply fossil fuel alternatives at reasonable economic and environmental expenses that can assist emission reduction in the transportation sector. However, apart from a general need to reduce fossil-based emissions, the shift from fossil energy carriers to renewables is likely to cause mismatches of supply and demand of electricity. This paper investigates the potential of integrated biorefineries to assist in balancing electricity demand and supply while co-producing fuels from biomass. At the example of a pulp mill and a nearby residential district, synergies between biomass valorization at an industrial site and residential energy demands are explored regarding defossilization potential and economic impacts. A Kraft pulp mill is integrated with thermochemical conversion processes, converting residuals of the pulping process to fuel. Power-to-fuel and fuel-to-power processes are enabled for increasing flexibility and enhancing additional fuel production in times of electricity oversupply. Multi-objective optimization is coupled with systematic solution generation and exploration approaches for deriving viable system configurations. Results indicate that direct emissions of the mill and the residential district can be reduced by up to 90% compared to the non-integrated system. Optimization of the prices of internal exchanges between mill and district reveals that this reduction comes at added expenses for all stakeholders, but that a reduction of emissions by approximately 50% provides economic benefits. Extrapolating the analysis to the European level reveals that the benefits of integration depend largely on the energy portfolio present in the considered region.

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

J. Schnidrig; R. Cherkaoui; Y. Calisesi; M. Margni; F. Maréchal

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.

Identification of typical district configurations: A two-step global sensitivity analysis framework

A. Chuat; J. Schnidrig; C. Terrier; F. Maréchal

The recent geopolitical conflicts in Europe highlighted the sensibility of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy system configurations to ensure energy supply stability, it is necessary to understand which parameters modulate the system configuration. This paper presents a framework that identifies a panel of technological solutions at the district level. First, a global sensitivity analysis is performed on a mixed integer linear programming model which optimally size and operate the system. The sensitivity analysis determines the most influential parameters of the model and provides a representative sampling of the solution space. The latter is then clustered using a density-based algorithm to identify typical solutions. Finally, the framework is applied to a suburban and residential Swiss neighborhood. The main outcome of the research is the high sensitivity of the model to energy carrier prices. As a result, the sampling space separates itself into two system types. The ones based on a natural gas boiler, and the ones relying on a combination of electrical heater and heat pump. For both types, the electricity demand is either fulfilled by PV panels or by electricity imports.

Integration of Life Cycle Impact Assessment in Energy System Modelling

J. Schnidrig; J. Brun; F. Maréchal; M. Margni

The Paris agreement is the first-ever universally accepted and legally binding agreement on global climate change. It is a bridge between today’s and climate-neutrality policies and strategies before the end of the century. However, government and private companies still struggle to develop cost-effective carbon-neutral strategies. Energy system modeling has proved essential in creating strategies to generate carbon-neutral scenarios under minimal costs. However, cost minimization does not necessarily lead to publicly acceptable solutions nor generate configura- tions that minimize environmental impacts. Here we show a methodology to integrate LCIA indicators in an energy system model, assessing the impact of energy system configurations on economic and environmental aspects. Here we show a methodology to integrate life cycle assessment metrics in an energy system model to account for (i) emissions and impacts beyond the operation of the energy system itself and (ii) identify configurations optimizing both economic and environmental aspects. The model is applied to the case study of Switzerland and shows that with little modifications to the energy system configuration, carbon neutrality can be reached under the cost minimization objective while identifying trade-offs with other environmental issues. This work allows the generation of MOO of energy systems, minimizing burden shifting of environmental impacts and generating robust solutions for the energy transition, increasing social acceptance towards the biggest challenge of the 21st century.

Regionalisation in high share renewable energy system modelling

J. Schnidrig; X. Li; A. Slaymaker; T.-V. Nguyen; F. Maréchal

Governments are setting ambitious targets to tackle the issue of global warming by switching to renewable energy sources and reducing CO2 -emissions. For example, as announced in November 2020, Canada aims to achieve net zero GHG emissions by 2050. Large countries such as Canada cannot easily apply a global energy strategy, each region having different energy demands and potentials. Optimization-based energy models can be used to simulate and compare different energy transition pathways - one of them is based on the use and production of hydrogen. For this purpose, other methods of defining regions within energy system models are considered by considering (i) political boundaries and (ii) clustering geographical and demographic characteristics. We propose a new modeling strategy by comparing two region definition strategies applied to the case of Canada, assessing the competing role of electricity and Hydrogen as energy vectors. Our case study shows the electrification of the energy system is essential to achieve net-zero emissions across all sectors to satisfy the mobility, heating, and electrical demands. In contrast, the role of hydrogen in the power, industrial, and transport sectors for valorizing excess electricity and decarbonizing them is identified.

Prospective study on the cost evolution for key energy technologies

X. Li; M. Souttre; J. Schnidrig; F. Maréchal

Drastic variations of energy costs are witnessed in past decades, especially for low-carbon technologies, where decreasing and increasing trends co-existed. Estimating the cost evolution in the future is hence essential in long-term energy planning. Despite a number of existing studies, the estimated costs show strong hetero- geneity. Additionally, emerging technologies, such as electrolysis and CCUS (carbon capture, utilisation and storage), have gained limited attention. To improve the plausibility of the cost projection, we analysed the rela- tionship between accumulated installation and the corresponding CAPEX for 14 low-carbon technologies, and applied 5-8 learning curves (LRs) via Non-Linear Optimization (NLP) for projecting the cost evolutions towards 2050. The LRs were carefully selected based upon the index of Coefficient of Determination, and calibrated by comparison to a bunch of existing literature. Based upon our results: (1) residential PV and onshore wind rank the highest and lowest respectively in terms of the decreasing potential; (2) the majority of energy technologies are promising to achieve 36% - 74% cost reduction in 2050 compared to 2020, with a mean value around 50%. This study can be helpful as benchmark for energy stakeholders in decision-making towards carbon neutrality.

Where is the money ? A decomposition of monetary flows behind fossil fuels

X. Li; J. Schnidrig; R. Briguet; F. Maréchal

Transition from fossils to renewables is leading to radical societal changes. Shifting the capital from fossils to renewables is commonly accompanied with political concerns, such as energy autonomy, domestic employment etc. Despite a decreasing trend in recent decades, energy cost remains the major bottleneck for a massive penetration of renewables, resulting in diverse policies with respect to carbon taxes and renewable subsidies. This study focuses on analysing the opportunities for Switzerland within the energy transition, through a systematic assessment on the curent petroleum supply chain with associated cost decomposition. By modeling a fossil fuels supply chain, it is within reach to estimate the final price decomposition of petroleum products. To be more precise, the aim of this study, based on open source data, is to highlight how the money spent in fossil fuels is distributed in the industry and to examine opportunities an energy transition could offer to the country in question. Applied to Switzerland, but applicable to any other country, the results show that more than 30% of the final price is spent and invested outside the country. For instance, the Swiss net import of fossil fuels alone amounted to 7.2 billions CHF in 2019. If this capital had been invested in PV, Switzerland could have produced 33.5 TWh/year, constituting 60% of Swiss electric production in 2020. In the near future, this reinvestment in PV would contribute more generally to the full development of solar energy, whose walls and roofs potential in the Swiss context is estimated to be around 67 TWh/year.

Assessment of the role of infrastructure in high share renewable energy systems

J. Schnidrig; X. Li; F. Maréchal

The transition of the global energy sector from fossil-based towards a zero-carbon system is a necessity to mitigate the impacts of climate change. The ratification of both, the Paris agreement in 2015 and the European Green Deal in 2019, illustrates the political will to reach climate neutrality. Thereby, one major focus lies on the development of the power section with the aim to include a high share of renewable sources, whilst using the synergies of other energy vectors for conversion, storage, and transportation. However, a successful decarbonisation of the energy sector is only achievable if the energy policies are accepted and implemented by the corresponding actors and stakeholders. The question arises: How can the power system in symbiosis to other energy vectors safely include the required amount of renewable energies ? The aim of this paper is to develop a Mixed Integer Linear Programming (MILP) modelling methodology, helping to answer this question. The proposed methodology allows to model the role of energy independence in future multi-energy distribution systems on different scales. On the basis of the current infrastructure, the inter-cell exchanges of the network will be categorized in terms of efficiency and capacity. The main exchanges of electricity, natural gas and hydrogen and, where appropriate, biomass and waste will also be represented. This methodology will identify how global energy system modelling can help national and international decision makers at different levels of the society to understand and assess the impact of infrastructure on the energy system, answering the question of levels of centralization/decentralization (storage capacity, renewable production e.g) and grids capacity at various system levels depending on energy system objective functions (e.g overall investment costs, CO2 emission targets and import/export targets).

An analysis of the impacts of green mobility strategies and technologies on different European energy system

T.-V. Nguyen; J. Schnidrig; F. Maréchal

A successful decarbonization 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 transport. This sector currently represents a quarter of the total greenhouse gas emissions and is shifting from fossil fuels to alternative energy carriers and propulsion systems. Decarbonizing this sector can follow multiple pathways, each having different costs, impacts and implications for the other sectors (industry, residential and services). This paper focuses on the impact of different decarbonization paths in the mobility sector on the whole energy system of a country. The hourly and monthly resolution model named EnergyScope was used and applied to three European countries with different characteristics, namely France, Germany and Switzerland. Their energy resources, demands and policies are strongly different, which has an impact on the preferred decar- bonization pathway to follow, and on its final costs and environmental impacts. Regardless of the case study, the most cost- and energy-efficient pathway to decarbonize road and rail mobility is through a heavy electrification, with short-range electric vehicles and buses for local mobility, and either hy- drogen or long-range electric vehicles for long-distance. The most cost-optimum vehicle fleet depends strongly on the projected costs of fuel cell and batteries in the upcoming year, as well as on the wind and solar energy potential. Large-scale deployment of biofuels seems improper for road transport because of the small potentials for sustainable biomass harvesting and the high installation costs of direct air capture, but may be the only viable solution for aviation.

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

J. Schnidrig; T.-V. Nguyen; X. Li; F. Maréchal

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 transporta- tion 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, im- pacts 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 devel- opment 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.

Application of artificial intelligence on uncertainty analysis for long-term energy system planning

X. Li; D. Muller; J. Schnidrig; F. Maréchal

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

J. Schnidrig; T.-V. Nguyen; X. Li; F. Maréchal

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.

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

J. Schnidrig; T.-V. Nguyen; A. Santecchia; F. Maréchal

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.