Scenario modelling and optimisation of renewable energy integration for the energy transition

A large number of countries have engaged themselves in an energy transition towards more re- newable energy in their energy systems. Motivations stem mainly from the need to reduce CO2 emissions, and from a desire of their population to phase out technologies such as nuclear. Most of these countries promote biomass, wind and solar energy sources, among other possibilities. How- ever the current rate of deployment of renewable energy systems globally is not sufficient to reach the CO2 emissions reduction that would allow to maintain the global average temperature increase below the 2°C threshold. The main barriers to a wider integration of renewable energy systems are i) their limited realisable potential, ii) their still limited competitiveness, iii) their intermittence; iv) public acceptance often related to poor level of energy literacy amongst citizens. Citizens are key decision-makers. They must decide on energy policies and on the energy technologies they use, hence they have the power to foster or halt the energy transition. This thesis presents two different strategies for addressing the problem of the integration of re- newable energy sources for energy transitions. The first one (Chapter 1) consists in developing an energy modelling tool to help decision-makers understand the energy system and find their own answers. The modelling approach also includes a new methodology for the calculation of the total cost of a national energy system. A model of the Swiss energy system has been created following this approach, which serves as basis to develop the Swiss-Energyscope online calculator. This calculator and its model present an optimal trade-off between scientific rigour and user-friendliness, which allows the reproduction of the energy transition scenarios conceived by the Swiss Government, and consequently its use for energy policy making. The second strategy (chapters 2 and 3) profits from the possibilities offered by mathematical mod- elling and optimisation to analyse national energy systems, and derive insights for policy and decision-makers. First, a methodology using a mix-integer linear programming (MILP) model analyses biomass usage pathways to determine its optimal use in Switzeland in 2035. Second, in order to study the role of biomass, non-linear optimisation is applied to create future scenarios. (Chapter 3) focuses on the solutions to deal with the variability of renewable electricity. To this end, a MILP model with hourly time resolution is conceived to study the use of flexible electricity supply and demand options for the integration of renewable electricity. The optimisation methodologies are validated on case studies for the Swiss energy system. Regarding biomass, the results reveal that woody biomass chemical conversion technologies can allow for an overall better performance in terms of CO2 avoided emissions compared to direct combustion, as long as the produced biofuels are used in efficient technologies. Results also show that the combination of the gasification-methanation process of woody biomass with the production of H2 produced from excess electricity would allow to reduce the Swiss natural gas imports to zero by 2050. Concerning the integration of variable renewable electricity, the cost difference between using flexible electricity supply- and demand-options or electricity imports to deal with variable renewable electricity is below 2.5% of the total cost of the energy system

The Impact of Uncertainty in National Energy Planning

Concerns related to climate change and security of energy supply are pushing various countries to define strategic energy plans. Strategic energy planning for national energy systems involves investment decisions (selection and sizing) for energy conversion technologies over a time horizon of 20-50 years. This long time horizon requires uncertainty to be accounted for. Long-term planning for energy systems is often based on deterministic economic optimization and forecasts of fuel prices. When fuel price evolution is underestimated, the consequence is a low penetration of renewables and more efficient technologies in favor of fossil alternatives. This work aims at overcoming this issue by assessing the impact of uncertainty on strategic energy planning decisions. A classification of uncertainty in national energy systems decision-making is performed. A Global Sensitivity Analysis (GSA) is performed in order to highlight the influence of the model uncertain parameters onto the energy strategy. Optimization under uncertainty is then applied to a general Mixed-Integer Linear Programming (MILP) problem having as objective the total annual cost and assessing as well the IPCC Global Warming Potential LCIA indicator (CO2-equivalent emissions). The application focuses on the case study of Switzerland. It is shown that in the uncertain domain investing in more efficient and cleaner technologies can be economically optimal

The information platform energyscope.ch on the energy transition scenarios

Switzerland like many countries plans to undertake an energy transition and the government proposes different paths for 2035 and 2050 to achieve it. However the authors of this paper felt the need for a better information of the public on the energy matters. A special web-based information platform was introduced in 2015. The platform includes a calculator, a book providing 100 questions and answers on energy and a MOOC for citizens with more than 20 short lectures on the various aspects of the Swiss energy transition. Unlike other interactive energy scenario calculators our calculator offers the possibility to show monthly averages of demand and supply, highlighting the strong seasonal patterns occurring when considering most countries from the central to the northern parts of Europe. The calculator indicates the effects of the user’s choices on 6 main indicators (final energy, electricity balance, % of renewables, CO2 emissions, long term wastes and costs) While the underlying model has already been published, this paper intends to discuss the reactions following the introduction of such a platform. Reactions from minority, but very active groups, including climate change deniers, ultra-pronuclear and anti-wind power opponents have been noticed and highlight the very emotional nature of the topic. Scenarios for 2050 are presented and discussed as well as examples of a new scenario that can be made using the calculator. All main parameters such a socioeconomic, heating and cogeneration technologies, transportation, electricity generation can be adapted

Exergy assessment of future energy transition scenarios with application to Switzerland

Using an exergy based indicator is highly desirable to compare future national energy strategies. A new web- based information platform called energyscope.ch, informing the general public on the Swiss energy transition was presented at ECOS2016. This paper presents a new extension of the approach that we plan to call exergyscope.ch, clearly stating exergy and distinguishing between primary exergy, final exergy and useful exergy. This allows for a graphical interpretation of the exergy efficiency of each conversion step from primary exergy to final exergy, all the way to useful exergy. Different future energy scenarios for Switzerland are compared to illustrate the gain in exergy efficiency between different strategy choices. Monthly variations in exergy supply are considered by using an average reference temperature for each month. The analysis assesses the useful exergy requirement for all energy services including building and transportation. For heating and cooling services, the proposed framework is coherent with the introduction, reported earlier, of an exergy efficiency indicator in a Law on energy. Accordingly the global exergy efficiency for providing a given useful exergy service can be calculated by multiplying the individual exergy efficiency of each conversion steps. The useful industrial thermal exergy is introduced in a simplified manner with an average service temperature

Thermo-Economic Optimization of Integrated First and Second Generation Sugarcane Ethanol Plant

The sugarcane industry has been responsible in some countries for the production of most of the sugar and ethanol available in the world for internal and external markets. In this sector, ethanol can be produced by fermentation of sugars obtained directly from sugarcane biomass, commonly called 1st generation ethanol. New processes using the enzymatic hydrolysis technology of lignocellulosic residues like bagasse and sugarcane leaves as feedstock can increase the ethanol production in these plants, reducing the land requirements and the environmental of impact biofuels production in large scale. The lignocellulosic ethanol production using enzymatic hydrolysis technology is one of the most promising alternatives of 2nd generation biofuels, due to its high conversion efficiencies and low environment impact. Some problems like high water consumption and enzymes costs must be overcome in order to reach commercial scale. The process integration and thermo-economic optimization of the process can be important for the design of this process in a sugarcane autonomous distillery aiming at the cost and environmental impact reduction. In this paper a process integration of the sugarcane ethanol distillery model is carried out taking into account 1st and 2nd generation processes in the same site using sugars and bagasse as feedstock respectively. Conflictive objectives such as maximization of the electricity or ethanol production are adopted in a multi-objective optimization technique using evolutionary algorithms, in order to provide a set of candidate solutions considering different configurations of the ethanol production process design

Strategic energy planning for large-scale energy systems: A modelling framework to aid decision-making

Concerns related to climate change and security of energy supply are pushing various countries to make strategic energy planning decisions. This requires the development of energy models to aid decision- making. Large scale energy models are often very complex and use economic optimization to define energy strategies. Thus, they might be black-boxes to public decision-makers. This work aims at over- coming this issue by proposing a new modelling framework, designed to support decision-makers by improving their understanding of the energy system. The goal is to show the effect of the policy and investment decisions on final energy consumption, total cost and environmental impact. The modelling approach and the model structure are described in detail. Final energy consumption is represented as the sum of three main components: heating, electricity and transportation. In this framework, a sequential modelling strategy allows the assessment of the competition between electricity and fuels in the heating and transportation sectors without increasing the model complexity. A monthly resolution is chosen in order to highlight seasonality issues of the energy system. Developed with the goal of being easily adaptable to any large-scale energy system, the modelling approach is currently implemented within an online energy calculator for the case of Switzerland