PhD Thesis by Gauthier Limpens (UCLouvain), Generating energy transition pathways: application to Belgium
On the 18th of June, Gauthier Limpens passed his PhD thesis. Through his 5 years of work and a strong collaboration with the EPFL (Lausanne) he co-developed the model EnergyScope and an extension which enables the optimisation of the transition pathways of a country energy system. The models developed will be used and developed through the BEST-energy project.
The manuscript is available here. The following paragraphs present the executive summary of the thesis.
Context and purpose of the thesis
By 2050, the European Union is committed to become climate neutral. This political commitment requires the energy system to be metamorphosed and drastically reduce its dependence on fossil fuels, the main sources of greenhouse gas emissions. A major debate confronts the different visions of the low-emission energy system, as well as the path to be adopted to reach this goal. Studies are regularly published on this subject, but the assumptions and models used are only partially shared, hindering the ability to challenge the work that has been done, or to update it. The objective of this work is to set up an open source methodology and to apply it to the case of Belgium.
The methodology consists of three steps. First we seek to understand the different strategies of a low emission energy system. This involves answering questions such as: what is the role of storage technologies? Or, how to integrate intermittent renewable energies? The analysis of the different options reveals the most plausible low-emission energy system. Secondly, as the model is based on multiple projections of prices, availabilities, efficiencies, etc., we analyse the impact of the uncertainties on these parameters and identify the most critical ones, i.e. those that will influence the most the cost of the system. Thirdly, the transition path to reach the low emission target is optimised in order to have the road-map from today’s system to tomorrow’s low emission system.
A low emission energy system relies on a mix of solutions
In the case of Belgium, which can be partly transposed to several European countries, the optimal solution is a mix: massive deployment of endogenous renewable energy, implementation of efficient technologies, and if this is not enough, importing electricity and renewable fuels from abroad. Primary energy consumption can be reduced by 40% by using more efficient technologies, such as cogeneration, and coupling the energy sectors, mainly with electric mobility and heat pumps. Then, based on this reduced primary energy demand, 50% of it can be produced locally and based on renewable energies: 60 TWh/y of biomass, 60 TWh/y of solar and 35 TWh/y of wind. Finally, the remaining 50% will be imported renewable fuels and electricity from our neighbours. The hypothetical use of additional renewables, such as geothermal energy or an extension of offshore wind farms, is beneficial to the system and reduces the dependence on foreign countries. These resources first need to be proven. The benefit of the mix is illustrated in the following figure where each curves represent a scenario with an abundant resource (i.e. above the expected potential):
On top of these scenarios, an additional one represents the extension of 2 GW of existing nuclear capacity.
Accounting for uncertainties qualifies the strategies
A global sensitivity analysis shows that, out of the hundreds uncertain parameters accounted, only a few of them are driving the uncertainty on the total cost of the system. The following figure illustrates the impact of each of the parameters on a low emission energy system in 2050:
The y-axis is logarithmic which emphasises the dominant role of top parameters. From the top-4, three groups of parameters can be listed, by order of importance: the price of renewable fuels, the extension of nuclear power beyond 2025 and the fuel cells characteristics (price and efficiency). Renewable fuels include the transformation of biomass into fuel and also the use of excess renewable electricity to produce hydrogen and eventually more complex molecules. These fuels production cost, and therefore their price, will be important. The uncertainty on their price changes the energy strategy: the highest the price, the highest the energy efficiency of the system. Today’s nuclear power plants are amortised and if their safety can be proven, a partial extension will economically and technically facilitate the transition to a low-emission society. Finally, the fuel cells are used in vehicles and cogeneration. If their price is low and their efficiency high, most of the mobility (cars, buses, trucks) will rely on this technology. In addition, heat and electricity will be produced on a domestic scale through cogeneration with hydrogen or gas. But if fuel cells don’t achieve this performance, then they may not appear in tomorrow’s system.
To facilitate decision-making, the uncertainty about the total cost of the system must be reduced. This requires to focus on a dozen uncertain parameters. As an illustration, reducing the uncertainty on the top-4 parameters can reduce the system cost uncertainty by 80%. Others parameters’ uncertainty, such as the one for the cost of wind power, will have limited influence on decision making because this technology will be deployed in all scenarios.
The transition pathway gives the road-map to follow
Optimising the transition pathway between 2015 and 2050 illustrates the priorities to be taken in each of the sectors and the efforts made in one sector to facilitate the integration of certain technologies into other sectors. As an example, the heat sector is strongly electrified and, as it can behave as a flexible electricity consumer, it facilitates the integration of intermittent renewables (solar and wind). Moreover, having a global view of the transition enables a sector to change progressively. For example, the transition to hydrogen mobility is progressive with hydrogen produced first from fossil fuels (steam reforming of natural gas) and then using renewable electricity (electrolysis) or imported. The following image represent, non-exhaustively, the decision taken in each sectors.