Many studies have demonstrated the feasibility of fully renewable power systems in various countries and regions. Yet the future costs of key technologies are highly uncertain and little is known about the robustness of a renewable power system to these uncertainties. To analyze it, we build 315 long-term cost scenarios on the basis of recent prospective studies, varying the costs of key technologies, and we model the optimal renewable power system for France over 18 meteorological years, simultaneously optimizing investment and dispatch.Our results show that the total cost of a 100% system is not that sensitive to the power mix chosen in 2050. Certainly, the optimal energy mix is highly sensitive to cost assumptions: the installed capacity in PV, onshore wind and power-to-gas varies by a factor of 5, batteries and offshore wind even more. But the total cost will not be higher than today, and choosing a non-optimal electrical mix does not significantly increase this total cost. Contrary to current estimates of integration costs, this indicates that renewable technologies will become by and large substitutable.
Following the first oil crisis, France launched the worlds largest ever nuclear energy program, commissioning 58 new reactors. These reactors are now reaching 40 years of age, the end of their technological lifetime. This places France at an energy policy crossroads: should the reactors be retrofitted or should they be decommissioned? The cost-optimal decision depends on several factors going forward, in particular the expected costs of nuclear energy production, electricity demand levels and carbon prices, all of which are subject to significant uncertainty. To deal with these uncertainties, we apply the Robust Decision Making framework to determine which reactors should be retrofitted. We build an investment and dispatch optimization model, calibrated for France. Then we use it to study 27 retrofit strategies for all combinations of uncertain parameters, with nearly 8,000 runs. Our analysis indicates that robust strategies involve the early closure of 10 to 20 reactors, while extending the life of all other reactors. These strategies provide a hedge against the risks of unexpected increases in retrofit costs, low demand and low carbon prices. Our work also highlights the vulnerabilities of the official French government scenarios, and complements them by suggesting new robust strategies. These results provide a timely contribution to the current debate on the lifetime extension of nuclear plants in France.
In the context of climate change mitigation and the Paris Agreement, it is critical to monitor and understand the dynamics of greenhouse gas emissions over different regions of the world. In this study, we quantify the contributions of different drivers behind the observed emission decrease in Europe between 2009 and 2014. To this end, we build a novel dataset of deflated input-output tables for each of the 28 EU countries. This dataset enables us to conduct the first Structural Decomposition Analysis of emissions in European countries since the economic crisis. Our results show that the largest drivers of emissions have been the improvement in carbon intensity (−394 MtCO 2 e), largely offset by the economic recovery (+285 MtCO 2 e). However, other less intuitive drivers also played a significant role in the emission decline: changes in the production system (−104 MtCO 2 e), mostly driven by an increase in imports; the evolution of final demand patterns (−101 MtCO 2 e); a decrease in emissions due to household heating (−83 MtCO 2 e) and private transport (−24 MtCO 2 e), with a small offset from population growth (+39 MtCO 2 e). However, these aggregate figures mask significant variations between EU countries which we also document. This study highlights the importance of including changes in consumption patterns, trade and temperature anomalies in tracking and fostering progress towards the Paris Agreement goals.
The threat of climate change requires redirecting investment towards low-carbon sectors, and this shift generates heated debates about its impact on employment. Many studies exist, most of which use CGE or Input-Output (IO) models. However, the economic mechanisms at play remain unclear. This paper disentangles the channels of job creation and studies to what extent the results of simpler IO models diverge from CGE results.Using stylized models, we show that a shift in investment creates jobs in IO if it promotes sectors with a higher share of labour in value added, lower wages or a lower import rate. In CGE, the first two channels also yield job creation, but there is no positive impact of targeting low-imports sectors -unless these do not export. Then we undertake a numerical analysis of two policies: the installation of solar panels and weatherization in France. Both policies have a positive effect on employment, in both models, due to the high share of labour and low wages in these sectors. IO results provide a good approximation of CGE results for solar (-14% to +34%) and are slightly higher for weatherization (+22% to +87%).Our findings challenge the idea that renewables boost employment by reducing imports, but they also suggest that a double dividend can be achieved by encouraging low-carbon labour-intensive sectors. Highlights• We identify three channels of job creation when redirecting investments • Encouraging labour-intensive or low-wage sectors creates employment in CGE and IO models • Encouraging low-importing sectors generates a marked positive effect in IO, but little to no effect in CGE • Numerically, investing in solar panels or weatherization creates jobs in both models.
Many studies have demonstrated the feasibility of fully renewable power systems. Yet the future costs of key technologies are highly uncertain, and little is known about the robustness of a renewable power system to these uncertainties. To analyze it, we build 315 cost scenarios by varying the costs of key technologies and we model the optimal renewable power system for France, simultaneously optimizing investment and dispatch. We add to the literature by studying a consecutive 18-years weather period; by testing all combinations of technology costs rather than changing them one-at-a-time; and by calculating the regret from optimizing the energy mix on the basis of cost assumptions that do not materialize.Our results indicate that the cost of a 100% system is not that sensitive to uncertainty. Admittedly, the optimal energy mix is highly sensitive to cost assumptions: across our scenarios, the installed capacity in PV, onshore wind and power-togas varies by a factor of 5, batteries and offshore wind even more. However, in every scenario the total production and storage cost is similar to, or lower than the current cost. This indicates that renewable technologies will become by and large substitutable. Moreover, even if the energy mix is optimized based on cost assumptions which turn out to be wrong, the extra cost is low: 4% in average and less than 9% in 95% of the scenarios.
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