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With the European Green Deal, the European Union (EU27) aims to achieve an ambitious decarbonization of its electricity supply, while actively involving its citizens. Scenarios from energy and electricity sector models seek to inform this transition, although it is unclear to what extent these scenarios are aligned with the views of the citizens. In this study, four multi-organization, multi-model ensembles of existing electricity supply scenarios have been compiled for France, Germany, Poland, and the whole EU27 in 2035, leading to 612 scenarios in total. These scenarios were then compared with 601 preferred scenarios elicited from French, German, and Polish citizens in a survey with an interactive scenario tool. Results show that model-based and citizens’ preferred scenarios converged only on having moderate shares of onshore and offshore wind power and low shares of biomass and waste incineration. In contrast to the majority of model-based scenarios, most Polish and German citizens preferred a deeper decarbonization for their national electricity supply, while French citizens preferred a deeper denuclearization. Additionally, most citizens of all three countries used significant shares of solar photovoltaics and low shares of fossil fuels with carbon capture and storage, hence diverging from model-based scenarios. Similar patterns were found for the EU27 scenarios: many model-based scenarios included large shares of nuclear power, natural gas, and coal, while surveyed citizens preferred scenarios dominated by diverse renewable sources. European modelers should now quantify these missing scenarios so that the EU27 energy transition can be informed by modeling that is in line with citizens’ perspectives.

Hydrogen is considered one of the key pillars of an effective decarbonization strategy of the energy sector; however, the potential of hydrogen as an electricity storage medium is debated. This paper investigates the role of hydrogen as an electricity storage medium in an electricity system with large hydropower resources, focusing on the Swiss electricity sector. Several techno-economic and climate scenarios are considered. Findings suggest that hydrogen storage plays no major role under most conditions, because of the large hydropower resources. More specifically, no hydrogen storage is installed in Switzerland if today's values of net-transfer capacities and low load-shedding costs are assumed. This applies even to hydrogen-favorable climate scenarios (dry years with low precipitation and dam inflows) and economic assumptions (high learning rates for hydrogen technologies). In contrast, hydrogen storage is installed when net-transfer capacities between countries are reduced below 30% of current values and load-shedding costs are above 1,000 EUR/MWh. When installed, hydrogen is deployed in a few large-scale installations near the national borders. [Display omitted] • High-fidelity models of Swiss electricity sector and hydrogen storage technologies. • No significant hydrogen storage is required in Switzerland under most scenarios. • Large hydropower resources reduce the need for hydrogen storage significantly. • Hydrogen storage becomes relevant with reduced electricity net transfer capacities. • Hydrogen storage is used for high self-sufficiency ratios to avoid load-shedding. [ABSTRACT FROM AUTHOR]

Long-range energy scenarios are commonly used to inform national energy policy decisions. Although the scenario approach aims to expand the spectrum of futures considered, in the past energy scenarios have not been diverse enough to include less expected real-world developments. We use a bottom-up energy system model EXPANSE with Modeling to Generate Alternatives (MGA) to assess the diversity of the existing ensemble of multi-organization, multi-model Swiss electricity supply scenarios. We show that both for 2035 and 2050 existing scenarios cover well the various possibilities in deployment of individual electricity generation technologies in terms of installed capacity or produced electricity. When analyzing scenarios as a whole, we find that in 2035 there is a lack of scenarios with high electricity demand and greater deployment of renewable technologies occurring simultaneously, as well as scenarios with a negligible or negative share of net electricity import. In 2050, there is also a lack of scenarios that depict high electricity demand and conservative deployment of new renewable technologies, especially solar PV. We propose six additional scenarios to be included to increase the diversity of the ensemble of Swiss electricity supply scenarios and achieve better understanding of the future possibilities and uncertainties. [ABSTRACT FROM AUTHOR]

This paper analyzes the optimal planning and operation of aggregated distributed energy resources (DER) with participation in the electricity market. Aggregators manage their portfolio of resources in order to obtain the maximum benefit from the grid, while participating in the day-ahead wholesale electricity market. The goal of this paper is to propose a model for aggregated DER systems planning, considering its participation in the electricity market and its impact on the market price. The results are the optimal planning and management of DER systems, and the appropriate energy transactions for the aggregator in the wholesale day-ahead market according to the size of its aggregated resources. A price-maker approach based on representing the market competitors with residual demand curves is followed, and the impact on the price is assessed to help in the decision of using price-maker or price-taker approaches depending on the size of the aggregated resources. A deterministic programming problem with two case studies (the average scenario and the most likely scenario from the stochastic ones), and a stochastic one with a case study to account for the market uncertainty are described. For both models, market scenarios have been built from historical data of the Spanish system. The results suggest that when the aggregated resources have enough size to follow a price-maker approach and the uncertainty of the markets is considered in the planning process, the DER systems can achieve up to 50% extra economic benefits, depending on the market share, compared with a non-aggregated business-as-usual approach (not implementing DER systems). [ABSTRACT FROM AUTHOR]

We present a meta-analysis of long-term energy-system scenario studies. The meta-analysis comprises a qualitative taxonomy of modeling approaches and a quantitative decomposition of scenario results across heterogenous studies. The analysis is exemplified by technology-detailed scenario studies of the Swiss electricity system. In the decomposition approach, we assess the variability across scenario results by a principal component analysis, which provides a low-dimensional approximation of multidimensional data. Additionally, by means of a distance measure, the extremality of a scenario result is evaluated, and a minimal set of representative scenarios is determined with respect to a considered scenario result. The proposed methods contribute to the analysis of commonality of modeling approaches and of multidimensional results across heterogenous scenario studies. [ABSTRACT FROM AUTHOR]

[Display omitted] • Retrospective cost-optimal scenarios are generated in 31 European countries in 1990–2019. • 24 accuracy indicators from literature are used for evaluating 34 model outputs. • The most informative smaller set of five accuracy indicators is identified, using clustering-based dissimilarity analysis. • Modeled scenarios in 31 countries are assessed by applying this small set of accuracy indicators. Retrospective evaluation of energy system models and scenarios is essential for ensuring their robustness for prospective policy support. However, quantitative evaluations currently lack systematic methods to be more holistic and informative. This paper reviews existing accuracy indicators used for retrospective evaluations of energy models and scenarios with the aim to find a small suite of complementary indicators. We quantify and compare 24 indicators to assess the retrospective performance of D-EXPANSE electricity sector modeling framework, used to model 31 European countries in parallel from 1990–2019. We find that symmetric mean percentage error, symmetric mean absolute percentage error, symmetric median absolute percentage error, root-mean-squared logarithmic error, and growth error together form the most informative suite of indicators. This study is the first step towards developing a model accuracy testbench to assess energy models and scenarios in multiple dimensions retrospectively. [ABSTRACT FROM AUTHOR]