The analysis of energy scenarios for future energy systems requires appropriate data. However, while more or less detailed data on energy production is often available, appropriate data on energy consumption is often scarce. In our JERICHO-E-usage dataset, we provide comprehensive data on useful energy consumption patterns for heat, cold, mechanical energy, information and communication, and light in high spatial and temporal resolution. Furthermore, we distinguish between residential, industrial, commerce, and mobility consumers. For our dataset, we aggregate bottom-up data and disaggregate top-down data both to the NUTS2 level. The NUTS2 level serves as an interface to validate our combined method approach and the calculations. We combine a multitude of data sources such as weather time series, standard load profiles, census data, movement data, and employment figures to increase the scope, validity, and reproducibility for energy system modeling. The focus of our JERICHO-E-usage dataset on useful energy consumption might be of particular interest to researchers who analyze energy scenarios where renewable electricity is largely substituted for fossil fuel (sector coupling).

The transformation of the energy system is a highly complex process involving many dimensions. Energy system models help to understand the process and to define either target systems or policy measures. Insights derived from the social sciences are not sufficiently represented in energy system models, but address crucial aspects of the transformation process. It is, therefore, necessary to develop approaches to integrate results from social science studies into energy system models. Hence, as a result of an interdisciplinary discourse among energy system modellers, social scientists, psychologists, economists and political scientists, this article explains which aspects should be considered in the models, how the respective results can be collected and which aspects of integration into energy system models are conceivable to provide an overview for other modellers. As a result of the discourse, five facets are examined: Investment behaviour (market acceptance), user behaviour, local acceptance, technology innovation and socio-political acceptance. Finally, an approach is presented that introduces a compound of energy system models (with a focus on the macro and micro-perspective) as well as submodels on technology genesis and socio-political acceptance, which serves to gain a more fundamental knowledge of the transformation process.

Solar hybrid mini-grid systems possess the potential to substantially support electrification in sub-Saharan Africa. While their technical reliability has been proven, their financial viability is achieved only by heavy subsidization as of now. Due to the growing importance of results-based financing, we ask whether newly developed business models leveraging on the value added of electricity supply in rural areas (such as the KeyMaker Model) bare the potential to substantially reduce amount of grants required to finance the initial capital investment and thus contribute to a sustainable form of development. The principle of the KeyMaker Model is based on utilizing the locally supplied mini-grid electricity to establish a local agro-processing project, the revenues of which are an additional income stream for the mini-grid operator, while the project creates an end-market for the local farmers to sell their produce. We have developed two scenarios (without and with KeyMaker Model) for four rural villages in Nigeria as a case study to scientifically assess the potential of KeyMaker Models. We simulated and optimized the mini-grid systems using the software tool HOMER. We then assessed their financial viability. Our analysis demonstrates grant finance requirements ranging from 82% to 99% of the total investment for the base-case mini-grid projects without consideration of the KeyMaker Model. We find that a well-selected KeyMaker Model such as cocoa bean processing reduced the grant requirement by 68 percentage points, while processes based on maize, palm oil and cassava processing achieved reductions of 36, 26 and 8 percentage points, respectively. Hence, we conclude that the value added by the introduction of new local business models bares the potential to reduce grant requirements for the socially and economically necessary electrification across the Global South.