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Highlights • Analysis of electricity demand in neighbourhoods, districts and municipalities. • Data-driven classification of electricity demand profiles of nearly 15000 urban areas. • Three statistically different urban area types found: residential, business and mixed. • Urban area types differ in terms of demand profiles and energy user composition. • Often-used residential-type demand represents only a minority of analysed areas. Abstract Cities and communities worldwide are seeking to become more sustainable by transitioning to renewable energy resources, and by introducing electric transportation and heating. The impact and suitability of such technologies for a given area heavily depend on local conditions, such as characteristics of local demand. In particular, the shape of a local demand profile is an important determinant for how much renewable energy can be used directly, and how charging of electric vehicles and use of electric heating affect a local grid. Unfortunately, a systematic understanding of local demand characteristics on different urban scales (neighbourhoods, districts and municipalities) is currently lacking in literature. Most energy transition studies simplify local demand to household demand only. This paper addresses this knowledge gap by providing a novel data-driven classification and analysis of demand profiles and energy user compositions in nearly 15000 neighbourhoods, districts and municipalities, based on data from the Netherlands. The results show that on all urban scales, three types of areas can be distinguished. In this paper, these area types are termed "residential", "business" and "mixed", based on the most prevalent energy users in each. Statistic analysis of the results shows that area types are pairwise significantly different, both in terms of their profiles and in terms of their energy user composition. Moreover, residential-type demand profiles are found only in a small number of areas. These results emphasise the importance of using local detailed spatio-temporal demand profiles to support the transition of urban areas to sustainable energy generation, transportation and heating. To facilitate the implementation of the obtained insights in other models, a spreadsheet modelling tool is provided in an addendum to this paper. [ABSTRACT FROM AUTHOR]

We introduce a bottom-up modeling framework that allows both the decentral and central planning of an integrated energy system with high shares of renewable generation. We take into account the distribution network structure as well as the changing local consumption due to high electrification rates of building heat supply and the transportation sector. This approach allows the analysis of pathways in between a cost-optimal system design and an equitable spatial distribution of renewable generation and battery storage capacities within the system. In addition, we investigate the optimal combination of short- and medium-term battery storage technologies, namely lithium-ion and redox flow batteries. Our results for the case of Baden-Wuerttemberg, a state in southern Germany, show that a central planning of renewable generation and storage capacity requirements results in lower levelized costs of electricity than a decentral design, as expected. However, pathways in between the two planning paradigms can lead to a more equitable inclusion of communities in the energy transition at reasonable cost increases, which might increase acceptance. The results of this study are of significance for policy-makers and local stakeholders, as they must address the conflicts that arise on a local level when expansion targets are planned centrally. • Framework for modeling local electricity consumption, considering structural changes • Optimal combination of short- and medium-term storage technologies (LiB and RFB) • Costs, storage and renewable capacity requirements for decentral vs. central planning [ABSTRACT FROM AUTHOR]

Abstract: The paper investigates how renewable technologies could promote the transition towards a sustainable energy production in developing nations. Based on two different developing nations in terms of economic, technological and institutional structure: South Africa and Senegal, we implemented scenarios in a bottom-up PowerPlan model in order to analyze the transition toward a sustainable electric production. Two scenarios have been considered: a business-as-usual (BAU) and a hybrid renewable energy (HRE) scenario. In the first scenario (BAU) we assume that the electricity demand is entirely satisfied by an increase of the investment in the current supply structure based on fossil-fuel energy source. Whereas in the renewable energy scenario, we assume 20% and 30% of the electricity supply being generated from renewable resources by 2020 and 2030 respectively. Focusing on wind and solar photovoltaic technologies, our results show the cost-competitiveness of renewable energy deployment in South Africa. In the case of Senegal, our results show that fossil-fuel resource remains the most competitive to generate electricity in the nation during the next coming years as long as environmental advantages of renewable resource are not considered. Our research indicates that in the case of a centralized electricity supply option, both a scale effect and a learning improvement could eventually strengthen the competitiveness of renewable technology deployment in developing nations. [Copyright &y& Elsevier]

• Electricity, hydrogen and methane system will be more integrated in the future. • The developed integrated model considers their interactions and interdependencies. • As proof-of-concept, the model is applied to the Dutch Infrastructure Outlook 2050. • Interweaving electricity, hydrogen and methane system will provide much needed flexibility. The future energy system is widely expected to show increasing levels of integration across differing energy carriers. Electricity, hydrogen, methane and heat systems may become increasingly interdependent due to coupling through conversion and hybrid energy technologies. Market parties, network operators, policy makers and regulators require tools to capture implications of possible techno-economic and institutional developments in one system for the operation of others. In this article, we provide an integrated electricity, hydrogen and methane systems modelling framework focusing on interdependencies between them. The proposed integrated electricity and (renewable) gas system model is a market equilibrium model with hourly price and volume interactions, considering ramp rates of conventional units, variability of intermittent renewables, conversion, transport as well as storage of electricity, hydrogen and methane. The integrated model is formulated as a linear program under the assumption of perfect competition. As proof-of-concept, the model has been applied to a test case consisting of 34 electricity nodes, 19 hydrogen nodes and 22 methane nodes, reflecting the regional governance scenario in the Dutch Infrastructure Outlook 2050 study. The case study also includes different sensitivity analyses with regard to variable renewable capacity, energy demand and biomass prices to illustrate model response to perturbations of its main drivers. This article demonstrates that the interweaving of electricity, hydrogen and methane systems can provide the required flexibility in the future energy system. [ABSTRACT FROM AUTHOR]

• Energy yield simulation of vertical bifacial PV array in 12 European locations. • Comparison with a conventional PV array (monofacial, equator-oriented, tilted). • Evaluation of market revenues based on historic day-ahead market prices. • Evaluation of LCOE and net present value. • Evaluation of system cost reduction from a macroeconomic perspective for Germany. Thanks to the two diurnal generation peaks, vertical bifacial photovoltaic power plants (VBPV) with a north-south axis represent an option to meet the challenges of a mismatch between electricity demand and the generation profile of conventional photovoltaic systems (C-PV). Despite this promising characteristic, it is hardly possible to assess the technical and economic properties of VBPV on the basis of existing studies. The present work is a contribution to close this gap. Among other things, the conducted analyses included electricity generation, market revenues, levelized costs of electricity (LCOE) and the cost-reducing effect of VBPV in a national electricity system. C-PV was used as a benchmark in all analyses. Electricity generation was simulated at twelve European sites in four countries. It has been found that above a latitude of 50° VBPV generates more electricity than C-PV. Due to the higher investments, VBPV had higher LCOE at all locations investigated. The results also showed that VBPV can generate higher revenues in electricity markets with a high share of C-PV capacity, but that these additional revenues are not yet sufficient to compensate for the higher investments. With an optimising electricity market model, it was also found that VBPV can contribute to reducing system costs in an electricity system with high shares of C-PV capacity. Against the background of the increasing importance of PV for the electricity supply of most European countries, these findings are of particular importance. In summary, it can be said that VBPV has significant potential at both the business and macro-economic level and that decision makers should promote the market entry of this technology. [ABSTRACT FROM AUTHOR]

• Integrated stakeholder preferences towards equality into electricity planning. • Framework for opportunity-focused approach for electricity planning. • Novel combination of economics, utility maximization, and least-cost frameworks. • Co-optimized generation and transmission investments under equality preferences. Access to electricity can lead to enhanced education, business, and healthcare opportunities. Governments in emerging economies are often faced with the challenge of increasing access to electricity and reducing system inequality, while operating under severe budget constraints. This paper develops a methodology for finding the optimal expansion of a power system under the objective of maximizing social benefit, as it relates to distributional equality for electricity access, subject to a budget constraint. This contrasts with traditional models, which minimize the cost of satisfying projected electricity demand. We formulate a generation expansion planning problem as a utility-maximization mixed-integer linear program and apply it to a case study analysis of a low-income country with limited electricity infrastructure. We focus our analysis on understanding how the optimal allocation of generation between centralized and distributed resources is impacted by stakeholder preferences toward equality and different budget levels. We find that a high preference for equality leads to lower overall electricity consumption levels, but improved electrification rates due to greater investment (300–750 km increase) in transmission infrastructure. If stakeholders move from a low to a high equality preference then they could see a 72–87% increase in energy access equality rating depending on the budget. Conversely, indifference to equality leads to higher overall consumption levels in urban areas but reduced electrification rates. This methodology can help decision makers evaluate the social trade-offs between improving energy access, reducing energy inequality and poverty, and increasing total electricity consumption when operating under budget constraints in their countries. [ABSTRACT FROM AUTHOR]

• Probabilistic simulation of security of electricity supply in central Europe. • Quasi-absolute levels of security of supply are unlikely to be maintained in future scenarios. • Sensitivity of security of supply towards meteorological influences is increasing. • Dependency on contributions from neighboring countries is growing. • Relevance to coordinate capacity planning on an international level is demonstrated. Against the backdrop of expansions of intermittent renewable energy capacity, planned nuclear phase-outs, and current debates on the additional mothballing of coal-fired power plants in central Europe, there is a substantial increase in uncertainty regarding security of electricity supply. In this context, we present a probabilistic and scenario-based analysis of impacts on security of supply for Germany as a case-study in the medium-term perspective (years 2020, 2022, and 2023). For our analysis, we introduce the energy security assessment module of the JERICHO energy system model from RWTH Aachen University. Our model allows for an hourly probabilistic simulation of security of supply and accounts for stochastic characteristics of (non-)availability of conventional generators, renewable feed-in, electricity demand, and import potentials from central-European countries. To increase the robustness of results, we use a comprehensive dataset of temperature, wind speeds, solar radiation and water levels from weather years 1986 to 2015 as input for our simulations. Our results indicate that Germany is unlikely to maintain its quasi-absolute levels of security of supply in the near future with a mean Loss of Load Expectation (LoLE) of up to 2.6 h in scenario year 2023. However, this does not necessarily imply that future levels of security of supply are insufficient. There is need for further assessments on identifying threshold levels for security of supply, which are economically efficient and acceptable for society. Our results also indicate that the sensitivity of security of supply for meteorological changes increases with reductions of conventional power plants. Finally, we demonstrate that the dependency of security of supply on imports from neighboring countries increases substantially calling for increased international coordination of national energy policies. [ABSTRACT FROM AUTHOR]