• Energy Research

After years of focusing exclusively on the technological side of electric mobility (e-mobility), services are getting more and more in the focus of scientists. Many recent works concentrate on the identification and analysis of the potential of new business models in this field. Although the relevancy of services for the success of e-mobility is becoming more obvious among industry and science, there is still a lack in scientific contributions when asking for a comprehensive overview of existing e-mobility services. With this paper, we try to bridge this gap by providing a framework that enables the description and classification of services around the usage of an electric vehicle (EV). The framework captures six dimensions which allows to characterize and compare different services. This enables the identification of commonalities and differences between the services and provides an interdisciplinary playground for developing new services and further research in this field.

Abstract The residential building sector has an important role to play in the energy transition due to a high share of final energy consumed and a considerable amount of CO 2 emitted. Ambitious targets in Germany relate amongst other things to a primary energy reduction of 80% and an increased usage of renewable energy sources in heat supply to 60% in 2050. Existing research in this area both lacks detail in modelling decentralised heat supply in residential buildings and fails to adequately quantitatively analyse this target achievement for Germany. In order to overcome these limitations, a novel model-based approach is presented in which the developed TIMES-HEAT-POWER optimisation model is coupled with a decentralised energy system optimisation model to determine optimal and realistic technology configurations, and a building stock simulation model to adequately and consistently project the evolution of the building stock in Germany. This novel configuration of models is then used to investigate the evolution of the electricity system and the residential heat system in Germany in the context of key energy-political targets up to 2050. The national goals related to primary energy reduction and the share of renewable energy sources in final energy demand in the residential heat sector are missed in the Reference Scenario. On the other hand, target achievement requires deep insulation measures and a supply-side technology shift away from gas and oil boilers towards heat pumps and solar thermal. The scenario analysis reveals a significant sensitivity of the deployment of micro-Combined heat and power technologies (μCHP) and heat pumps to, amongst other things, the evolution of fuel prices, renewable electricity technologies, heat and electricity demand as well as technological progress. Further model extension can be identified inter alia in broadening the system boundaries to integrate further sectors (tertiary, industrial) or incorporating different user categories and decision rationales.

To estimate the (future) impact of hydrogen generation on the electricity market, it is necessary to adequately consider electrolyzers’ flexibility in models to evaluate the integration. Therefore, a cost-minimizing linear optimization problem for determining the dispatch of electrolyzers is integrated into an existing agent-based electricity market simulation model. In a case study with two scenarios considering most western European countries, effects on the wholesale electricity spot markets are investigated. Scenario one considers locally demanded and produced hydrogen. Scenario two assumes one single internal hydrogen market to cover all modeled markets.The results indicate that average wholesale electricity prices and renewable curtailments differ only slightly between scenarios. However, the cost of dispatching electrolyzers is substantially lower in one single internal hydrogen market. Additionally, the utilization of electrolyzers between markets is more evenly distributed. Hydrogen is produced mainly in markets with substantial wind potentials, such as Denmark and Great Britain.

Purpose The connection between urbanization and energy consumption in the context of cross-country and cross-sector analyses is poorly understood, especially in the Association of South East Asian (ASEAN). This paper aims to present the first extensive multi-level analysis of the relationship between urbanization and energy consumption in ASEAN countries from 1995 to 2013. Design/methodology/approach The multi-level (across country and sector) index decomposition method is used to analyze urbanization, energy mix, energy intensity and activity effects on energy demand. Urbanization is measured by two representative factors, name the urban population and the number of non-agriculture workers. Findings Despite the decreasing rate of urbanization, its effect on energy consumption has played the most important role since 2000. Since then, the effect has continued to increase at the national and sectoral levels across the whole region. The strongest urbanization impacts are encountered in the residential sector, followed by transportation and industrial sectors with much weaker effects in the commercial sector. The way in which urbanization impacts energy consumption depends strongly on the income level of the country studied. Practical implications The results provide quantitative relationships between urbanization and energy demand. For example, if the urban population and the non-agriculture workers decreased by 0.1 per cent per year, this would reduce energy demand by 1.4 per cent and 2.6 per cent per year respectively. Originality/value This contribution provides detailed quantitative insights into the relationships between urbanization and energy demand at sectoral, national and international levels, which are invaluable for policymakers in the region.

The recent rapid expansion of renewable energy capacities in Germany has been dominated by decentralised wind, photovoltaic (PV) and bioenergy plants. The spatially disperse and partly unpredictable nature of these resources necessitates an increasing exploitation of integration measures such as curtailment, supply and demand side flexibilities, network strengthening and storage capacities. Indeed, one solution to the large-scale integration of renewable energies could be decentralised autonomous municipal energy systems. The achievement of grid parity for some renewable energy technologies has strengthened the desire of some communities to become independent from central markets. Whilst many communities in Germany already strive for socalled energy autonomy, the vast majority do so only on an annual basis. Several studies have already analysed the technical and economic implications of the mainly decentralised future energy system, but most are restricted in their insights by limited temporal and spatial resolution. The large number (11,131) of German municipalities means that a national analysis at this resolution is not feasible. Hence, this study employs a cluster analysis to develop a municipality typology in order to analyse the techno-economic suitability of these municipalities for autonomous energy systems. A total of 34 socio-technical indicators are employed at the municipal level, with a particular focus on the sectors of Private Households and Transport, and the potentials for decentralised renewable energies. The first step is to scale the indicator values and reduce their number by using a factor analysis. Several alternative methods are weighed against each other, and the most suitable methods for the factor analysis are chosen. Secondly, selected quantitative cluster validation methods are employed alongside qualitative criteria to determine the optimal number of clusters. This results in a total of ten clusters, which show a large variation as well as some overlap with respect to specific indicators. For example, one cluster contains all major German cities and has a low potential for renewable energies. Another cluster, on the other hand, contains the municipalities with a higher potential for renewable energies due to their high hydrothermal potential for geothermal power. An analysis of the municipalities from three German renewable energy projects “Energy Municipalities”, ”Bioenergy Villages” and “100% Renewable Energy Regions” shows that in eight of the ten clusters municipalities are aiming for energy autonomy (in varying degrees). It is challenging to differentiate between the clusters regarding readiness for energy autonomy projects, however, especially if the degree of social acceptance and engagement for such projects is to be considered. To answer the more techno-economical part of this question, future work will employ the developed clusters in the context of an energy system optimisation. Insights gained at the municipal level will then be qualitatively transferred to the national context to assess the implications for the whole energy system.

Electric vehicles are one of the concepts towards green and sustainable transportation systems. However, several uncertainties with respect to electricity demand and availability of electric vehicles as well as electricity supply by renewable energy sources influence an optimal scheduling through smart charging strategies. This paper investigates the possibilities to integrate additionally loads of uncertain renewable energy sources by smart charging strategies of three different electric vehicle fleets namely, commercial customers, commuters, and opportunity parkers. Therefore, data from an empiric field test with a public charging infrastructure in a parking garage with a photovoltaic system is taken. Various strategies are analyzed, considering the changing individual electricity demand, restrictions and parking times of electric vehicle fleets by combining a Monte Carlo simulation approach with different methodologies like a heuristic algorithm, an optimization model and stochastic programming. The numerical results indicate that the domestic photovoltaic generation of the car park can be fully used by the electric vehicle fleets for charging and the utilization of photovoltaic can be doubled when comparing uncontrolled and optimized charging strategies. The commuter fleet has the highest CO2 emission reduction potential of all three electric vehicle fleets. Moreover, load management decreases costs, even when uncertainties are considered

Abstract Adequately accounting for interactions between Low Carbon Technologies (LCTs) at the building level and the overarching energy system means capturing the granularity associated with decentralised heat and power supply in residential buildings. This paper combines dwelling/household archetypes (DHAs) combined with a mixed integer linear program to generate optimal (minimum cost) technology configurations and operation schedules for individual dwellings. These DHAs are scaled up to three socioeconomically differentiated neighbourhood clusters at the Output Area level in the UK. A synthetic distribution network generation and simulation assesses the required network upgrade costs for these clusters with different LCT penetration scenarios. Whilst the application here is to the United Kingdom (UK) setting, the method is largely based on freely available data and is therefore highly transferable to other contexts. The results show significant differences between the upgrade costs of the three analysed network types, and especially the semi-rural cluster has much higher costs. The employment of heat pumps together with photovoltaics (PV) has strong synergy effects, which can considerably reduce the network upgrade and carbon abatement costs if deployed in parallel. The determined CO 2 -abatement costs also suggest that decarbonisation measures with these two technologies should focus on semi-urban neighbourhoods due to the lower cost in comparison to the semi-rural case. This shows that such a socioeconomically differentiated approach to distribution network modelling can provide useful energy policy insights.

Abstract Decentralised community energy resources are often abundant in smaller, more rural communities. Such communities often lack the capacity to develop extensive energy concepts and thus to exploit these resources in a consistent way. This paper presents an integrated participatory approach to developing feasible energy concepts for small communities. The novelty lies in the combination of methods, the consideration of uncertainties, and the application to an exemplary municipality in Germany. Stakeholder workshops are combined with energy modelling and multi-criteria decision analysis (MCDA), and a high transferability is ensured with mainly public data. The workshop discussion revealed three values: economic sustainability, environmental sustainability, and local energy autonomy. A total of eight alternatives for the 2030 energy system are identified to achieve these values. We find that an alternative that seeks only maximization of economic sustainability should be rejected based on elicited preferences. Instead, several alternatives seeking a maximization of environmental sustainability with constraints on economic sustainability (i.e. total cost) and local energy autonomy consistently achieve the highest overall performance scores. A maximization of economic sustainability or local energy autonomy alone results in the lowest overall performance scores and should therefore not be pursued by the community. The intermediate alternatives demonstrate that an equivalent performance gain with respect to autonomy comes at higher costs than the same gain with respect to environmental sustainability. Similarities between the best performing alternatives in terms of technologies that can be installed by 2030 show that our methodology can generate concrete and robust recommendations on building-level measures for energy system design.