• Energy Research

Higher shares of fluctuating generation from renewable energy sources in the power system lead to an increase in grid balancing demand. One approach for avoiding curtailment of renewable energies is to use excess electricity feed-in for heating applications. To assess in which regions power-to-heat technologies can contribute to renewable energy integration, detailed data on the spatial distribution of the heat demand are needed. We determine the overall heat load in the residential building sector and the share covered by electric heating technologies for each administrative district in Germany, with a temporal resolution of 15 minutes. Using a special evaluation of German census data, we defined 729 building categories and assigned individual heat demand values. Furthermore, heating types and different classes of installed heating capacity were defined. Our analysis showed that the share of small-scale single-storey heating and large-scale central heating is higher in cities, whereas there is more medium-scale central heating in rural areas. This results from the different shares of single and multi-family houses in the respective regions. To determine the electrically-covered heat demand, we took into account heat pumps and resistive heating technologies. All results, as well as the developed code, are published under open source licenses and can thus also be used by other researchers for the assessment of power-to-heat for renewable energy integration. 18 pages, 23 figures

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. An strategy with strong use of energetic simulations is developed here and the core elements shall be presented. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation-tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of an optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is to give a brought introduction to the intended planning processes and decision-making framework and to find and identify research gaps that will have to be addressed in the future.

Abstract In silicon heterojunction solar cells with thin intrinsic layers (SHJ) based on n-type silicon wafers, it is common to use a p-doped front emitter and back surface field (n-layer). In this study, SHJ cells were developed and investigated in front surface field (FSF) configuration with a n-doped layer at the front side. The electrical and optical properties of the FSF play a crucial role in cell operation. Ideally, the FSF demonstrates low light absorption, efficient extraction of electrons to contacts, as well as chemical and electrical passivation. The goal of this work is to study the physical properties of n-doped microcrystalline silicon thin films and apply them as the FSF layer in SHJ solar cells. We demonstrate promising results in such SHJ solar cells with short-current density of 2.9 mA/cm² higher compared to reference cells with amorphous FSF.

Abstract Climate change mitigation requires a fundamental transformation in the power supply system particularly in cities. Urban energy models integrated in Geographic Information Systems (GIS) have been playing a central role in shaping this transformation. In this regards, openness and transparency have been recently gaining a prominent importance and attracting increasing political interest. As renewables share has grown to high levels in cities, flexibilisation options including storage become vital to ensure a reliable, affordable and sustainable Urban Electricity System (UES). Energy modelling provides policymakers with qualitative and quantitative insights required for the planning and operation of future UES. Hence, the representation of UES requires an appropriate characterisation of different urban energy requirements that should be adequately incorporated in a spatial-temporal framework including both static and dynamic datasets. This paper introduces an open GIS-based platform for the optimisation of flexibility options costs and operation in urban areas. The platform reproduces the urban energy infrastructure (spatial dimension), simulates demand and supply (spatial and temporal dimension) and performs a linear programming optimisation to explore scenarios for the economic deployment of micro-generation and decentralised storage. The total UES costs and required storage capacities for different urban energy scenarios are investigated here. A key finding of this contribution is that investing in local electricity storage and on-site renewable power generation can significantly reduce the total system costs and increase urban self-sufficiency. The developed platform is showcased for the city of Oldenburg.

Abstract As the world is already highly urbanised, energy systems in cities are already responsible for significant amount of the global Greenhouse Gas (GHG) emissions. Therefore, climate change mitigation demands a fundamental transformation in the Urban Energy Systems (UES), energy markets and energy policies. In this context, the large shift to micro-generation from renewable energy sources and their integration in the current energy system are a technical challenge for future energy systems design and operation. This will be further exacerbated if flexibilisation technologies such as storage are not efficiently integrated. For this purpose, an accurate modelling and representation of UES requires the characterisation of different urban energy requirements. These requirements, along with the urban fabric of cities, should be adequately incorporated in a spatial-temporal framework including both static and dynamic datasets. In this context, urban energy models provide policymakers with qualitative and quantitative insights for the planning of future UES. Within this framework, urban energy models integrated in Geographic Information Systems (GIS) will play an important role due to their multi-layer approach. This study introduces an open source GIS-based platform called FlexiGIS for the optimisation of energy systems in cities. FlexiGIS is used in this contribution to optimally allocate distributed battery storage in urban areas. The FlexiGIS platform provides the urban energy infrastructure (spatial dimension), simulates electricity consumption and generation (spatial and temporal dimension) and performs a linear optimisation for the economic deployment of micro-generation and decentralised storage under different energy scenarios. The first case study considers the city as a single system or ‘energy cell’, while the second one assumes that the city is divided into connected subsystems or districts. The total UES costs and required storage capacities for the investigated scenarios are obtained using optimisation. A key finding is that, for the investigated scenarios, investing in local electricity storage and renewable power generation can significantly reduce the total system costs and increase urban self-sufficiency. This study also highlights that the off-grid scenario (isolated city) is not an optimal choice.

AbstractSolar cells used in building integration of photovoltaic cells (BIPV) are commonly made from crystalline wafer cells. This contribution investigates the challenges and benefits of using bifacial solar cells in vertical installations. We show that those cells get up to 13% more irradiance compared to optimum tilted south facing monofacial modules in Germany. The role of the n‐layer in thin amorphous bifacial single‐junction cells intended to be used as bifacial cells in BIPV applications is investigated. In contrast to the superstrate cell design, a transparent n‐layer and back contact play a key role to achieve high bifaciality. We therefore increased the transparency of the n‐layer by adding CO2, increasing the PH3 flow in the deposition gas and tested different thicknesses. With those measures, we reached a bifaciality of 98% for short‐circuit current density and 99% for open‐circuit voltage.