• 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

In order to analyse the mid- and long-term impacts of energy related policies, different modelling approaches can be derived. However, the results of even the best energy system model will highly depend on the underlying input data. First, in this contribution the importance and availability issues of grid data in the context of energy system modelling are highlighted. Second, this paper focuses on power grid modelling based on open and publicly available data from OpenStreetMap using open source software tools. Two recent approaches developed to build electrical transmission network models using openly available data sources are presented and discussed. The proposed methods provide transparent assumptions, simplifications and documentation of grid modelling. This results in the ability of scientists and other stakeholders to validate, discuss or reproduce the results of energy system models. Thus the new open approaches offer a unique opportunity to increase transparency, comparability and reproducibility of results in energy system modelling.

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.

Power system expansion models are a widely used tool for planning powersystems, especially considering the integration of large shares of renewableresources. The backbone of these models is an optimization problem, whichdepends on a number of economic and technical parameters. Although theseparameters contain significant uncertainties, the sensitivity of power systemmodels to these uncertainties is barely investigated. In this work, we introduce a novel method to quantify the sensitivity ofpower system models to different model parameters based on measuring theadditional cost arising from misallocating generation capacities. The value ofthis method is proven by three prominent test cases: the definition of capitalcost, different weather periods and different spatial and temporal resolutions.We find that the model is most sensitive to the temporal resolution. Fur-thermore, we explain why the spatial resolution is of minor importance andwhy the underlying weather data should be chosen carefully.

Este trabajo presenta un estudio de los efectos que la integración de instalaciones de electrólisis para procesos Power-to-X tiene en la red eléctrica. La novedosa configuración de simulación combina un modelo de optimización de red de alta resolución y un modelo de programación detallado para la electrólisis de agua alcalina. La utilización y congestión de las líneas eléctricas en el norte de Alemania se investiga mediante el establecimiento de diferentes capacidades instaladas y estrategias de producción de la instalación de electrólisis. Para capacidades de electrólisis de hasta 300 MW (~50 ktH2/a), se observan impactos locales en la red, mientras que las capacidades más altas causan impactos suprarregionales. Por lo tanto, los impactos se definen como desviaciones de la utilización media de la línea superiores al 5%. Además, se determina que la congestión mínima de la línea coincide con la estrategia de producción diaria restringida de la instalación de electrólisis. Nuestro resultado muestra un buen compromiso para la operación integrada de la instalación de la red con un coste de producción mínimo y un impacto reducido en la red. Ce travail présente une étude des effets de l'intégration des installations d'électrolyse pour les processus Power-to-X sur le réseau électrique. La nouvelle configuration de simulation combine un modèle d'optimisation de grille à haute résolution et un modèle d'ordonnancement détaillé pour l'électrolyse de l'eau alcaline. L'utilisation et la congestion des lignes électriques dans le nord de l'Allemagne sont étudiées en définissant différentes capacités installées et stratégies de production de l'installation d'électrolyse. Pour les capacités d'électrolyse jusqu'à 300 MW (~50 ktH2/a), des impacts locaux sur le réseau sont observés, tandis que des capacités plus élevées provoquent des impacts suprarégionaux. Ainsi, les impacts sont définis comme des écarts par rapport à l'utilisation moyenne de la ligne supérieurs à 5%. En outre, la congestion minimale de la ligne est déterminée pour coïncider avec la stratégie de production quotidienne contrainte de l'installation d'électrolyse. Notre résultat montre un bon compromis pour le fonctionnement intégré du réseau avec un coût de production minimum et un impact réduit sur le réseau. This work presents a study of the effects that integration of electrolysis facilities for Power-to-X processes have on the power grid. The novel simulation setup combines a high-resolution grid optimization model and a detailed scheduling model for alkaline water electrolysis. The utilization and congestion of power lines in northern Germany is investigated by setting different installed capacities and production strategies of the electrolysis facility. For electrolysis capacities up to 300 MW (∼50 ktH2/a), local impacts on the grid are observed, while higher capacities cause supra-regional impacts. Thereby, impacts are defined as deviations from the average line utilization greater than 5%. In addition, the minimum line congestion is determined to coincide with the daily-constrained production strategy of the electrolysis facility. Our result show a good compromise for the integrated grid-facility operation with minimum production cost and reduced impact on the grid. يقدم هذا العمل دراسة للتأثيرات التي يحدثها دمج مرافق التحليل الكهربائي لعمليات Power - to - X على شبكة الطاقة. يجمع إعداد المحاكاة الجديد بين نموذج تحسين الشبكة عالي الدقة ونموذج جدولة مفصل للتحليل الكهربائي للمياه القلوية. يتم التحقيق في استخدام وازدحام خطوط الطاقة في شمال ألمانيا من خلال تحديد السعات المركبة المختلفة واستراتيجيات الإنتاج لمنشأة التحليل الكهربائي. بالنسبة لسعات التحليل الكهربائي التي تصل إلى 300 ميجاوات (50 كيلوطن من الهيدروجين/أ)، يتم ملاحظة التأثيرات المحلية على الشبكة، بينما تتسبب السعات الأعلى في تأثيرات فوق إقليمية. وبالتالي، يتم تعريف التأثيرات على أنها انحرافات عن متوسط استخدام الخط أكبر من 5 ٪. بالإضافة إلى ذلك، يتم تحديد الحد الأدنى لازدحام الخط ليتزامن مع استراتيجية الإنتاج المقيدة يوميًا لمنشأة التحليل الكهربائي. تظهر نتائجنا حلاً وسطًا جيدًا لتشغيل مرافق الشبكة المتكاملة مع الحد الأدنى من تكلفة الإنتاج وتقليل التأثير على الشبكة.

The integration of variable renewable energy sources (RES) with increased share in power supply systems leads to new challenges in power system models. In this context, flexibility options have a high potential to balance fluctuating renewable energy feed-in in a cost efficient and low emission way [8, 9]. However, the combination of model parameters like simulation time, space, sectors with increasing level of detail call for advances in model reduction techniques [6]. Hence, a trade-off between the increasing complexity introduced by introducing flexibility options and the required computational effort has to be found. In Section 1, the extension of storage units in the energy system as one of these flexibility options is investigated with the eGo model [4]. Furthermore, the model can take into account several other possibilities of flexibility options such as demand side management or power-to-X, which can be modelled as functional storage. The latter will gain in importance when the heat and transport sector are decarbonized by the use of sector coupling [1]. Section 2 presents an approach of the technoeconomic assessment of flexibility options from an operator's point of view, based on a large-scale energy system model.

In this work, we investigate the economic viability of demand response (DR) as a balancing option for variable renewable energies, such as wind and solar. Our assessment is based on a highly resolved national energy system model for Germany coupled with a regional DR optimisation model. First, this allows us to determine the spatially resolved flexibility demand, e.g., for avoiding transmission grid congestion. Second, a high number of DR technologies from the residential, commercial and industrial sector, as well as sector coupling, can be considered to cover the regional flexibility demand. Our analysis is based on a scenario for 2035 with a 66% share of renewable energy sources in the power generation. The results show that the largest DR capacity is being installed in the west of Germany, an area with a high density of population and industry. All DR units have an aggregated capacity below 100 MW per transmission grid node. For the economic assessment, we further differentiate between two cases. In the first case with full DR cost consideration, the optimisation selects only large-scale technologies with low specific investment costs. The second case assumes that the required communication components are already installed. Here, we consider only variable costs and disregard the investment costs. As a result, several small-scale DR technologies are used, such as e-mobility. We publish the developed methodology as an open-source model, which allows reuse for other scientific purposes.