Martin Robinius

Impact of different time series aggregation methods on optimal energy system design

Abstract Modeling renewable energy systems is a computationally-demanding task due to the high fluctuation of supply and demand time series. To reduce the scale of these, this paper discusses different methods for their aggregation into typical periods. Each aggregation method is applied to a different type of energy system model, making the methods fairly incomparable. To overcome this, the different aggregation methods are first extended so that they can be applied to all types of multidimensional time series and then compared by applying them to different energy system configurations and analyzing their impact on the cost optimal design. It was found that regardless of the method, time series aggregation allows for significantly reduced computational resources. Nevertheless, averaged values lead to underestimation of the real system cost in comparison to the use of representative periods from the original time series. The aggregation method itself e.g., k-means clustering plays a minor role. More significant is the system considered: Energy systems utilizing centralized resources require fewer typical periods for a feasible system design in comparison to systems with a higher share of renewable feed-in. Furthermore, for energy systems based on seasonal storage, currently existing models integration of typical periods is not suitable.

Time series aggregation for energy system design: Modeling seasonal storage

The optimization-based design of renewable energy systems is a computationally demanding task because of the high temporal fluctuation of supply and demand time series. In order to reduce these time series, the aggregation of typical operation periods has become common. The problem with this method is that these aggregated typical periods are modeled independently and cannot exchange energy. Therefore, seasonal storage cannot be adequately taken into account, although this will be necessary for energy systems with a high share of renewable generation.

Fower-to-hydrogen and hydrogen-to-X: Which markets? Which economic potential? Answers from the literature

With the expansion of renewable energys contribution to the energy mix, balancing the electricity grid is becoming increasingly challenging. Alongside other solutions, Power-to-Hydrogen concepts are gaining significant interest. In this paper, the “Task 38”, initiated by the Hydrogen Implementing Agreement of the International Energy Agency, presents the first of a two-step literature review regarding Power-to-Hydrogen and Hydrogen-to-X concepts with a focus on prospective market and economic potential. The study reveals a large scope of literature that shows a considerable variety of suggested implementation schemes. The transportation sector is identified as the most promising consumer market. Hydrogen-to-Gas pathways will require subsidies in order to be profitable. Hydrogen-to-Power becomes an economically promising option in the context of systems with high shares of renewables and a need for longer-term storages. Additionally, key enablers for Power-to-Hydrogen concepts are identified; namely support policies, concurrently with ongoing progress on the development and implementation of industry standard.

An option for stranded renewables: electrolytic-hydrogen in future energy systems

Future energy systems will likely be challenged by large quantities of stranded renewable electricity that cannot be used in the conventional electrical grid. Using surplus electricity for electrolysis and thereby producing hydrogen is seen as a valuable solution functioning as an energy storage and transport medium and providing other sectors, such as transport or industry, with required feedstocks at the same time. In this study, we suggest using a set of assessment tools to highlight the quantitative potential, cost and environmental performance of electrolytic hydrogen production, transmission and storage. Our approach employs power sector modeling for Germany with three sequential elements: (i) a market model, (ii) power flow modeling, and (iii) re-dispatch modeling. The results were then used to identify suitable locations for large scale electrolysis plants. Electrolysis, large-scale gas storage, a transmission pipeline and other system components were scaled-up and the total cost was calculated. In a final step, we looked at greenhouse gas emissions as one of the major aspects regarding the environmental performance of the hydrogen delivered. Based on our analysis, annual hydrogen production rates of up to 189 kilotons have been determined for the state of Schleswig-Holstein, which exhibits the largest potential for utilizing surplus power from renewables. The economic analysis reveals a hydrogen cost of 3.63–5.81€ kg−1, including installations, for large-scale storage and transmission. If surplus power from renewables is used for hydrogen production, the total greenhouse gas emissions of hydrogen provision were determined to be up to 435 gCO2-eq. kg−1. Using grid electricity, this value increased to some 17 000 gCO2-eq. kg−1.

Quantifizierung lokaler Stromüberschüsse in Deutschland anhand unterschiedlicher Windenergie-Ausbaustufen

Die Bundesregierung hat klare Ziele zur Reduktion der Treibhausgase (THG), bezogen auf 1990 von 40% bis 2020, 55% bis 2030, 70% bis 2014 und 80-95% bis 2050, gesetzt [1]. [2-4] zeigt, dass mit dem Power-to-Gas Konzept und der Nutzung des so entstehenden Wasserstoffs im Verkehrssektor das Reduktionsziel fur das Jahr 2030 erreicht werden kann. Das verwendete Szenario geht von einer installierten Onshore-Windenergieleistung von 169 GW aus. Dieses bilanzielle Modell wird um ein regionales Modell erweitert, welches in Gemeindeauflosung die Stromuberschusse aus der Windenergie lokalisiert und quantifiziert. Dadurch konnen zukunftig Fragen zum Standort und zur Dimensionierung von Elektrolyseuren zur Wasserstoffherstellung beantwortet werden.