Our research results show the economic potential of new information technology options in the smart grid. From our research results, we derive concrete requirements for a target-oriented design of energy markets, systems and services. Our contribution to the implementation of the energy transition also includes the identification of sensible adjustments to the regulatory framework. Follow the link below, to check out our most recent research contributions.
Integrating Hydrogen in Single-price electricity systems: The effects of spatial economic signals
Authors: vom Scheidt, Frederik; Qu, Jingyi; Staudt, Philipp; Mallapragada, Dharik S.; Weinhardt, Christof
Abstract: Hydrogen can contribute substantially to the reduction of carbon emissions in industry and transportation. However, the production of hydrogen through electrolysis creates interdependencies between hydrogen supply chains and electricity systems. Therefore, as governments worldwide are planning considerable financial subsidies and new regulation to promote hydrogen infrastructure investments in the next years, energy policy research is needed to guide such policies with holistic analyses. In this study, we link an electrolytic hydrogen supply chain model with an electricity system dispatch model. We use this methodology for a cross-sectoral case study of Germany in 2030. We find that hydrogen infrastructure investments and their effects on the electricity system are strongly influenced by electricity prices. Given current uniform single-prices in Germany, hydrogen production increases congestion costs in the electricity grid by 17%. In contrast, passing spatially resolved electricity price signals leads to electrolyzers being placed at low-cost grid nodes and further away from consumption centers. This causes lower end-use costs for hydrogen. Moreover, congestion management costs decrease substantially, by up to 20% compared to the benchmark case without hydrogen. These savings could be transferred into according subsidies for hydrogen production. Thus, our study demonstrates the benefits of differentiating economic signals for hydrogen production based on spatial criteria.
Merchant Transmission in Single-Price Electricity Markets with Cost-Based Redispatch
Authors: Staudt, Philipp; Oren, S. S.
Abstract: Transmission expansion is a complex problem in energy market design and research has not yet provided a market-based solution that is superior to a (partly) regulated approach. Furthermore, markets with a single market clearing price lack regional incentives for system friendly generation or transmission capacity expansion. In this paper, we propose a market design for transmission expansion that can be implemented in single-price markets with cost-based redispatch and we describe its properties. We show that our market solution is incentive compatible, satisfies the ’beneficiary pays’ requirement and leads to a welfare optimal grid expansion otherwise achieved by an integrated optimization approach of a benevolent grid operator. We apply the mechanism to the German electricity system in 2018, 2019 and 2030 as an example and show that transmission capacity expansion is greatly reduced using the mechanism instead of a no-congestion regulation. We also test the robustness of the approach to erroneous generation capacity expectations and find that the impact on economic results is limited. Finally, we extend our approach to include congestion reducing generation capacity investment and discuss the strategic effects on a 6-node reference grid.
A Sharing Economy For Residential Communities With PV-Coupled Battery Storage: Benefits, Pricing And Participant Matching
Authors: Henni, Sarah; Staudt, Philipp; Weinhardt, Christof
Abstract: The transition of the energy sector towards more decentral, renewable, and digital structures and higher involvement of local residents as prosumers calls for innovative business models. In this paper, we investigate a sharing economy model that enables a residential community to share solar generation and storage capacity. We simulate 520 sharing communities of five households each with differing load profile configurations and find that they achieve average annual savings of 615€ as compared to individual operation. Using the gathered data on electricity consumption in a sharing community, we discuss a fixed pricing approach to achieve a fair distribution of the profits generated through the sharing economy. We further investigate the impact of prosumers’ and consumers’ load profile patterns on the profitability of the sharing communities. Based on these findings, we explore the potential to match and coordinate suitable communities through a platform-based sharing economy model. Our results enable practitioners to find optimal additions to an energy-sharing community and provide new insights for researchers regarding possible pricing schemes in energy communities.
Decision Support And Strategies For The Electrification Of Commercial Fleets
Authors: Schmidt, Marc; Staudt, Philipp; Weinhardt, Christof
Abstract: Electric vehicles have proven to be a viable mobility alternative that leads to emissions reductions and hence the decarbonization of the transportation sector. Nevertheless, electric vehicle adoption is progressing slowly. Vehicle fleets are a promising starting point for increased market penetration. With this study, we address the issue of fleet electrification by analyzing a data set of 81 empirical mobility patterns of commercial fleets. We conduct a simulation to design a decision support system for fleet managers evaluating which fleets have a good potential for electrification and how fleets can improve the number of successful electric trips by adapting their charging strategy. We consider both heuristics and optimized scheduling. Our results show that a large share of fleets can score a close to optimal charging schedule using a simple charging heuristic. For all other fleets, we provide a decision mechanism to assess the potential of smart charging mechanisms.
Probabilistic forecasting of household loads: Effects of distributed energy technologies on forecast quality
Authors: vom Scheidt, Frederik; Dong, Xinyuan; Bartos, Andrea; Staudt, Philipp; Weinhardt, Christof
Publication: Association for Computing Machinery
Abstract: Distributed energy technologies introduce new volatility to the edges of low voltage grids and increase the importance of short-term forecasting of electric loads at a granular level. To address this issue, first probabilistic forecasting models for residential loads have been developed in recent years. However, knowledge is lacking about how well these models perform for households with different endowments of distributed energy technologies. Therefore, we first create a new semi-synthetic data set which contains not only conventional residential loads, but net loads of 40 households differentiated regarding heating type (electric space heating, no electric space heating), and rooftop solar installation (solar, no solar). Second, we develop a novel probabilistic forecasting model based on Gated Recurrent Units that uses data from weather forecasts and calendar variables as external features. We apply the developed model, and three benchmarks, to the new data set and find that the GRU model outperforms the other models for households with electric heating, with solar, and with both technologies, but not for households without distributed energy technologies.
Infrastructural Coupling Of The Electricity And Gas Distribution Grid to Reduce Renewable Energy Curtailment
Authors: Henni, Sarah; Staudt, Philipp; Kandiah, Balendra; Weinhardt, Christof
Abstract: Following the European Union’s emission reduction goals, the expansion of intermittent renewable energy sources is being pursued by numerous member states. This poses challenges especially to low-voltage electricity grids that are not designed for the volatile and unpredictable feed-in from renewable generation capacity. In addition to the expansion of renewable capacity, further measures, including the decarbonization of the transport, heating and industrial sectors are needed to achieve the environmental targets. Sector coupling refers to the electrification of end-user energy demand as well as the coupling of different energy infrastructures such as the electricity and gas networks through Power-to-Gas technology. In this paper, we address these issues by developing a methodology that enables distribution system operators to identify future grid constraints in advance and to address them using Power-to-Gas technology using geographical information systems. In further detail, we present a novel approach to identify sections of the distribution network that are likely to be congested in the future in order to locate congestion-induced potential sites for Power-to-Gas plants. We show the applicability of our approach in a case study for a municipality in the German state of Baden-Wurttemberg. We show the economic feasibility of a medium-sized Power-to-Gas plant that couples the gas and electricity distribution networks. Our findings offer insights into the possibility to use the existing gas infrastructure in order to integrate surplus electricity generation, avoid electricity grid congestion and to further decarbonize energy demand.
Scaling The Concept Of Citizen Communities Through A Platform-Based Decision Support System
Authors: Golla, Armin; Henni, Sarah; Staudt, Philipp
Publication: Association for Information Systems
Abstract: The first generation of prototypes for citizen energy communities is completed. While these pilot projects of decentralized energy communities receive much attention in research, their concepts have yet to be implemented on a large scale. We find that potential participants of citizen energy communities lack information and the means to propose and implement joint infrastructure projects like shared electrical storage investment. Furthermore, in current pilots, the main focus is often directed towards electricity generation and consumption. However, for a successful energy transition, the three energy sectors of electricity, heat and mobility need to be considered. In this paper, we introduce a platform-based decision support information system that enables residential consumers and prosumers to create citizen energy communities. We determine the information that is needed to configure a local energy infrastructure and conceptualize a coordination mechanism that merges diverging preferences of participants. We demonstrate the application of the proposed framework on empirical data from the Landau Microgrid Project to provide a proof of concept. The developed platform facilitates the transition of citizen energy communities from a niche phenomenon to a large-scale concept and is therefore an implementable solution from the information system domain towards the mitigation of climate change.
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