Abstract Background An ’energy community’ can add socioeconomic components to microgrids and has recently been solidified as the regulatory concept of a ’Citizen Energy Community’ by the European Union. Such energy communities can further be supplemented with digital capabilities. This paper provides insights from a 13-month case study on a digitally enabled energy community with prosumers with limited ability to provide manual demand response, who were enabled to engage in peer-to-peer trading of local energy generation. Results Long-term willingness to pay for local sustainable electricity in the market environment was lower than expected. Overall willingness and ability to provide manual demand response might be low. Participants’ use of the provided digital tools were at least partly driven by their desire to control energy costs. Conclusions Repeat interaction with the energy community’s market and its inherent complexities might limit the ability of energy communities to provide technical and economic benefits. This diminishes the appeal of corresponding business models. One direction to make energy communities more attractive to regulators and utilities is the conceptualization, design, and empirical evaluation of systems that lead to low perceived complexity for participants while enabling high levels of external automated control.

Background : Citizen Energy Communities, particularly local energy markets, have been discussed for several years as a concept that allows private households, prosumers, and small local generation facilities to be actively integrated into the existing energy system. According to the literature, it promotes investment incentives and introduces local price signals, to which the participants respond with behavioral changes. However, there is a lack of long-term, real-world data, and insights on participants’ behavior in such communities, which is crucial to assess their overall performance and functionality. We fill this research gap by analyzing user behavior based on a one-year pilot project’s recorded data and expert interviews with its participants. Results : In three analyses, we observe that participants are initially willing to pay a premium price above the grid tariff for local green power, but this willingness decreases in the long run, affecting investment incentives. In contrast to assumptions in the literature, participants show decreasing activity over time and do not respond to specific information nudges. However, regular reminders and reports are perceived as valuable by the participants and support their integration into the community. Also, we cannot confirm behavioral consumption changes in response to different price signals. Conclusion : Our results show that the active integration of participants is more challenging than hitherto assumed, and both market mechanism complexity and the need for automation play a central role in a successful design.

In recent years, local energy markets have become an important concept in more decentralized energy systems. Implementations in pilot projects provide first insights into different hypotheses and approaches. From a technical perspective, the requirements for the IT infrastructure of a local energy market are diverse, and a holistic view of its architecture is therefore necessary. This article presents an IT-architecture, which enables all basic local energy market functionalities, processes and modules based on the available literature. The proposed IT-architecture can serve as a blueprint for future local market projects as it covers the basic processes and is at the same time extendable. Furthermore, we give a detailed description of a real-world implementation of a local energy market using the described IT-architecture and discuss the advantages and disadvantages of the utilized technologies along with this case study.

Coordinated operation of Coupled Electric Power and District Heating Networks (CEPDHNs) brings advantages as e.g., the district heating networks can provide flexibility to the electric power network, and the entire system operation can be further decarbonized through heat pumps and electric boilers using electricity from renewable energy sources. Still, today CEPDHNs are often not operated in a coordinated way causing a lack of efficiency. This paper shows, how efficient resource allocation is achieved by determining the power exchange between both networks over an aggregated market. We introduce a welfare-optimizing, market-based operation for a CEPDHN that satisfies operational constraints and considers network losses. The objective is to integrate uniform pricing market-clearing and operational constraints into one approach, in order to obtain high incentive compatibility for the market participants while preventing high uplift costs from redispatch. For this, we use a hybrid market model mainly based on uniform marginal pricing and additionally utilize pay-as-bid pricing for a fraction of the allocated bids and offers. We perform a case study with a real CEPDHN to validate the functionality of the developed approach. The results show that our solution leads to efficient resource allocation while maintaining safe network operation and preventing uplift costs due to redispatch.

The rapid transformation of the electricity sector increases both the opportunities and the need for Data Analytics. In recent years, various new methods and fields of application have been emerging. As research is growing and becoming more diverse and specialized, it is essential to integrate and structure the fragmented body of scientific work. We therefore conduct a systematic review of studies concerned with developing and applying Data Analytics methods in the context of the electricity value chain. First, we provide a quantitative high-level overview of the status quo of Data Analytics research, and show historical literature growth, leading countries in the field and the most intensive international collaborations. Then, we qualitatively review over 200 high-impact studies to present an in-depth analysis of the most prominent applications of Data Analytics in each of the electricity sector's areas: generation, trading, transmission, distribution, and consumption. For each area, we review the state-of-the-art Data Analytics applications and methods. In addition, we discuss used data sets, feature selection methods, benchmark methods, evaluation metrics, and model complexity and run time. Summarizing the findings from the different areas, we identify best practices and what researchers in one area can learn from other areas. Finally, we highlight potential for future research.

Transmission grid congestion is one of the consequences of an increasing power generation from intermittent renewable capacities. These are often installed in the periphery and have rare generation peaks. It thus becomes more complicated to ensure a balanced grid operation at all times. It is necessary to develop holistic strategies for the management of congestion that consider short and long operating horizons. This paper introduces several congestion management mechanisms along minimal analytical and numerical models. These solutions are then discussed in regard to the necessary data availability and their contribution to an improved congestion management strategy. The paper therefore contributes to the development of a research agenda at the intercept between economists and computer scientists in the area of energy informatics.

Local energy markets (LEMs) are a highly discussed topic in the academic community. In this paper, we address one of the most critical challenges for these markets. In recent years the valuation of energy sources by the consumer became more differentiated. Today many consumers prefer various energy sources (e.g. PV or Wind) in different degrees. Taking this distinction into account causes several challenges in the market design as energy becomes a heterogeneous good. We show that already existing auction mechanisms cannot provide a satisfactory solution to represent these differences. As a result, we propose a two-step mechanism specifically tailored for the differing consumer valuations. It introduces a merit-order based market for each type of energy. Thus, each separate market deals with one source of energy and is cleared separately. With that, the determination of the chronological order of the different markets becomes essential. The proposed mechanism aims at taking the various preferences of all consumers into account by using the Borda count voting mechanism. The theoretically presented market mechanism is supported by a real-life data case study with data from the Landau Microgrid Project.

The increasing development of small, distributed generation capacity poses a challenge to transmission grid operators. It is becoming increasingly difficult to react with an optimal expansion of the transmission grid, especially as the intermittent infeed increases. Therefore, in this paper we propose a mechanism to liberalize transmission system expansions to allow for a market to coordinate appropriate reactions to changes in generation and demand. We evaluate it analytically on exemplary networks.

Currently, blockchain technology is a widely discussed hype in the energy community. It may have the potential to revolutionize the energy system and support the energy transition towards distributed renewable generation. In particular, local electricity markets (LEMs) seem to provide applications for the usage of blockchain technology. Through its innovative design as a distributed and decentralized information system, blockchain supporters see its potential in organizing residential households and prosumers in LEMs. We assess the current maturity of blockchain-based applications for LEMs. To this end, we develop a blockchain maturity model that constitutes a framework for analyzing the current and future maturity of blockchain-based LEMs in a comprehensive structured approach. In a second step, we apply the new blockchain maturity model to an use case of a blockchain-based LEM. Our assessment shows that, in the current status, the project is in an early stage of maturity due to missing regulatory rules and standardization.

In many European countries, electricity-related charges, distribution grid tariffs and taxes for small consumers depend on the amount of energy they draw from the grid. Often, grid tariffs in regulated markets do not yet provide incentives for grid-compatible behavior e.g., load capping or a temporal shifting of loads. When designing new grid fee tariffs, regulators must consider a wide range of criteria: Economic incentives must be in line with grid operation and expansion. Further, practical aspects in terms of complexity, transaction costs and enforceability must be considered. In addition, ethical requirements must be met, since basic services must be provided for all participants. Most research evaluates new grid fee tariffs only regarding isolated aspects. Additionally, these aspects are usually only analyzed qualitatively. Our paper provides a comprehensive overview of the criteria for assessing grid tariffs in various aspects derived from literature. We propose measurable constructs to quantify three assessment criteria. These criteria are embedded in a framework to make grid tariffs comparable for a given population of grid users. The applicability of the framework is demonstrated for a stylized population of grid participants in four scenarios. The aim is to provide political decision-makers with a comprehensible basis for the evaluation and development of new tariffs for grid fees. We find that adding a demand component makes tariffs more cost reflective in all scenarios and leads to a smaller average bill change at the current shares of domestic PV and BEV usage compared to consumption based fees.