@article{SchellerJohanningSeimetal., author = {Scheller, Fabian and Johanning, Simon and Seim, Stephan and Schuchardt, Kerstin and Krone, Jonas and Haberland, Rosa and Bruckner, Thomas}, title = {Legal Framework of Decentralized Energy Business Models in Germany: Challenges and Opportunities for Municipal Utilities}, series = {Zeitschrift f{\"u}r Energiewirtschaft}, volume = {42}, journal = {Zeitschrift f{\"u}r Energiewirtschaft}, number = {3}, issn = {0343-5377}, doi = {10.1007/s12398-018-0227-1}, pages = {207 -- 223}, abstract = {Feasible and profitable business models to better integrate and harness decentrally generated renewable energy are expected to constitute a key element for the energy transition in Germany. Until now, generated electricity of decentralized systems is to the largest extent only used by the property owner directly or fed into the public grid. To make better use of the generated electricity, it is necessary to find business models that provide an opportunity for different market actors, such as municipal utilities and residential prosumers. Due to the importance, yet low-anticipated monetary potential of such solutions, the legislator encourages their implementation by exemption of statutory fees, levies and taxes as well as by offering public remunerations, premiums and compensations in some cases. Capitalizing on these benefits, however, is only feasible under compliance with the legal requirements. In the light of the considerations above, this work states and analyzes the legal and regulatory framework of different business models within the German energy landscape. The major aim is to identify opportunities and challenges for the implementation of the business models self consumption, direct consumption, direct marketing, demand response, community electricity storage and net metering at the municipal level. The findings show that the profitability of various decentralized on-site business models depends primarily on the current statutory cost exemptions and compensations. At the same time, the regulation is characterized by unsystematic specific exemptions which leads to uncertainty regarding long-term planning. Additionally, although not directly privileged by the existing legal framework, municipal utilities are better suited to handle the legal burdens due to their experience and their administrative infrastructure.}, language = {en} } @incollection{SchellerJohanningBruckner, author = {Scheller, Fabian and Johanning, Simon and Bruckner, Thomas}, title = {Integrierte techno-sozio-{\"o}konomische Modellierung urbaner Systeme}, series = {Agentenbasierte Modellierung urbaner Transformationsprozesse}, booktitle = {Agentenbasierte Modellierung urbaner Transformationsprozesse}, editor = {Johanning, Simon and Scheller, Fabian and K{\"u}hne, Stefan and Bruckner, Thomas}, isbn = {9783832554132}, doi = {10.30819/5413.01}, pages = {7 -- 17}, language = {de} } @article{SchellerKeitschKondziellaetal., author = {Scheller, Fabian and Keitsch, K. and Kondziella, H. and Georg Reichelt, D. and Dienst, S. and K{\"u}hne, S. and Bruckner, T.}, title = {Evaluation von Gesch{\"a}ftsmodellen im liberalisierten Energiemarkt}, series = {BWK. Das Energie-Fachmagazin}, volume = {67}, journal = {BWK. Das Energie-Fachmagazin}, number = {11}, pages = {24 -- 25}, language = {en} } @article{SchellerKroneKuehneetal., author = {Scheller, Fabian and Krone, Jonas and K{\"u}hne, Stefan and Bruckner, Thomas}, title = {Provoking Residential Demand Response Through Variable Electricity Tariffs - A Model-Based Assessment for Municipal Energy Utilities}, series = {Technology and Economics of Smart Grids and Sustainable Energy}, volume = {3}, journal = {Technology and Economics of Smart Grids and Sustainable Energy}, number = {1}, doi = {10.1007/s40866-018-0045-x}, abstract = {With the suitable infrastructure of information and communication technologies in place, customers are able to perform demand response (DR), meaning that they can decrease or increase their electricity consumption in response to changes in their electricity tariff. In this research, different variable electricity tariffs are designed taking both customer and utility preferences into account. Subsequently, a model-based analysis on the basis of optimization model IRPopt (Integrated Resource Planning and Optimization) is carried out. Electricity customers are exposed to the designed tariffs in order to find out whether variable electricity tariffs are a suitable instrument for municipal energy utilities to exploit the potential laying in residential DR. Loads considered for DR in this work are those of selected electric household appliances and the loads of electric heat pumps. One major contribution of this work is that the assessment differentiates between different types of energy utilities, whose specific generation profiles are taken into account in the design of the variable tariffs. The results show that variable electricity tariffs have a small economic potential. However, customers only benefit if the design of the business model includes a proper compensation mechanism. In this context, successful business models require the direct cooperation of different municipal energy market actors. Furthermore, taking the specific generation profiles of municipal energy utilities into account in the design of variable electricity tariffs helps to increase the energy autonomy of municipalities.}, language = {en} } @inproceedings{SchellerReicheltDienstetal., author = {Scheller, Fabian and Reichelt, David G. and Dienst, Steffen and Johanning, Simon and Reichardt, Soren and Bruckner, Thomas}, title = {Effects of implementing decentralized business models at a neighborhood energy system level: A model based cross-sectoral analysis}, series = {14th International Conference on the European Energy Market (EEM)}, booktitle = {14th International Conference on the European Energy Market (EEM)}, isbn = {978-1-5090-5499-2}, doi = {10.1109/eem.2017.7981910}, pages = {1 -- 6}, abstract = {The reliable integration of decentralized energy technologies and the associated system transformations represent a challenging task. Taking into account existing cross-sectoral demand and supply structures, diverse communities require specific solutions. With an appropriate business model, municipal utilities might be capable to transform themselves in a successful way. For better decision-making, they need to investigate under what conditions certain business cases might represent a sustainable part of the future system and their future portfolio. On the basis of an innovative multi-model and cross-sector approach, this research paper aims to assess opportunities of such business models in terms of four strategic targets: affordability, profitability, autarky and ecology. The results of the combined evaluation of synthetic case studies provide insights under what conditions different business models show positive performance.}, language = {en} } @incollection{SchellerSchulteJohanningetal., author = {Scheller, Fabian and Schulte, Emily and Johanning, Simon and Geyler, Stefan and Moritz, Marie and Bruckner, Thomas}, title = {Beschreibung der realen Fallstudien als Forschungsobjekt f{\"u}r die modellbezogenen Analysen}, series = {Agentenbasierte Modellierung urbaner Transformationsprozesse. Smart Utilities And Sustainable Infrastructure Change}, booktitle = {Agentenbasierte Modellierung urbaner Transformationsprozesse. Smart Utilities And Sustainable Infrastructure Change}, editor = {Johanning, Simon and Scheller, Fabian and K{\"u}hne, Stefan and Bruckner, Thomas}, isbn = {9783832554132}, doi = {10.30819/5413.02}, pages = {21 -- 38}, language = {de} } @article{SchellerDoserSlootetal., author = {Scheller, Fabian and Doser, Isabel and Sloot, Daniel and McKenna, Russell and Bruckner, Thomas}, title = {Exploring the Role of Stakeholder Dynamics in Residential Photovoltaic Adoption Decisions: A Synthesis of the Literature}, series = {Energies}, volume = {13}, journal = {Energies}, number = {23}, doi = {10.3390/en13236283}, pages = {6283 -- 6283}, abstract = {Despite the intensive research on residential photovoltaic adoption, there is a lack of understanding regarding the social dynamics that drive adoption decisions. Innovation diffusion is a social process, whereby communication structures and the relations between sender and receiver influence what information is perceived and how it is interpreted. This paper addresses this research gap by investigating stakeholder influences in household decision-making from a procedural perspective, so-called stakeholder dynamics. A literature review derives major influence dynamics which are then synthesized based on egocentric network maps for distinct process stages. The findings show a multitude of stakeholders that can be relevant in influencing photovoltaic adoption decisions of owner-occupied households. Household decision-makers are mainly influenced by stakeholders of their social network like family, neighbors, and friends as well as PV-related services like providers and civil society groups. The perceived closeness and likeability of a stakeholder indicate a higher level of influence because of greater trust involved. Furthermore, the findings indicate that social influence shifts gradually from many different stakeholders to a few core stakeholders later on in the decision-making process. These insights suggest that photovoltaic (PV) adoption may be more reliably predicted if a process perspective is taken into account that not only distinguishes between different stakeholders but considers their dynamic importance along the process stages. In addition, especially time- and location-bound factors affect the influence strength. This clearly shows the importance of local and targeted interventions to accelerate the uptake.}, language = {en} } @article{SchellerDoserSchulteetal., author = {Scheller, Fabian and Doser, Isabel and Schulte, Emily and Johanning, Simon and McKenna, Russell and Bruckner, Thomas}, title = {Stakeholder dynamics in residential solar energy adoption: findings from focus group discussions in Germany}, series = {Energy Research \& Social Science}, volume = {76}, journal = {Energy Research \& Social Science}, issn = {2214-6326}, doi = {10.1016/j.erss.2021.102065}, pages = {102065 -- 102065}, abstract = {Although there is a clear indication that stages of residential decision making are characterized by their own stakeholders, activities, and outcomes, many studies on residential low-carbon technology adoption only implicitly address stage-specific dynamics. This paper explores stakeholder influences on residential photovoltaic adoption from a procedural perspective, so-called stakeholder dynamics. The major objective is the understanding of underlying mechanisms to better exploit the potential for residential photovoltaic uptake. Four focus groups have been conducted in close collaboration with the independent institute for social science research SINUS Markt- und Sozialforschung in East Germany. By applying a qualitative content analysis, major influence dynamics within three decision stages are synthesized with the help of egocentric network maps from the perspective of residential decision-makers. Results indicate that actors closest in terms of emotional and spatial proximity such as members of the social network represent the major influence on residential PV decision-making throughout the stages. Furthermore, decision-makers with a higher level of knowledge are more likely to move on to the subsequent stage. A shift from passive exposure to proactive search takes place through the process, but this shift is less pronounced among risk-averse decision-makers who continuously request proactive influences. The discussions revealed largely unexploited potential regarding the stakeholders local utilities and local governments who are perceived as independent, trustworthy and credible stakeholders. Public stakeholders must fulfill their responsibility in achieving climate goals by advising, assisting, and financing services for low-carbon technology adoption at the local level. Supporting community initiatives through political frameworks appears to be another promising step.}, language = {en} } @article{SchellerBurgenmeisterKondziellaetal., author = {Scheller, Fabian and Burgenmeister, Balthasar and Kondziella, Hendrik and K{\"u}hne, Stefan and Reichelt, David G. and Bruckner, Thomas}, title = {Towards integrated multi-modal municipal energy systems: An actor-oriented optimization approach}, series = {Applied Energy}, volume = {228}, journal = {Applied Energy}, issn = {1872-9118}, doi = {10.1016/j.apenergy.2018.07.027}, pages = {2009 -- 2023}, abstract = {Against the backdrop of a changing political, economic and ecological environment, energy utilities are facing several challenges in many countries. Due to an increasing decentralization of energy systems, the conventional business could be undermined. Yet the reliable integration of small-scale renewable technologies and associated system transformations could represent an opportunity as well. Municipal energy utilities might play a decisive role regarding successful transition. For better decision-making, they need to investigate under which conditions certain novel business cases can become a sustainable part of their future strategy. The development of the strategy is a challenging task which needs to consider different conditions as business portfolio, the customer base, the regulatory framework as well as the market environment. Integrated Multi-Modal Energy System (IMMES) models are able to capture necessary interactions. This research introduces a model-driven decision support system called Integrated Resource Planning and Optimization (IRPopt). Major aim is to provide managerial guidance by simulating the impact of business models considering various market actors. The mixed-integer linear programming approach exhibits a novel formal interface between supply and demand side which merges technical and commercial aspects. This is achieved by explicit modeling of municipal market actors on one layer and state-of-the-art technology components on another layer as well as resource flow relations and service agreements mechanism among and between the different layers. While this optimization framework provides a dynamic and flexible policy-oriented, technology-based and actor-related assessment of multi-sectoral business cases, the encapsulation in a generic software system supports the facilitation. Based on the actor-oriented dispatch strategy, flexibility potential of community energy storage systems is provided to demonstrate a real application.}, language = {en} } @article{ReicheltKuehneSchelleretal., author = {Reichelt, David Georg and K{\"u}hne, Stefan and Scheller, Fabian and Abitz, Daniel and Johanning, Simon}, title = {Towards an Infrastructure for Energy Model Computation and Linkage}, series = {INFORMATIK 2020}, journal = {INFORMATIK 2020}, editor = {Reussner, R. H. and Koziolek, A. and Heinrich, R.}, doi = {10.18420/inf2020_21}, pages = {225 -- 235}, abstract = {Decision makers strive for optimal ways of production and usage of energy. To adjust their behavior to the future situation of markets and technology, the execution of different models predicting e.g. energy consumption, energy production, prices and consumer behavior is necessary. This execution is itself time-consuming and requires input data management. Furthermore, since different models cover different aspects of the energy domain, they need to be linked. To speed up the linkage and reduce manual errors, these linkage needs to be automated. We present IRPsim, an infrastructure for computation of different models and their linkage. The IRPsim-infrastructure enables management of model data in a structured database, parallelized model execution and automatic model linkage. Thereby, IRPsim allows researchers and practitioners to use energy system models for strategic business model analysis.}, language = {en} } @article{BiemannGunkelSchelleretal., author = {Biemann, Marco and Gunkel, Philipp Andreas and Scheller, Fabian and Huang, Lizhen and Liu, Xiufeng}, title = {Data Center HVAC Control Harnessing Flexibility Potential via Real-Time Pricing Cost Optimization Using Reinforcement Learning}, series = {IEEE Internet of Things Journal}, volume = {10}, journal = {IEEE Internet of Things Journal}, number = {15}, doi = {10.1109/jiot.2023.3263261}, pages = {13876 -- 13894}, abstract = {With increasing electricity prices, cost savings through load shifting are becoming increasingly important for energy end users. While dynamic pricing encourages customers to shift demand to low price periods, the nonstationary and highly volatile nature of electricity prices poses a significant challenge to energy management systems. In this article, we investigate the flexibility potential of data centers by optimizing heating, ventilation, and air conditioning systems with a general model-free reinforcement learning (RL) approach. Since the soft actor-critic algorithm with feedforward networks did not work satisfactorily in this scenario, we propose instead a parameterization with a recurrent neural network architecture to successfully handle spot-market price data. The past is encoded into a hidden state, which provides a way to learn the temporal dependencies in the observations and highly volatile rewards. The proposed method is then evaluated in experiments on a simulated data center. Considering real temperature and price signals over multiple years, the results show a cost reduction compared to a proportional, integral and derivative controller while maintaining the temperature of the data center within the desired operating ranges. In this context, this work demonstrates an innovative and applicable RL approach that incorporates complex economic objectives into agent decision-making. The proposed control method can be integrated into various Internet of Things-based smart building solutions for energy management.}, language = {en} }