Modeling flexibility using artificial neural networks

The flexibility of distributed energy resources (DERs) can be modeled in various ways. Each model that can be used for creating feasible load profiles of a DER represents a potential model for the flexibility of that particular DER. Based on previous work, this paper presents generalized patterns for exploiting such models. Subsequently, the idea of using artificial neural networks in such patterns is evaluated. We studied different types and topologies of ANNs for the presented realization patterns and multiple device configurations, achieving a remarkably precise representation of the given devices in most of the cases. Overall, there was no single best ANN topology. Instead, a suitable individual topology had to be found for every pattern and device configuration. In addition to the best performing ANNs for each pattern and configuration that is presented in this paper all data from our experiments is published online. The paper is concluded with an evaluation of a classification based pattern using data of a real combined heat and power plant in a smart building

Definition von Flexibilität in einem zellulär geprägten Energiesystem

Bereits existierende nationale und internationale Definitionen des Begriffs Flexibilität sind zu unpräzise und werden den Anforderungen, die sich bei der Beschreibung von Flexibilität innerhalb eines zellulären Energiesystems ergeben, nicht gerecht. Diese Arbeit benennt und definiert Flexibilitätsbegriffe, um ein gemeinsames Verständnis zu schaffen. Zunächst werden die technisch-ökonomischen Flexibilitätsbegriffe Fahrkurve, Flexibilitäts-bereitstellung, Flexibilitätserbringung, Quantifizierbarkeit, Prognostizierbarkeit sowie explizite und implizite Flexibilität beschrieben. Im Anschluss werden Begriffe beschrieben, die mit der Ansteuerung und dem Abruf von Flexibilität einhergehen. Darunter fallen die aktive und passive Flexibilitätserbringung, der zustands- und kommunikationsgesteuerte Flexibilitätsabruf sowie der direkte und indirekte Flexibilitätsabruf. Zuletzt wird eine Unterscheidung anhand des Verwendungszwecks in system-, netz- und marktdienliche Flexibilität vorgenommen. Das Ergebnis sind exakte Begriffsdefinitionen und Begriffsabgrenzungen, auf deren Basis Flexibilitätsprodukte beschrieben und kategorisiert werden können, die für die Konzeption und Demonstration eines zellulären geprägten Energiesystems unabdingbar sind

Conceptualising fields of action for sustainable intensification A systematic literature review and application to regional case studies

[EN] After two decades of research on sustainable intensification (SI), namely securing food production on less environmental cost, heterogeneous understandings and perspectives prevail in a broad and partly fragmented scientific literature. Structuring and consolidating contributions to provide practice-oriented guidelines are lacking. The objectives of this study are to (1) comprehensively explore the academic SI literature, (2) propose an implementation-oriented conceptual framework, and (3) demonstrate its applicability for region-specific problem settings. In a systematic literature review of 349 papers covering the international literature of 20 years of SI research, we identified SI practices and analysed temporal, spatial and disciplinary trends and foci. Based on key SI practices, a conceptual framework was developed differentiating four fields of action from farm to regional and landscape scale and from land use to structural optimisation. Its applicability to derive region specific SI solutions was successfully tested through stakeholder processes in four European case studies. Disciplinary boundaries and the separation of the temporal and spatial strands in the literature prevent a holistic address of SI. This leads to the dominance of research describing SI practices in isolation, mainly on the farm scale. Coordinated actions on the regional scale and the coupling of multiple practices are comparatively un-derrepresented. Results from the case studies demonstrate that implementation is extremely context-sensitive and thus crucially depends on the situational knowledge of farmers and stakeholders. Although, there is no 'one size fits all' solution, practitioners in all regions identified the need for integrated solutions and common action to implement suitable SI strategies at the regional landscape level and in local ecosystems.This research was financially supported by the European Commission under grant agreement 652615 and conducted in the context of the ERA-Net FACCE SURPLUS project VITAL, with the national funders NWO (Netherlands), BMBF (Germany), INIA (Spain), ANR (France).Weltin, M.; Zasada, I.; Piorr, A.; Debolini, M.; Geniaux, G.; Moreno-Pérez, OM.; Scherer, L.... (2018). Conceptualising fields of action for sustainable intensification A systematic literature review and application to regional case studies. Agriculture Ecosystems & Environment. 257:68-80. https://doi.org/10.1016/j.agee.2018.01.023S688025

Multi-modal Building Energy Management

The energy transition from fossil energy carriers and centralized power plants towards renewable energy sources and distributed generation calls for suitable approaches supporting this change. Smart buildings adapting their inbound and outbound energy provision, i.e., their demand from as well as supply to surrounding energy systems, will be an essential part of a multi-modal future energy system. A promising way to gain additional flexibility in our energy systems is a holistic energy management approach to the provision, conversion, distribution, storage, and utilization of all energy carriers. This thesis contributes to the field of Energy Informatics by providing, firstly, theoretical foundations of multi-energy systems, multi-modal energy management, and multi-commodity optimization, secondly, the architectural design and exemplary implementation of an automated building energy management system performing multi-modal energy management by means of multi-commodity optimization, and, finally, the evaluation of exemplary smart buildings using multi-modal building energy management systems, quantifying the expected effects of automated energy management, hybrid home appliances, and measures of demand side management in exemplary multi-energy systems

Modeling flexibility using artificial neural networks

Abstract The flexibility of distributed energy resources (DERs) can be modeled in various ways. Each model that can be used for creating feasible load profiles of a DER represents a potential model for the flexibility of that particular DER. Based on previous work, this paper presents generalized patterns for exploiting such models. Subsequently, the idea of using artificial neural networks in such patterns is evaluated. We studied different types and topologies of ANNs for the presented realization patterns and multiple device configurations, achieving a remarkably precise representation of the given devices in most of the cases. Overall, there was no single best ANN topology. Instead, a suitable individual topology had to be found for every pattern and device configuration. In addition to the best performing ANNs for each pattern and configuration that is presented in this paper all data from our experiments is published online. The paper is concluded with an evaluation of a classification based pattern using data of a real combined heat and power plant in a smart building