Modeling multimodal energy systems

Information and communication technology (ICT) and the technology of coupling points including power-to-gas (PtG), power-to-heat (PtH) and combined heat and power (CHP) reshape future energy systems fundamentally. To study the resulting multimodal smart energy system, a proposed method is to separate the behavior of the component layer from the control layer. The component layer includes pipelines, power-lines, generators, loads, coupling points and generally all components through which energy flows. In the work at hand, a model is presented to analyze the operational behavior of the component layer. The modeling problem is formulated as state and phase transition functions, which present the external commands and internal dynamics of system. Phase transition functions are approximated by ordinary differential equations, which are solved with integral methods. State transition functions are nonlinear algebraic functions, which are solved numerically and iteratively with a modified Newton-Raphson method. In a proof-of-concept case study, a scenario shows the expected multi-sector effects based on evaluated models

Requirements for an Open Digital Platform for Interdisciplinary Energy Research and Practice

Energy systems are changing rapidly and energy research is fundamental to enable and optimize this change involving academics, practitioners, and the public. Therefore, an open digital platform to share knowledge and experiences is crucial for the energy sector. We identify and discuss requirements from 36 semi-structured interviews with various stakeholders for a platform based on five essential elements. The competence element enables researchers and developers to find suitable partners for their research and practice projects, and the best practices element delivers ideas to structure cooperative energy research. The repository element helps to find available data and frameworks for energy systems’ simulation and optimizations. Frameworks and models are coupled by using the simulation element. Last, results and contents from the energy community can be published within the transparency element to reach various interested stakeholders. We discuss implications and recommendations as well as further research directions

Dynamic inspection interval determination for efficient distribution grid asset-management

Asset-management accounts for a significant share of grid operators’ influenceable costs, which are under high economic pressure due to deregulation. In asset-management, visual inspections are the main measure to determine asset conditions. In the context of digitalization, we propose a concept to acquire additional information about the condition of distribution substations and to derive flexible inspection intervals from this information, in contrast to fixed intervals that are common in scientific literature and practice. Thus, knowledge about the substations increases, inspection intervals can be expanded dynamically, and significant cost savings are possible, which we demonstrate by the example of a German distribution grid operator

A Multi-Criteria Metaheuristic Algorithm for Distributed Optimization of Electric Energy Storage

The distributed schedule optimization of energy storage constitutes a challenge. Such algorithms often expect an input set containing all feasible schedules or respectively require to efficiently search the schedule space. It is hardly possible to accomplish this with energy storage due to its high flexibility. In this paper, the problem is introduced in detail and addressed by a metaheuristic algorithm, which generates a preselection of schedules. Three contributions are presented to achieve this goal: First, an extension for a distributed schedule optimization allowing a simultaneous optimization is developed. Second, an evolutionary algorithm is designed to generate optimized schedules. Third, the algorithm is extended to include an arbitrary local criterion. It is shown that the presented approach is suitable to schedule electric energy storage in real households and industries with different generator and storage types

Choosing the right model for unified flexibility modeling

Using aggregated flexibility from distributed small-scale power devices is an extensively discussed approach to meet the challenges in modern and increasingly stochastic energy systems. It is crucial to be able to model and map the flexibility of the respective power devices in a unified form to increase the value of the cumulative flexibility from different small-scale power devices by aggregation. In order to identify the most suitable approach for unified flexibility modeling we present a framework to evaluate and compare the advantages and disadvantages of already existing modeling approaches in different levels of detail. As an introduction to flexibility modeling and as a basis for the evaluation process we initially provide a comprehensive overview of the broad range of flexibility models described in scientific literature. Subsequently, five selected modeling approaches allowing the generation of a unified flexibility representation for different power devices are presented in detail. By using an evaluation metric we assess the suitability of the selected approaches for unified flexibility modeling and their applicability. To allow a more detailed performance analysis, the best evaluated models are implemented and simulations with different small-scale devices are performed. The results shown in this paper highlight the heterogeneity of modeling concepts deriving from the various interpretations of flexibility in scientific literature. Due to the varying complexity of the modeling approaches, different flexibility potentials are identified, necessitating a combination of approaches to capture the entire spectrum of the flexibility of different small-scale power devices. Furthermore, it is demonstrated that a complex model does not necessarily lead to the discovery of higher flexibility potentials, and recommendations are given on how to choose an appropriate model. © 2022, The Author(s)

Towards Improved Findability of Energy Research Software by Introducing a Metadata-based Registry

Research software in the energy domain becomes increasingly important for the analysis, simulation, and optimization of energy systems and supports design decisions in the required transition of energy systems to tackle the climate crisis. To make energy research software (ERS) more findable, it should be described with metadata following the FAIR (findable, accessible, interoperable, and reusable) principles and be registered in a common registry. To this end, we motivate and present a concept for a metadata-based registry for ERS which should enable researchers to easily add new ERS as well as to find new ERS

Towards Improved Findability of Energy Research Software by Introducing a Metadata-based Registry

Research software in the energy domain becomes increasingly important for the analysis, simulation, and optimization of energy systems and supports design decisions in the required transition of energy systems to tackle the climate crisis. To make energy research software (ERS) more findable, it should be described with metadata following the FAIR (findable, accessible, interoperable, and reusable) principles and be registered in a common registry. To this end, we motivate and present a concept for a metadata-based registry for ERS which should enable researchers to easily add new ERS as well as to find new ERS