Research Projects
Smart Energy
The energy transition and increasing sector coupling pose major challenges for energy system research. In this context, digitization processes towards cyber-physical energy systems (CPES) facilitate the transformation in many ways and have an equal impact on technical, social and societal issues, but also on the research process itself. Research efforts on CPES rely heavily on model- and (co-) simulation-based approaches. In this context, tracking data and models is a complex challenge that needs to be addressed in each research project. These challenges are addressed by nfdi4energy throughout the research and transfer cycle of projects in energy system research: from identifying partners with relevant competencies and knowledge for a project, to formulating research proposals and experiments, to identifying and coupling methods, models and data, to preparing results for publication, to identifying follow-up activities.
In the Nuremberg Metropolitan Region, the restructuring of the energy supply makes a decisive contribution to achieving the Paris climate targets. The use of renewable energies makes it possible to reduce dependence on fossil energy sources and to embark on a sustainable, environmentally conscious path. However, the interconnectedness of urban and rural areas complicates the evaluation of options for action and may affect the active participation of political actors, business enterprises and citizens.
The simulation tool developed as part of the Klimapakt2030plus project supports decision-makers and stakeholders in implementing the energy transition with the help of a comprehensive energy system model. It enables the analysis of interactions between energy sources, storage options and consumption patterns, taking into account constraints such as grid infrastructure and regional conditions. By illustrating the impact of policy measures on the dynamics of energy supply, the tool closes the gap between policy goals and practical implementation.
(Own Funds)
Abstract:
Today's computer technology supports researchers and scientists in developing their complex ideas and innovative technologies. The use of such new ideas and technologies in an increasingly complex overall technical and ecological system will be examined in this project. These can be production systems, transport systems, computer networks, smart grids, or even a combination of such systems.
The modeling and analysis of such complex systems is supported by powerful data structures and algorithms, which enable the use of common PCs for the calculations. For example, data structures such as Multi-Valued Decision Diagrams (MDDs), analytical methods from queuing theory, hybrid simulation, Mixed-Integer Linear Programming (MILP), and combinations tailored to the system are used.
(Own Funds)
Abstract:
The expansion of renewable energy sources and the growing share of decentralized and highly fluctuating energy producers pose complex challenges for modern energy systems. Storage systems such as CHP systems with heat storage, pure electricity storage, or other technologies also play a decisive role. Furthermore, communication between producers, consumers, and storage as well as the intelligent control of electricity producers and consumers is crucial for the stability and efficiency of the energy system.
The aim of the project is the development of methods and tools for the comprehensive analysis of the increasingly renewable energy-based energy industry at the level of individual houses and smart grids. As part of the project, the simulation framework i7-AnyEnergy is being developed, which enables the rapid development of hybrid simulation models of networked intelligent energy systems. For this purpose, methods such as discrete event simulation (e.g., for consumer, weather, and control models) and system dynamics models (e.g., for energy and cost flows) are combined in a simulation model. The simulation framework i7-AnyEnergy provides basic components for the energy consumption (electrical and thermal), for energy production (eg gas heating, combined heat and power with fuel cells), for renewable energy (photovoltaic), for energy storage (batteries, chemical storage such as based on LOHC), as well as for the control. These components are used to create house models that can be coupled to smart grid models with a common weather model and a communication Network.
(Own Funds)
Abstract:
The expansion of renewable energy sources and the growing share of decentralized and highly fluctuating energy producers pose complex challenges for modern energy systems. Storage systems such as CHP systems with heat storage, pure electricity storage, or other technologies also play a decisive role. Furthermore, communication between producers, consumers, and storage as well as the intelligent control of electricity producers and consumers is crucial for the stability and efficiency of the energy system.
The aim of the project is the development of methods and tools for the comprehensive analysis of the increasingly renewable energy-based energy industry at the level of individual houses and smart grids. As part of the project, the simulation framework i7-AnyEnergy is being developed, which enables the rapid development of hybrid simulation models of networked intelligent energy systems. For this purpose, methods such as discrete event simulation (e.g., for consumer, weather, and control models) and system dynamics models (e.g., for energy and cost flows) are combined in a simulation model. The simulation framework i7-AnyEnergy provides basic components for the energy consumption (electrical and thermal), for energy production (eg gas heating, combined heat and power with fuel cells), for renewable energy (photovoltaic), for energy storage (batteries, chemical storage such as based on LOHC), as well as for the control. These components are used to create house models that can be coupled to smart grid models with a common weather model and a communication Network.
(Third Party Funds Group – Overall project)
Abstract:
Germany decided to reorganize its energy supply system in a sustainable way by initiating the energy transition (Energiewende). One of its main targets is to be one of the most environmentally friendly and energy-conserving economies worldwide with competitive energy prices at the same time. This requires the support of all-embarrassing analytical systems, which take into account the technical, market and regulatory framework at once. Existing energy system analysis models often neglect or simplify the modeling of the electrical grid, which motivated the preliminary multidisciplinary work of the chairs of the FAU Erlangen-Nürnberg in the recent years.
A holistic system-oriented modeling approach for the electrical power supply system in Germany was initially developed with a focus on Bavaria. The model of the German electrical power supply system includes the transmission grid, conventional power plants and feed-in from renewables concerning the current market mechanisms in Germany. With the developed model it is possible to derive statements about grid and storage expansion or the development of CO2 emissions for the federal state Bavaria. The overall model includes sub-models for optimization (determination of cost-optimal expansion scenarios), for simulation (stochastic simulation of different scenarios with high temporal resolution and technical detail) and grid analysis (quasi-stationary AC load flow calculations) for checking the required grid planning criteria and stable system operation.
Within the research project KOSiNeK funded by the Federal Ministry for Economic Affairs and Energy (BMWi) we now extend the existing holistic system-oriented modeling approach for the German electric energy system to derive statements about the future development of the system within the European context. This includes both the evaluation of net expansion scenarios and the simulation and analysis of regulatory frameworks. In order to cope with the increasing complexity of the problem, new approaches from the fields of mathematics, computer sciences and net analysis are necessary, which includes aggregation and decomposition techniques, hierarchical multipoint model approaches as well as probabilistic methods to determine the probability of occurrence of certain conditions. This leads to models of high complexity. To take this into account, the approaches from mathematics, computer science and grid analysis will also be coupled iteratively. This enables displaying technical and economic aspects with regard to the control of power plants in a very detailed manner as well as considering grid-regulations in order to guarantee a safe electrical power supply. In addition, it is possible to examine energy markets in an European context including their regulatory framework. The flexible and component-based model construction allows the influence of new market mechanisms such as dividing Germany into price zones or changing market conditions or funding mechanisms with a detailed, agent-based market model. For the integrated power grid analysis, the continental European transmission grid is integrated by network equivalents. A novel probabilistic approach will also be developed to evaluate the grid expansion scenarios.
The project KOSiNeK (project number 03ET4035) is funded by the 6th energy research program of the German Federal Ministry for Economic Affairs and Energy (BMWi).