TY - CHAP A1 - Markgraf, Klaus A1 - Dietrich, Benjamin A1 - Müller, Katja A1 - Flassig, Robert J A1 - Flassig, Peter Michael T1 - FINEconcepts - Wissenstransfer und Energiesystemoptimierung mithilfe des digitalen Zwillings T2 - Konferenz: NWK 2023, HS Harz N2 - Climate change, but also geopolitical circumstances, are moving topics such as energy efficiency and renewable energies more and more into the focus of the population, economy , and politics. As a result, the will to optimize new and existing energy systems extends from private individuals to companies and even entire communities. This work describes the development and usage of a new software called FINEconcepts which creates a digital twin of an energy system. This virtual model can then be used to optimize the energy system based on annual costs, CO2 emissions or other relevant criteria such as self-sufficiency. Because all system components, which include renewable technologies as well, can be added as a building block with chosen but changeable parameters, the software allows the user to explore and awaken interest and understanding of technologies that were previously considered too costly, irrelevant, or unrealistic. Implemented projects in small and large companies as well as in residential areas did prove, that the usage of FINEconcepts leads not only to more efficient energy systems by increasing the use of renewable energy, but also increased knowledge and understanding in terms of energy. Besides economics, ecology and security, understanding is an equally important factor in achieving a sustainable energy supply. Y1 - 2023 SP - 428 EP - 435 ER - TY - CHAP A1 - Markgraf, Klaus T1 - Entwicklung eines Tools zur spezifischen, lastgangbasierten Eigenverbrauchsoptimierung mittels PV-Leistungsprognose T2 - Konferenz: 18. Symposium Energieinnovation, 2024, Graz/Austria N2 - The German government's initiative to cover 80% of the gross electricity supply with renewable energies by 2050 brings considerable ecological benefits, but also poses several challenges. One of these challenges is the growing number of photovoltaic systems (PV systems), which, due to their high feed-in power, already pose a risk to the security of the electricity distribution grid during long periods of sunny weather. To counteract this, active research is being carried out in the field of PV power forecasting. This research is primarily aimed at providing the grid operator with a predicted power output, which enables a longer planning horizon and thus increases the operational grid security. However, the considerable annual electricity consumption of private households and the increasing spread of PV systems for self-consumption show that the energy behavior of households, especially self-consumption, also influences grid security. Additionally, households have an incentive to boost their self-consumption because the cost of drawing each kilowatt-hour from the grid is substantially higher than the compensation received for injecting an equivalent amount of energy back into the grid. However, as of now, there is no software available that easily enables households to tailor the usage patterns of their electrical appliances according to a photovoltaic (PV) forecast. The project described here aims to close this gap by creating such software. Various PV forecasting models are used and tested for their suitability for this purpose. A self-generated optimization process is implemented in this project to optimize the consumer configuration based on the PV forecasts. The here-developed tool enables the user to enter parameters for his PV system and the specific load profiles of his electrical appliances. Based on this data, the optimization algorithm determines a consumption plan with a forecast horizon until the end of the next day that maximizes the user's self-consumption. To validate the tool, the optimization process is carried out over a period of 60 days using a predefined scenario and the results are compared with a scenario in which the electrical appliances are intuitively operated at midday. The analysis of these results ultimately shows the potential impact of such a tool on the economic efficiency of private households and the supply stability. Y1 - 2024 U6 - https://doi.org/10.6084/m9.figshare.25610976 SP - 1 EP - 10 ER -