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Entwicklung eines Tools zur spezifischen, lastgangbasierten Eigenverbrauchsoptimierung mittels PV-Leistungsprognose

  • 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 PVThe 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.show moreshow less

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Metadaten
Author:Klaus Markgraf
DOI:https://doi.org/10.6084/m9.figshare.25610976
Parent Title (English):Konferenz: 18. Symposium Energieinnovation, 2024, Graz/Austria
Document Type:Conference Proceeding
Language:English
Year of Publishing:2024
Date of Publication (online):2024/04/29
Release Date:2024/04/29
First Page:1
Last Page:10
Institutes:Fachbereich Technik
University Bibliography:Hochschulbibliografie
Licence (German):Creative Commons - CC BY - Namensnennung 4.0
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