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Impact of Renewable Energy Expansion to the Balancing Energy Demand of Differential Balancing Groups
(2018)
The research addresses the present situation on the German electricity market caused by variable renewable energy sources. The increasing number of households with photovoltaic and battery storage systems and their impacts require special attention. These systems change the traditional electricity customer from the sole electricity consumer to an electricity producer and consumer in one person. These so-called prosumers differ in their actual electricity demand from the initially estimated electricity demand with standard load profile. This discrepancy results in deviations within a differential balancing group. Thereby, the main finding of this research is a significant higher balancing energy demand with the expansion of photovoltaic and battery storage systems. Hence, the standard load profile is particularly not suitable for differential balancing groups with a high penetration of solar systems and still less suitable for groups with solar and battery storage systems
Artificial intelligence and design of experiments for resource adequacy assessment in power systems
(2024)
Germany’s national climate protection policy, the German Energy Transition, is oriented towards the reduction of energy-related greenhouse gas emissions by rapidly expanding the share of renewable energy systems. New challenges arise regarding technical and energy economical integration as installed wind and photovoltaic power capacities increase continuously. This thesis contributes to the topic by introducing a framework for online multi-criteria flexibility allocation in electrical distribution networks with transport capacity limitations. It considers technical aspects and market participant interests that may contradict each other. Local master data is preprocessed using geospatial information of buildings, photovoltaic systems, wind turbines, and the human population within a spatial domain of interest. By combining weather forecast data, this establishes the foundation for predicting power flow in the electrical distribution network and generating grid-beneficial criteria utilizing the smart grid traff.