Schrage, Rico and Tiemann, Paul Hendrik and Niesse, Astrid
SIGENERGY Energy Inform. Rev.
The distributed schedule optimization of energy storage constitutes a challenge. Such algorithms often expect an input set containing all feasible schedules and, therefore, require searching the schedule space efficiently. However, 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. Two 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 with respect to multiple criteria. It is shown that the presented approach is suitable to schedule electric energy storage in actual households and industries with different generator and storage types.
feb / 2023
Association for Computing Machinery
MIRAGE Multi-Purpose Battery Storage Swarm SiNED Systemdienstleistungen für sichere Stromnetze in Zeiten fortschreitender Energiewende und digitaler Transformation