2022/08/15 by Rico Schrage, Schrage, Rico, Paul Hendrik Tiemann +3 · 1 citation
Engineering · #Smart Grid Energy Management #Microgrid Control and Optimization #Optimal Power Flow Distribution
paper · pdf · doi:10.48550/arxiv.2208.07185
The distributed schedule optimization of energy storage constitutes a challenge. Such algorithms often expect an input set containing all feasible schedules or respectively require to efficiently search the schedule space. 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. Three 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. Third, the algorithm is extended to include an arbitrary local criterion. It is shown that the presented approach is suitable to schedule electric energy storage in real households and industries with different generator and storage types.