2017/10/31 by Leander Kotzur, Peter Markewitz, Martin Robinius +1 · 1 citation
Engineering · Mathematics · #Computer science #Electrical engineering #Energy (signal processing) #Energy storage #Engineering #Industrial engineering #Integrated Energy Systems Optimization #Mathematical optimization #Mathematics #Power (physics) #Process Optimization and Integration #Renewable energy #Series (stratigraphy) #Smart Grid Energy Management #Statistics #Superposition principle #Term (time) #math.OC
paper · pdf · doi:10.1016/j.apenergy.2018.01.023
Submitted to Applied Energy
openalex publication_date 2018/01/28 · arxiv created 2018/01/31 · arxiv updated 2018/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The optimization-based design of renewable energy systems is a computationally demanding task because of the high temporal fluctuation of supply and demand time series. In order to reduce these time series, the aggregation of typical operation periods has become common. The problem with this method is that these aggregated typical periods are modeled independently and cannot exchange energy. Therefore, seasonal storage cannot be adequately taken into account, although this will be necessary for energy systems with a high share of renewable generation. To address this issue, this paper proposes a novel mathematical description for storage inventories based on the superposition of inter-period and intra-period states. Inter-period states connect the typical periods and are able to account their sequence. The approach has been adopted for different energy system configurations. The results show that a significant reduction in the computational load can be achieved also for long term storage-based energy system models in comparison to optimization models based on the full annual time series.