2020/05/19 by Fabian Scheller, Robert Burkhardt, Robert Schwarzeit +3
Computer Science · Economics, Econometrics and Finance · Engineering · #Business #Competition (biology) #Demand side #Economics #Electric Vehicles and Infrastructure #Electrical engineering #Electricity #Electricity demand #Electricity generation #Electricity system #Energy storage #Engineering #Environmental economics #Flexibility (engineering) #Industrial organization #Microgrid Control and Optimization #Natural resource economics #Power (physics) #Smart Grid Energy Management #cs.SY #econ.GN #eess.SY #q-fin.EC
paper · pdf · doi:10.1016/j.apenergy.2020.114969
published as Applied Energy, Volume 269, 2020, 114969
openalex publication_date 2020/05/19 · arxiv created 2020/11/11 · arxiv updated 2020/11/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Community electricity storage systems for multiple applications promise benefits over household electricity storage systems. More economical flexibility options such as demand response and sector coupling might reduce the market size for storage facilities. This paper assesses the economic performance of community electricity storage systems by taking competitive flexibility options into account. For this purpose, an actor-related, scenario-based optimization framework is applied. The results are in line with the literature and show that community storage systems are economically more efficient than household storage systems. Relative storage capacity reductions of community storage systems over household storage systems are possible, as the demand and generation profiles are balanced out among end users. On average, storage capacity reductions of 9% per household are possible in the base case, resulting in lower specific investments. The simultaneous application of demand-side flexibility options such as sector coupling and demand response enable a further capacity reduction of the community storage size by up to 23%. At the same time, the competition between flexibility options leads to smaller benefits regarding the community storage flexibility potential, which reduces the market viability for these applications. In the worst case, the cannibalization effects reach up to 38% between the flexibility measures. The losses of the flexibility benefits outweigh the savings of the capacity reduction whereby sector coupling constitutes a far greater influencing factor than demand response. Overall, in consideration of the stated cost trends, the economies of scale, and the reduction possibilities, a profitable community storage model might be reached between 2025 and 2035. Future work should focus on the analysis of policy frameworks.