Optimization of Battery Energy Storage Systems for Prosumers and Energy Communities Under Capacity-Based Tariffs

The transition toward capacity-based network tariffs shifts the primary role of battery energy storage systems (BESS) from traditional energy arbitrage to active peak shaving. This paper presents a mixed-integer linear programming (MILP) optimization model for the co-optimization of both BESS size and operation scheduling for multiple prosumers operating individually and within energy community (EC). The model accounts for battery cyclic degradation and reduces the state of health (SOH) over the project lifetime. The framework is evaluated by a comprehensive techno-economic analysis of BESS integration under Slovenia’s multi-block tariff structure. The results demonstrate that while individual distributed BESS integration is highly profitable, centralized EC BESS financially underperforms. Because centralized BESS cannot directly reduce individual contracted power limits, its profitability relies on energy arbitrage, making the initial investment and double grid fees the primary barriers. Conversely, integrating distributed storage with peer-to-peer (P2P) trading minimizes the required BESS capacity while maintaining profitability. The evaluation also reveals that ECs do not automatically act as socio-economic equalizers, indicated by a stable Gini coefficient. However, a break-even analysis reveals the necessary reduction in capital costs to overcome these hurdles, confirming the strong future viability of centralized EC BESS.