Unlocking the full value of battery storage: Fuse-constrained, multi-service stacking and peak shaving in a unified optimization frameworkShow others and affiliations
2026 (English)In: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 141, article id 119458Article in journal (Refereed) Published
Abstract [en]
Battery energy storage systems enhance grid flexibility by enabling participation in frequency containment reserves (FCR), day-ahead (DA), and peak shaving (PS) markets—each with distinct operational and economic rules. Yet, operators face a key challenge: how to stack services without compromising reliability or lifespan? This study presents a unified mixed-integer linear programming framework for optimal multi-service stacking, rigorously integrating technical constraints — including real-world fuse limits and battery degradation — alongside market participation requirements. Uniquely, the model balances both droop-based and energy-based FCR participation, precise day-ahead market trading, and behind-the-meter cost management, all while tracking the interplay of physical and regulatory boundaries. The framework is tested using real industrial data from Sweden, under the coordinated rules of Svenska kraftnät. Results reveal that holistic co-optimization is not just a theoretical ideal but a practical economic lever: stacking services increases net profit by about 83% compared to the single-market strategy (DA). This highlights the need for a holistic approach that manages state of energy (SoE), degradation, and fuse limits. The analysis shows that moderate relaxations in fuse limits boost revenue, but benefits plateau, suggesting that reasonable sizing captures most economic gains without costly upgrades to fuses or grid infrastructure.
Place, publisher, year, edition, pages
Elsevier BV , 2026. Vol. 141, article id 119458
Keywords [en]
Battery energy storage systems, FCR market, Fuse limit, MILP optimization, Peak shaving, Battery management systems, Battery storage, Commerce, Constrained optimization, Cost benefit analysis, Integer linear programming, Mixed-integer linear programming, Secondary batteries, Day-ahead, Frequency containment reserve market, Multi-services, Optimisations, Peak-shaving, Reserve markets, Stackings, Digital storage
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:mdh:diva-74555DOI: 10.1016/j.est.2025.119458ISI: 001621581000001Scopus ID: 2-s2.0-105021475491OAI: oai:DiVA.org:mdh-74555DiVA, id: diva2:2016662
2025-11-262025-11-262025-12-03Bibliographically approved