Fuzzy Soft Set-Based Decision-Making for Economic Evaluation of Battery Energy Storage in Solar Photovoltaic Systems: A Systematic Literature Review

Economic evaluation of Battery Energy Storage Systems (BESSs) integrated with solar photovoltaic (PV) systems requires the consideration of financial performance, operational behavior, battery degradation, reliability, and uncertainty. This PRISMA-based systematic review synthesizes mathematical and decision-making approaches relevant to Fuzzy Soft Set-based PV–BESS evaluation. Searches in Scopus, ScienceDirect, SpringerLink, and Taylor & Francis Online identified 789 records published between 2015 and 2026, and 74 studies were included. All studies were coded by theme, method, and economic and technical criteria, while 15 representative studies were analyzed at the equation level. Six model families were identified: techno-economic valuation, multi-objective planning, operational energy management, reliability assessment, fuzzy and multi-criteria decision-making, and degradation-aware optimization or control. Most studies appeared in 2024–2026 (57/74; 77.0%), while keyword analysis highlighted decision making and battery storage. Common formulations included NPV, NPC, LCOE, IRR, payback period, market revenue, battery capacity fade, equivalent full cycles, degradation cost, LPSP, LOLE, EENS, Monte Carlo simulation, and fuzzy ranking methods. These components remain fragmented across separate frameworks. Fuzzy Soft Set is therefore positioned as a potential parameterized decision-support layer for integrating heterogeneous outputs, subject to further theoretical development and empirical validation. This direction is relevant to Sustainable Development Goal 7 (Affordable and Clean Energy).