Battery Energy Storage Systems: Data-Driven Optimization for a New Utility Asset Class
This e-book reveals how utilities can use predictive battery analytics to enhance BESS performance, reduce operational risk, and maximize the value of their energy storage assets.
- How predictive analytics improves battery state of charge (SOC) accuracy and reduces unplanned downtimes.
- Why relying solely on a Battery Management System (BMS) leaves blind spots, and how to close them.
- Best practices for warranty compliance and performance contract management using independent monitoring.
- How to build a compelling business case for investing in analytics-driven energy storage operations.
Energy storage asset operators face challenges in accurately understanding the health, performance, and availability of their battery systems. Traditional tools like Battery Management Systems often fall short in detecting early signs of degradation or safety risks, leading to unplanned downtimes and increased operational costs. Managing complex warranties and performance contracts adds further pressure, especially as battery portfolios grow in size and diversity. Predictive analytics addresses these issues by providing deep, actionable insights that enable proactive maintenance, risk mitigation, and optimized performance across the entire battery fleet.