Improve BESS Performance Through Enhanced State-of-Charge Estimation: The Case for Probabilistic Cloud-Based Battery Analytics

Key Takeaways:

• Unlocking confidence in usable capacity can increase returns by up to 10%.
• Costly penalties from System Operators can be avoided.
• The volume of tradeable energy can be significantly increased by tracking dynamic uncertainty in State-of-Charge (SOC).

 

The Evolving Role of BESS in Energy Markets

Rapid advancements in LFP battery manufacturing have significantly lowered costs, making utility-scale Battery Energy Storage Systems (BESS) an increasingly critical component of modern electricity networks. BESS not only provide essential grid stability services but also enable a higher share of renewable generation in the energy mix. The primary revenue streams for BESS in most liberalised energy markets are built on a combination of energy arbitrage, grid stability services (such as frequency response and reserve services), and capacity market services. Effective delivery of any of these services requires an accurate determination of the present and forecasted State-of-Charge (SOC). However, the widespread use of SOC estimates that are solely derived from the Battery Management System (BMS) can introduce significant errors due to the inherent uncertainty in the techniques used. When trading energy, this can mean that at the point of delivery there is insufficient energy remaining in the BESS to deliver on its obligations. If SOC estimations fail in grid stability services, assets may be unable to provide the necessary energy, resulting in...