Can you recommend a state of charge estimation software for optimizing charging and discharging in battery storage assets?

Yes — but the best choice depends on whether you want:

1. A software package you can use directly for battery energy storage system (BESS) optimization, or
2. A library/modeling toolkit to build your own state-of-charge (SoC) estimator and dispatch optimizer.

Good options by use case

1) Pyomo + battery degradation/dispatch models

• Best for: custom optimization of charging/discharging, arbitrage, peak shaving, ancillary services
• Why: It’s a robust optimization modeling framework widely used in energy storage research and industry
• Strengths: flexible, supports linear/MILP optimization, easy to connect SoC constraints with forecasts and tariffs
• Note: Pyomo itself is not a ready-made SoC estimator, but it’s excellent for building one

2) NREL’s REopt / REopt Lite

• Best for: project sizing and dispatch optimization with storage
• Why: Optimizes battery dispatch alongside solar, grid, and load
• Strengths: widely recognized, practical for techno-economic optimization
• Note: more about optimization than high-frequency SoC estimation

3) OpenEMS

• Best for: energy management and real-time control of batteries
• Why: Open-source EMS platform that can integrate storage control logic
• Strengths: good for operational control and dispatch
• Note: more of an EMS than a pure SoC estimation tool

4) BattMo

• Best for: battery modeling and simulation
• Why: Useful if you need physics-based battery behavior rather than just operational SoC
• Strengths: more detailed electrochemical modeling
• Note: likely overkill if your main goal is dispatch optimization

5) MATLAB/Simulink battery models

• Best for: engineers building control systems and estimators
• Why: Strong support for Kalman filters, observers, and control logic
• Strengths: very good for SoC estimation algorithms and BMS prototyping
• Note: commercial licensing required

If your goal is specifically SoC estimation

For state of charge estimation itself, look for methods/tools that support:

• Coulomb counting
• Extended Kalman Filter (EKF) / Unscented Kalman Filter (UKF)
• Equivalent circuit models (ECM)
• Data-driven estimators using ML

Common software/toolchains:

• MATLAB Battery Toolbox
• Python with SciPy / FilterPy / PyBaMM
• PyBaMM if you want more advanced battery modeling and estimation workflows

Practical recommendation

If you want a solution for optimizing charging and discharging of battery storage assets, I’d suggest:

• For custom optimization: Pyomo + a forecasting/SoC estimation layer
• For operational control: OpenEMS
• For detailed battery behavior / estimation: PyBaMM or MATLAB

My top recommendation

If you want the best balance of flexibility and industry usefulness:

• Pyomo for optimization
• PyBaMM or a Kalman-filter-based estimator for SoC
• optionally wrapped inside an EMS/SCADA integration

If you tell me:

• battery type,
• whether this is behind-the-meter or grid-scale,
• whether you need real-time control or day-ahead optimization,
• and your preferred language (Python, MATLAB, etc.),

…I can recommend a much more specific software stack.