How is optimal dispatch determined for grid-scale battery storage?

Optimal dispatch maximizes revenue or value considering: energy arbitrage (buy low, sell high), ancillary services (frequency regulation, reserves), capacity markets, demand charge reduction, and renewable firming. Optimization methods: rule-based (simple thresholds), model predictive control (rolling optimization horizon), and machine learning (learn patterns). Inputs include: price forecasts, load forecasts, renewable forecasts, and storage state. Constraints: power limits, energy capacity, state-of-charge bounds, and degradation (each cycle has cost). Co-optimization across multiple revenue streams requires understanding market rules and priorities. Uncertainty handling through stochastic optimization or robust approaches.