BESS Simulator

Revenue minus degradation cost, per module

Not all dispatch days are profitable after degradation cost. This simulator computes net P&L at module resolution using real market data, empirical degradation models, and full settlement.

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Simulation Output

Revenue, degradation, and thermal profile per module

Each simulation produces a complete P&L with per-module detail for every hour in the window.

Revenue

  • Day-ahead energy arbitrage
  • Real-time market boost
  • Ancillary services: capacity + mileage
  • Full settlement per stream

Degradation

  • Calendar + cycle aging degradation model
  • Per-module capacity degradation tracking
  • Revenue vs degradation tradeoff
  • Degradation cost in dollars per cycle

Module Simulation

  • IR-based current splitting across modules
  • Thermal simulation per module
  • SOC tracking with BMS constraints
  • Voltage with hysteresis + IR drop

Under The Hood

What the simulator computes

Each simulation runs the full market and battery model stack on every module in the fleet.

Revenue Engine

  • DAM schedule optimization
  • Real-time price spike detection and boost
  • AGC signal simulation for frequency regulation
  • Capacity + mileage settlement
  • Energy arbitrage settlement (DAM S1 + RTM S2)

Battery Model

  • Degradation modeling (calendar + cycle aging)
  • IR-based current distribution per module
  • Thermal model per module with weather data
  • 6th-order OCV polynomial + hysteresis
  • BMS limit enforcement with regulation headroom

Revenue-Degradation Optimization

Finding the dispatch days that actually make money

Dispatching every day maximizes gross revenue. But some days cost more in degradation than they earn. The simulator identifies the knee point where marginal revenue per marginal degradation flattens.

The problem

Every dispatch cycle degrades the battery. That degradation has a dollar cost: capacity degradation percentage times capex per kWh. Low-revenue days can be net negative after this cost. Dispatching all days leaves money on the table.

The approach

Days are sorted by revenue-to-degradation ratio. Plotting cumulative revenue against cumulative degradation cost reveals a knee point: above it, dispatch is efficient. Below it, returns are diminishing.

The output

Net P&L per day after degradation cost. Which days to dispatch and which to skip. The optimal operating point that maximizes profit over the simulation window, not just gross revenue.

Get Started

Run a simulation on your project

Enter your market, battery configuration, and capacity allocation. Results are delivered as a detailed P&L report.

Start in the Copilot

Or email hello@amperical.ai with your specs