Energy Management System Dispatch Strategies
Simulate, compare, and optimize how your hybrid energy system operates. Rule-Based and Economic LP dispatch — each modeled over 219,000 timesteps across 25 years.
Two Strategies, One Platform
Energy Optima models both major EMS dispatch approaches used by commercial microgrid controllers from ABB, Schneider Electric, and Siemens. Your dispatch strategy choice can change project economics by 10-15%.
Strategy 1
Rule-Based Dispatch
Deterministic priority list: PV → Wind → Battery → Grid → Diesel. Fixed rules executed in order at every timestep. The dominant approach in deployed microgrids worldwide.
- Decision logic maps directly to PLC code
- DG preemptive activation with configurable SOC thresholds
- Startup delay modeled accurately (2-5 min diesel warm-up)
- Best for: first-time teams, reliability-first projects, no forecasting infra
Strategy 2
Economic LP Dispatch
Linear programming optimization that minimizes total electricity cost over a rolling 24-hour horizon. Solves for optimal battery charge/discharge, grid import/export, and diesel scheduling at every timestep.
- Degradation-aware: won't cycle battery for small price spreads
- MPC rolling horizon — re-optimizes every 30 minutes
- Terminal SOC value prevents horizon-end battery drain
- Best for: >1 MW projects, TOU tariffs, professional operators
How the EMS Engine Works
Energy Optima's simulation engine includes a full EMS model — the same decision logic that a real PLC or industrial microgrid controller would execute. Click each section to see the technical approach.
Deterministic Priority Dispatch
Rule-Based dispatch follows a fixed priority list at every timestep. It is the simplest and most predictable strategy — and the most widely deployed in commercial microgrid controllers worldwide.
How it works: At each hour, the EMS calculates available PV and wind from weather data, subtracts the load demand, and applies the priority chain:
- Surplus (generation > load): Charge battery first, then export to grid, then curtail
- Deficit (load > generation): Discharge battery first, then import from grid, then start diesel
DG Preemptive Activation: When battery and diesel coexist, the diesel doesn't wait until the battery is empty. Two SOC thresholds control this:
- Activation SOC (e.g., 15%): When battery drops below this, diesel starts warming up
- Deactivation SOC (e.g., 40%): When diesel has charged battery back to this level, it stops
This prevents the "1-hour blackout" problem where diesel needs 2-5 minutes to start but there's no battery reserve left to bridge the gap.
Real-world mapping: Rule-based dispatch directly translates to PLC code. If you program a Schneider Electric EcoStruxure, ABB Ability MGS, or Siemens MGMS controller with the same priority list and SOC thresholds, you get the same behavior.
Linear Programming Optimization
Economic Dispatch solves a mathematical optimization problem at every timestep — minimizing total electricity cost over a configurable planning horizon (typically 24 hours) while respecting all system constraints.
What the LP decides for each hour:
P_charge[t]— Battery charging power (kW)P_discharge[t]— Battery discharging power (kW)P_import[t]— Grid import power (kW)P_export[t]— Grid export power (kW)P_diesel[t]— Diesel generation power (kW)SOC[t]— Battery state of charge
What the LP minimizes:
Minimize: Total Cost = Grid Import Cost
- Grid Export Revenue
+ Battery Degradation Cost
+ Diesel Fuel Cost
+ Unmet Load Penalty (high, last resort)
- Terminal SOC Value (option value of stored energy)Degradation-Aware Optimization: The LP factors in battery wear cost — calculated from battery CAPEX and warranty cycles:
degradation_cost = battery_capex / (2 × warranty_cycles)
Example: $300/kWh / (2 × 5000 cycles) = $0.030/kWh per full cycleThis means the LP won't cycle the battery for a $0.01/kWh arbitrage opportunity if the degradation cost is $0.03/kWh. It actively protects the battery while maximizing financial returns.
Terminal SOC Value: Without a terminal value, the LP would drain the battery at horizon end. Energy Optima assigns a value to stored energy based on diesel fuel cost — the "option value" of having energy available for future uncertainty.
Dynamic Power Constraints (DPC): Battery power capability changes with SOC. At 90% SOC, a battery can't accept full charge power (CC→CV transition). Energy Optima's DPC model captures this:
P_charge[t] ≤ P_rated × (0.6 + 0.4 × (1 - SOC[t])) × SOH
P_discharge[t] ≤ P_rated × (0.6 + 0.4 × SOC[t]) × SOHValidated against published research (arXiv:2403.16821), achieving 93% reduction in constraint violations compared to fixed power limits.
Manufacturer-Specific Degradation
Most tools use a simple linear model: "battery degrades 2% per year." This is wildly inaccurate. Energy Optima uses manufacturer-specific degradation tables — 13,260 data points across 85 real battery products.
How it works: Each battery has 156 data points covering 26 years, 3 C-rates (0.25C, 0.33C, 0.5C), and 2 cycle frequencies. The simulation performs 3D linear interpolation at every timestep to find exact SOH and DC RTE values for current operating conditions.
Why this matters for EMS:
- Power capability degrades: A battery at 85% SOH can only deliver 85% of its original power. The EMS must account for this in dispatch decisions.
- Efficiency degrades: DC round-trip efficiency drops over time (e.g., 95% → 88%), changing the economic calculus for every cycle.
- Lifecycle cost accuracy: The difference between a battery cycled at 0.25C once daily vs 0.5C twice daily can be 10+ years of usable life. Your EMS strategy determines which path you take.
Battery Augmentation: When SOH drops below a user-defined threshold (e.g., 80%), Energy Optima can model adding capacity. The simulation tracks per-generation assets with PCS matching, mirroring real-world augmentation contracts offered by CATL, BYD, and Samsung SDI.
Closing the Simulation-to-Reality Gap
The LP solves a linearized model of the system. Real batteries are nonlinear. Energy Optima's execution validation loop bridges this gap — the same approach used by commercial MPC controllers from ABB and Siemens.
The validation loop:
- LP solver produces optimal dispatch plan using linear constraints
- Dispatch plan is checked against the real nonlinear battery model (CC-CV curves, voltage sags, SOH-adjusted limits)
- If the plan violates real-world constraints, corrected limits are fed back to the LP
- LP re-solves with updated constraints — iterates up to 3 times
- Target: less than 0.1 kW gap between LP plan and what the real battery can deliver
This eliminates the gap between "what the optimizer planned" and "what the hardware can actually do" — a gap that can cost millions in missed energy over 25 years.
Choose the Right Dispatch Strategy
Two identical systems with different dispatch strategies — or even different SOC thresholds — can have 10-15% difference in lifetime savings. Here's how to choose.
| Criteria | Rule-Based | Economic LP |
|---|---|---|
| Best project size | All sizes, especially <1 MW | >1 MW |
| Forecasting required | No | Yes (PV/load/price) |
| Grid tariff type | Flat or simple TOU | TOU, demand charges, market participation |
| Operator expertise | Low — predictable behavior | High — optimization tuning |
| Primary concern | Reliability, simplicity | Cost minimization |
| Simulation-to-reality match | 85-90% (limited by forecast error) | 70-80% (with good forecasting) |
| Commercial EMS products | Schneider EcoStruxure, ABB MGS, Siemens MGMS | ABB OPTIMAX, Schneider Wonderware, Fluence Mosaic |
Where Energy Disappears — The Full Loss Chain
Every stage of the power path incurs losses. Energy Optima models all seven stages — if you ignore a 2% transformer loss, over 25 years that's millions of kWh of "missing" energy.
Charge Path (AC Bus → Battery)
Discharge Path (Battery → AC Bus)
Additionally, SKID-type PCS units with integrated step-up transformers are modeled with separate transformer efficiency (η ≈ 99.5-99.8%). Auxiliary power (BMS, HVAC, fire suppression) is modeled per-component from manufacturer data — 5 load points × 3 temperatures per battery.
Configure Your EMS Strategy in Minutes
Compare Rule-Based and Economic LP dispatch side-by-side. See which strategy delivers better economics for your tariff structure, load profile, and system configuration — all before a single component ships.
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