EnexaEMS Simulator v1.0
Simulation Overview
  • Input SummaryAll configuration parameters
  • Simulation AlgorithmsReactive vs Smart EMS explained
  • Result OverviewSide-by-side comparison
Configuration
  • Location SetupEquipment specs & constraints
  • FinancialsCosts, income & margins
  • Solar ProductionPV generation profile
  • Charging SessionsEV demand profile
  • Not ModeledKnown gaps & limitations
  • SmartEMS ConfigPlanner tuning parameters
Reactive BMS
  • BMS AlgorithmHow the reactive BMS works
  • BMS ReactiveRule-based simulation results
SmartEMS
  • SmartEMS AlgorithmHow the 2-layer optimizer works
  • SmartEMS ResultsOptimized simulation output

Not Modeled

What this simulation does not model -- known gaps and simplifications before optimization

11 known limitations identified

This simulation models energy flows, battery cycling, PV production, and hourly price arbitrage for a single ADS-TEC CP320 ChargePost on a typical summer Saturday. The following factors are not yet included in the financial model. They should be considered when interpreting results and before using the optimizer output for investment decisions.

3 Critical3 Significant5 Minor
Critical

Missing cost/revenue factors that materially affect the P&L

Battery Round-Trip Efficiency Not Modeled
Critical
The simulation assumes every kWh stored in the battery comes back out at 100% efficiency. In reality, AC-DC conversion, DC-DC conversion, and thermal losses reduce round-trip efficiency (RTE) to 85-90% for LFP/NMC battery systems. The ADS-TEC ChargePost has an integrated DC-coupled battery, which avoids one AC-DC conversion stage (better than AC-coupled BESS), but still has DC-DC conversion losses in the battery management system.

Estimated Impact

With ~300 kWh daily battery throughput and 88% RTE, approximately 36 kWh/day is lost to heat. At avg procurement of ~13.4 ct/kWh, this is ~4.82 EUR/day hidden cost.

Real-world range:85-92% round-trip efficiency (DC-coupled BESS at high end, AC-coupled at low end)

Recommendation

Add a batteryRoundTripEfficiency parameter (default 0.88) to the store. Every kWh discharged should cost 1/RTE kWh on the input side. The optimizer must account for this -- sometimes it is cheaper to use grid directly than to cycle through battery at a loss.

Operational Expenditure (OpEx) Not Modeled
Critical
The simulation only considers energy costs and battery wear. All ongoing operational costs of running a public EV charging station are excluded. In Germany, operating a public HPC station requires Eichrecht-compliant metering (PTB-certified), a charging management system (CPMS), payment processing, SIM/IoT connectivity, insurance, and regular maintenance.

Estimated Impact

Estimated daily OpEx for a single HPC unit: - Eichrecht backend (has-to-be, Plug Surfing, etc.): ~2-4 EUR/day - CPMS software license (ChargeCloud, Wirelane): ~3-5 EUR/day - Payment processing (e-clearing, card terminal): ~2-4% of revenue - Maintenance / service contract: ~5-14 EUR/day (for 320 kW HPC) - Insurance (liability + equipment): ~3-8 EUR/day - Connectivity (IoT SIM, VPN): ~0.50 EUR/day - Total estimate: 15-35 EUR/day or ~5,500-12,800 EUR/year

Real-world range:15-35 EUR/day for a single HPC station (depends on service level agreement and utilization)

Recommendation

Add a flat dailyOpEx field to the cost model. Even a rough estimate of 20 EUR/day would make the P&L far more realistic.

Capital Expenditure (CAPEX) Amortization Not Modeled
Critical
The simulation does not account for the initial investment required to build the charging station. This is often the largest single cost factor and determines the payback period / ROI.

Estimated Impact

Estimated CAPEX components: - ADS-TEC CP320 ChargePost: ~150,000-200,000 EUR - PV system (150 kWp rooftop): ~120,000-180,000 EUR - Grid connection upgrade (80 kW NS): ~15,000-40,000 EUR - Installation, civil works, signage: ~20,000-40,000 EUR - Total: ~305,000-460,000 EUR - Over 10 years: ~84-126 EUR/day amortization - Over 15 years: ~56-84 EUR/day amortization

Real-world range:300,000-460,000 EUR total investment; 55-130 EUR/day depending on depreciation period

Recommendation

Add CAPEX inputs (equipment cost, installation cost, depreciation years) and compute daily amortization. This is essential for any investor/business case evaluation.

Significant

Factors that could shift results by 10-30%

Roaming & Payment Processing Fees Not Modeled
Significant
When an EV driver charges via a Mobility Service Provider (MSP/EMP) like Maingau, ADAC, Shell Recharge, etc., the CPO receives a roaming settlement, not the full ad-hoc retail price. Roaming platforms (Hubject intercharge, OCPI/Gireve) take a fee, and the MSP takes a margin. Even for direct ad-hoc users, card payment processing has costs.

Estimated Impact

- Roaming settlement: CPO typically receives 70-85% of the end-user price - Hubject/intercharge platform fee: ~0.50-2.00 EUR/session - Card payment processing: ~2-4% of transaction value - On 59 ct/kWh retail: effective revenue could be 42-52 ct/kWh via roaming - Typical CPO revenue mix: ~40% roaming, ~30% ad-hoc, ~30% subscription

Real-world range:Effective blended revenue: 42-55 ct/kWh (vs. 59 ct/kWh nominal ad-hoc)

Recommendation

Add a blendedRevenueDiscount factor (default ~15%) or model separate revenue streams for ad-hoc, roaming, and subscription users.

Retail Price (59 ct/kWh) Below Market Ad-Hoc Average
Significant
The configured retail price of 59 ct/kWh is below typical German ad-hoc DC fast charging rates in 2025. Major CPOs charge significantly more for ad-hoc (without subscription): - EnBW ad-hoc: 79 ct/kWh - Aral Pulse ad-hoc: 79 ct/kWh - Tesla Supercharger (non-Tesla): 55-60 ct/kWh - Ionity ad-hoc: 79 ct/kWh - Fastned: 69-73 ct/kWh At 59 ct, this represents a deliberate competitive undercut or a subscription-tier price.

Estimated Impact

If ad-hoc market rate is 69-79 ct and you charge 59 ct, you leave 10-20 ct/kWh on the table. On 600 kWh/day throughput, that is 90 EUR/day potential uplift.

Real-world range:49 ct (subscription) to 79 ct (ad-hoc) depending on provider and access model

Recommendation

This may be an intentional pricing strategy. Document whether 59 ct targets subscription users, is a volume-attraction strategy, or should be raised to 69 ct market rate.

Negative EPEX Spot Prices Not Modeled
Significant
The current EPEX Spot price profile has only positive prices (min 1.0 ct/kWh at 13:00). In summer 2024/2025, Germany regularly saw negative day-ahead prices during solar surplus hours (typically 11:00-15:00 on sunny weekends). Negative prices mean the CPO gets PAID to consume electricity.

Estimated Impact

On summer Saturdays in 2024, EPEX DAM prices in Germany reached -5 to -10 ct/kWh for several hours. This means the optimizer could benefit from aggressively charging the battery during negative-price windows (you get paid to fill the battery, then sell that energy to EV drivers at 59 ct). Missing this underestimates the battery arbitrage opportunity by ~2-5 EUR/day on sunny days.

Real-world range:-10 to +15 ct/kWh typical range on summer weekends (2024/2025 data)

Recommendation

Allow negative values in the EPEX price input. Add preset profiles for different day types (sunny weekend with negatives, cloudy weekday, winter evening peak).

Minor

Refinements for higher fidelity (under 10% impact)

14a StromNEV Netzentgelt Reduction Not Modeled
Minor
Since January 2024, controllable consumption devices (steuerbare Verbrauchseinrichtungen) including EV chargers can opt into 14a StromNEV to receive reduced grid fees. The grid operator gains the right to temporarily reduce the connection to 4.2 kW (per charging point) during grid congestion events. In return, the Netzentgelt Arbeitspreis is reduced.

Estimated Impact

Potential Netzentgelt reduction of ~30-60% on the Arbeitspreis component. With current Netzentgelt ~5.0 ct/kWh, savings could be 1.5-3.0 ct/kWh on all imported energy. However, the curtailment to 4.2 kW could disrupt HPC charging sessions during grid events (rare, typically < 100h/year).

Real-world range:1.5-3.0 ct/kWh reduction; curtailment risk during ~50-100 hours/year

Recommendation

Evaluate with local DSO whether 14a is compatible with battery-buffered HPC (the battery can likely absorb curtailment events without impacting EV charging).

Idle/Blocking Fees Not Modeled
Minor
Many CPOs charge a Blockiergebiihr (blocking/idle fee) when an EV remains connected after charging is complete. Typical rates are 10-15 ct/min, starting 10-15 minutes after charging ends. This is both a revenue source and an incentive to free the connector for the next user.

Estimated Impact

With 25 daily sessions, if even 20% of users overstay by 10 minutes at 10 ct/min, that is 5 sessions * 10 min * 0.10 EUR/min = 5 EUR/day additional revenue. Actual data from German CPOs suggests idle fee revenue is ~3-8% of total charging revenue.

Real-world range:3-8% additional revenue on top of energy sales

Recommendation

Add an optional idle fee parameter. This is a minor revenue source but helps with realistic P&L.

Single-Day Simulation (No Seasonal Variation)
Minor
The simulation models a single typical summer Saturday. Real-world performance varies dramatically by season: winter has ~70% less PV output, different EPEX price curves (higher evening peaks, no midday solar dip), and different EV charging patterns (lower battery efficiency in cold, more energy needed per session). Annual financial projections from a single summer day will significantly overestimate PV contribution and potentially overestimate margins.

Estimated Impact

Summer PV output ~6-8 kWh/kWp/day vs winter ~1-2 kWh/kWp/day in Germany. Annual extrapolation from a summer day overestimates PV savings by ~40-60%. Winter EPEX prices are typically higher (more gas-fired generation), which means higher procurement costs but also higher grid arbitrage potential.

Real-world range:Annual PV yield: ~950-1,100 kWh/kWp/year (vs. summer day * 365 suggests ~1,800+)

Recommendation

Add representative profiles for 4 seasons or at least summer/winter. Weight annual projections: ~5 months summer-like, ~4 months shoulder, ~3 months winter.

EV Battery Thermal Losses Not Modeled
Minor
The energy requested by each EV session is computed as a simple percentage of battery capacity. In reality, DC fast charging generates significant heat in both the charger and the EV battery. The EV's Battery Management System (BMS) may throttle charging rate or require additional energy for thermal management (heating in winter, cooling in summer). Typical DC fast charging efficiency is 90-95% (energy delivered to battery vs. energy drawn from charger).

Estimated Impact

5-10% of energy drawn from the charger does not end up as usable SOC in the EV. This means the CPO sells slightly more kWh than the EV actually stores, which is actually favorable for revenue but means the kWh-per-session estimates are slightly low (the meter bills the gross, not net).

Real-world range:90-95% charging efficiency at HPC rates

Recommendation

This slightly underestimates billed kWh per session. For accurate billing simulation, add a dcChargingOverhead factor of ~5-8%.

Grid Connection Upgrade Costs Not Modeled
Minor
The simulation assumes an 80 kW grid connection exists. In practice, upgrading a supermarket's grid connection or adding a dedicated connection for the charger involves DSO coordination, potentially transformer upgrades, and significant lead times (6-18 months in Germany). The cost depends heavily on the distance to the nearest suitable transformer and the required capacity.

Estimated Impact

Grid connection costs: - NS 80 kW (if transformer has capacity): ~5,000-15,000 EUR - NS 80 kW (if transformer upgrade needed): ~20,000-50,000 EUR - New dedicated MS connection: ~50,000-150,000 EUR These are one-time costs rolled into CAPEX.

Real-world range:5,000-150,000 EUR depending on local grid infrastructure

Recommendation

Include in CAPEX amortization when that module is added.

What this simulation DOES cover

EPEX Spot prices at 15-min resolution (96 quarter-hour slots per day)
Dynamic grid import cost (EPEX + itemized fees/taxes)
Leistungspreis (demand charge) on peak 15-min grid draw
Battery wear cost based on cycle life and replacement cost
PV production profile (PVGIS-based, with system losses)
PV self-consumption savings at hourly avoided procurement cost
Flat retail pricing model (59 ct/kWh ad-hoc)
Grid export via EEG, Direktvermarktung, or spot-indexed
25 realistic sequential EV charging sessions
1-minute resolution energy flow simulation
Equipment constraints (grid cap, battery SOC floor/ceiling, discharge rate)
Per-kWh margin analysis by energy source (PV / Grid / Battery)