Swap Network Service (SNS) Business Model¶
Overview¶
The SNS-Swap-Network-Service (SN) model represents a real estate infrastructure operator (landlord model) that owns/controls physical locations and provides battery housing and charging services to the Battery Fleet operator.
Critical Modeling Methodology: Integer Unit Constraints¶
Physical Architecture¶
Rack = Slots + Chargers - 1 Rack = 15 slots (fixed physical constraint) - Default: 15 chargers per rack (1:1 slot:charger ratio) - Flexible: Can deploy fewer chargers if slots share charging capacity
Component Costs: - Slot hardware: $60/slot (20%) - rack structure, mounting - Charger hardware: $240/charger (80%) - power electronics, cables - Installation: $300/rack - wiring, commissioning
Two-Layer Economic Model¶
The model explicitly separates installed capacity (integer-constrained) from actual usage (demand-driven) to capture the economic impact of modular infrastructure:
Infrastructure Layer (Integer-Constrained)¶
Installed Racks = SNS_SCALE_FACTOR (integer: 1, 2, 3...)
Installed Slots = Installed Racks × 15
Installed Chargers = Installed Racks × chargers_per_rack
Total CapEx = Based on installed capacity
Fixed OpEx = Property + Labor + Security (on installed racks)
Operational Layer (Demand-Driven)¶
Active Slots = ds_total_slots (from demand-supply)
Slot Utilization = Active Slots / Installed Slots
Revenue = Only from active slots
Variable OpEx = Only on active usage (electricity)
Economic Impact¶
Example: Test Case A - Demand: 20 slots needed - Supply: Must build 2 racks = 30 slots (can't build 1.33 racks!) - Utilization: 20/30 = 67% - CapEx Burden: Pay for 30 slots - Fixed OpEx Penalty: Spread over 30 slots → higher per-slot cost - Revenue: Only from 20 active slots - Result: Longer payback period due to 33% overcapacity
This models the fundamental infrastructure investment challenge: You cannot build partial units, so demand-supply mismatches create unavoidable inefficiencies that directly impact ROI.
Terminology¶
- Slot: Physical location where a battery sits (15 per rack, fixed)
- Charger: Power electronics that charge batteries (default 15 per rack, can be <15)
- Rack: Complete infrastructure unit containing slots + chargers
- Installed Capacity: What you built (integer racks)
- Active Capacity: What demand actually uses
- Utilization Rate: Active / Installed (key economic metric)
Business Context¶
This model analyzes the investment opportunity for swap rack operators who provide charging infrastructure and electricity distribution services to battery fleet operators. The model uses unit economics based on a single charging slot to simplify scalability analysis.
Central Question: "Can I profitably operate a charging bay network?" (SNS-Swap-Network-Service Operator Perspective)
Integrated Workbook¶
📥 Download Full Ecosystem Model
This model is implemented in the SNS-Swap-Network-Service tab of the integrated workbook. All parameters are sourced from both the SNS-Swap-Network-Service tab (local parameters) and global settings, ensuring consistency across all ecosystem models.
Business Context¶
Design Principle: Bottom-Up Modeling - Unit economics constrained by battery asset profitability requirements.
Swap network operators need to evaluate: - Capital investment per charging bay (infrastructure + installation) - Daily operating costs (labor, property, electricity) - Revenue model (electricity markup to battery operators) - Network scalability and site-level economics - Return on investment and operational viability
Critical Constraint from Battery Asset Model: - Battery operators need daily net cash > $0.98/kWh to achieve profitability - Current overhead (labor + property) = $0.65/kWh/day represents 41% of battery OpEx - Swap network must deliver infrastructure services efficiently to enable battery asset viability - Target: Total allocated overhead < $0.40/kWh/day (38% reduction from current)
Model Inputs¶
Source: All input parameters are defined in the
SNS-Swap-Network-Servicetab of the Excel workbook and referenced using named ranges throughout the model.
CapEx (Capital Expenditure per Bay)¶
These represent the upfront investment required per charging bay:
| Parameter | Symbol | Value | Unit | Description | Excel Location |
|---|---|---|---|---|---|
| Rack cost per bay | SNS_RACK_COST |
300 | USD/bay | Hardware cost per charging slot (battery cradle, connectors, control electronics) | SNS-Swap-Network-Service!C7 |
| Installation cost | SNS_INSTALL_COST |
20 | USD/bay | Wiring, mounting, commissioning per bay | SNS-Swap-Network-Service!C8 |
| Total CapEx per bay | sns_capex_per_bay |
320 | USD/bay | Rack + Installation | Calculated |
| Service life | SNS_SERVICE_LIFE |
1000 | days | Depreciation period (~3 years) | SNS-Swap-Network-Service!C9 |
| Residual value % | SNS_RESIDUAL_PCT |
0 | ratio | No scrap value (fully depreciated infrastructure) | SNS-Swap-Network-Service!C10 |
CapEx Rationale: - Rack cost (\(300):** Includes battery cradle, charging connectors, control electronics, and safety systems - **Installation (\)20): Minimal cost assuming pre-wired facility; higher if electrical infrastructure upgrades needed - Service life (1000 days): Conservative estimate; actual hardware may last longer but technological obsolescence considered - Zero residual value: Infrastructure is site-specific and has limited resale value
Operational Parameters (Charging Capacity)¶
These define the charging throughput capacity of each bay:
| Parameter | Symbol | Value | Unit | Description | Excel Location |
|---|---|---|---|---|---|
| Charger power rating | SNS_CHARGER_POWER |
2.0 | kW | Installed power per bay (2kW slow charger) | SNS-Swap-Network-Service!C13 |
| Operating hours per day | SNS_OPERATING_HOURS |
12 | hours/day | Hours per day the bay is available for charging | SNS-Swap-Network-Service!C14 |
| Bay utilization rate | SNS_BAY_UTILIZATION |
0.50 | ratio | Percentage of operating time actually used for charging (50%) | SNS-Swap-Network-Service!C15 |
| Charging efficiency | SNS_CHARGE_EFFICIENCY |
0.93 | ratio | Energy retention during charging (7% loss from heat, conversion inefficiency) | SNS-Swap-Network-Service!C16 |
Operational Parameters Rationale: - 2kW charger: Matches battery charging rate; slow charging extends battery life vs fast charging - 12 hours/day operating: Assumes daytime operations (6 AM - 6 PM); nighttime charging possible but adds labor costs - 50% utilization: Conservative estimate; actual utilization depends on battery/bay ratio (to be coupled in integrated model) - 93% efficiency: Industry-standard charging efficiency; 7% loss is unavoidable in DC charging systems
Throughput Calculation:
Actual throughput = Power × Operating hours × Utilization
= 2 kW × 12 hrs × 50%
= 12 kWh/bay/day
Grid consumption = Actual throughput ÷ Charging efficiency
= 12 kWh ÷ 0.93
= 12.90 kWh/bay/day (includes 7% loss)
Network Configuration¶
These define the scale and structure of the swap station network:
| Parameter | Symbol | Value | Unit | Description | Excel Location |
|---|---|---|---|---|---|
| Bays per station | SNS_BAYS_PER_STATION |
15 | bays | Charging slots per location (site-level infrastructure) | SNS-Swap-Network-Service!C19 |
| Stations managed | SNS_STATION_COUNT |
10 | stations | Total locations in network (network-level scale) | SNS-Swap-Network-Service!C27 |
| Total network bays | sns_total_bays |
150 | bays | Total charging capacity | Calculated |
Network Configuration Rationale: - 15 bays/station: Optimized for Activity-Based Costing; allows efficient labor and property cost allocation - 10 stations: Pilot network scale; provides geographic coverage while maintaining operational control - Total 150 bays: Sufficient to serve 100-300 battery fleet (depending on battery/bay ratio to be determined in coupling)
Activity-Based Cost Drivers (Site Operations)¶
These represent the fixed costs at the station level that must be allocated across bays:
| Parameter | Symbol | Value | Unit | Description | Excel Location |
|---|---|---|---|---|---|
| Property ownership cost | SNS_PROPERTY_COST |
50 | USD/month | Utilities, property tax, insurance for owned location | SNS-Swap-Network-Service!C23 |
| Labor: Attendant wage | SNS_LABOR_RATE |
100 | USD/month | Part-time site attendant salary | SNS-Swap-Network-Service!C24 |
| Labor: Hours per station | SNS_LABOR_HRS_STATION |
10 | hours/month | Cleaning, monitoring, troubleshooting | SNS-Swap-Network-Service!C25 |
| Security cost | SNS_SECURITY_COST |
20 | USD/month | Cameras, locks, insurance | SNS-Swap-Network-Service!C26 |
ABC Cost Allocation:
Property cost per bay = $50 ÷ 15 bays = $3.33/bay/month = $0.11/bay/day
Labor cost per bay = $100 ÷ 15 bays = $6.67/bay/month = $0.22/bay/day
Security cost per bay = $20 ÷ 15 bays = $1.33/bay/month = $0.04/bay/day
Total fixed OpEx = $0.11 + $0.22 + $0.04 = $0.37/bay/day
ABC Drivers Rationale: - Property (\(50/month):** Assumes owned property; includes utilities, property tax, insurance; rent would be higher - **Labor (\)100/month): Part-time attendant (~40 hrs/month × \(2.50/hr); assumes low-supervision automated bays - **Labor hours (10 hrs/month):** Minimal on-site time; majority of management is remote monitoring - **Security (\)20/month): Basic security (cameras, locks); assumes low-theft environment - Activity-Based Costing:** Fixed costs allocated per bay ensures accurate unit economics and scalability analysis
Revenue Model (Electricity Pricing)¶
The swap network's primary revenue is from selling electricity to battery operators:
| Parameter | Symbol | Value | Unit | Description | Excel Location |
|---|---|---|---|---|---|
| Electricity markup % | SNS_ELEC_MARKUP |
0.20 | ratio | Premium charged to BCS_ (20% above wholesale cost) | SNS-Swap-Network-Service!C28 |
| Grid electricity rate | sns_eps_facility_rate |
0.32 | USD/kWh | Wholesale electricity cost from power generator | Referenced from EPS_ model |
Revenue Calculation:
Grid energy consumed = 12.90 kWh/bay/day
Wholesale cost = 12.90 × $0.32 = $4.13/bay/day
Retail price to BF = $0.32 × (1 + 20%) = $0.384/kWh
Revenue from BF = 12.90 × $0.384 = $4.95/bay/day
Electricity margin = $4.95 - $4.13 = $0.82/bay/day
Pricing Rationale: - 20% markup: Industry-standard margin for electricity resale; covers distribution overhead and infrastructure costs - Wholesale rate ($0.32/kWh): Togo's high electricity cost; significantly above typical $0.15/kWh in other markets - Margin preservation: 20% markup ensures consistent margin regardless of wholesale price fluctuations
Model Outputs¶
Source: All calculations are performed in the
SNS-Swap-Network-Servicetab using formulas that reference the named ranges.
Calculated Metrics¶
The following table shows the actual Excel implementation with multi-step formulas for clarity:
| Metric | Excel Formula | Value | Unit | Description |
|---|---|---|---|---|
| CapEx Metrics | ||||
| sns_capex_per_bay | =sns_rack_cost+sns_install_cost |
320.00 | USD/bay | Total capital per bay |
| sns_total_bays | =sns_station_count*sns_bays_per_station |
150 | bays | Network capacity |
| sns_residual_value | =sns_capex_per_bay*sns_residual_pct |
0.00 | USD/bay | No salvage value |
| Throughput Capacity | ||||
| sns_actual_throughput | =sns_charger_power*sns_operating_hours*sns_bay_utilization |
12.00 | kWh/bay/day | 2kW × 12h × 50% |
| sns_grid_energy_consumed | =sns_actual_throughput/sns_charge_efficiency |
12.90 | kWh/bay/day | Includes 7% loss |
| ABC Allocation (Fixed Costs) | ||||
| sns_property_per_bay | =sns_property_cost/sns_bays_per_station |
3.33 | USD/bay/month | Property overhead |
| sns_labor_per_bay | =sns_labor_rate/sns_bays_per_station |
6.67 | USD/bay/month | Labor overhead |
| sns_security_per_bay | =sns_security_cost/sns_bays_per_station |
1.33 | USD/bay/month | Security overhead |
| sns_fixed_opex_month | =sns_property_per_bay+sns_labor_per_bay+sns_security_per_bay |
11.33 | USD/bay/month | Total fixed costs |
| sns_fixed_opex_day | =sns_fixed_opex_month/30 |
0.38 | USD/bay/day | Daily fixed costs |
| Electricity Economics | ||||
| sns_elec_cost_per_bay | =sns_grid_energy_consumed*sns_eps_facility_rate |
4.13 | USD/bay/day | Wholesale cost |
| sns_elec_price_to_bf | =sns_eps_facility_rate*(1+sns_elec_markup) |
0.384 | USD/kWh | Retail price (20% markup) |
| sns_elec_revenue_per_bay | =sns_grid_energy_consumed*sns_elec_price_to_bf |
4.95 | USD/bay/day | Revenue from BF |
| sns_elec_margin_per_bay | =sns_elec_revenue_per_bay-sns_elec_cost_per_bay |
0.82 | USD/bay/day | Electricity profit |
| Total Metrics | ||||
| sns_total_opex_per_bay | =sns_fixed_opex_day+sns_elec_cost_per_bay |
4.51 | USD/bay/day | Fixed + Variable OpEx |
| sns_total_revenue_per_bay | =sns_elec_revenue_per_bay |
4.95 | USD/bay/day | Only electricity revenue |
| sns_daily_net_cash | =sns_total_revenue_per_bay-sns_total_opex_per_bay |
0.44 | USD/bay/day | Net cash flow |
Key Performance Indicators¶
The following KPIs reference pre-calculated metrics from the Calculated Metrics section:
| KPI | Excel Formula | Value | Unit | Description |
|---|---|---|---|---|
| SNS_Daily_Net_Cash_KPI | =sns_daily_net_cash |
0.44 | USD/bay/day | Daily profitability per bay |
| SNS_Electricity_Margin_KPI | =sns_elec_margin_per_bay |
0.82 | USD/bay/day | Electricity markup profit |
| SNS_Actual_Throughput_KPI | =sns_actual_throughput |
12.00 | kWh/bay/day | Energy delivered to batteries |
| SNS_Payback_Period_KPI | =sns_capex_per_bay/sns_daily_net_cash |
727 | days | Time to recover CapEx (~2 years) |
| SNS_Network_Revenue_KPI | =sns_total_revenue_per_bay*sns_total_bays |
742.50 | USD/day | Total network revenue (150 bays) |
| SNS_Profit_Margin_KPI | =(sns_daily_net_cash/sns_total_revenue_per_bay)*100 |
8.89 | % | Net margin percentage |
Calculation Logic¶
Cost Structure Breakdown (Per Bay/Day)¶
| Component | Calculation | Value | % of Total OpEx | USD/bay/day |
|---|---|---|---|---|
| Fixed Costs (ABC Allocation) | ||||
| Labor | $100÷15÷30 | 23% | 0.22 | |
| Property | $50÷15÷30 | 11% | 0.11 | |
| Security | $20÷15÷30 | 4% | 0.04 | |
| Subtotal Fixed | 38% | 0.38 | 8% of OpEx | |
| Variable Costs (Electricity) | ||||
| Grid electricity | 12.90 × $0.32 | 4.13 | 92% of OpEx | |
| Total OpEx | 100% | 4.51 | USD/bay/day |
Revenue Structure Breakdown (Per Bay/Day)¶
| Component | Calculation | Value | % of Revenue | USD/bay/day |
|---|---|---|---|---|
| Wholesale electricity cost | 12.90 × $0.32 | 4.13 | 83% | |
| Electricity markup (20%) | 12.90 × $0.064 | 0.82 | 17% | |
| Total Revenue | 100% | 4.95 | USD/bay/day |
Profitability Analysis¶
| Metric | Calculation | Value | Unit |
|---|---|---|---|
| Daily Revenue | Electricity sales | 4.95 | USD/bay/day |
| Daily OpEx | Fixed + Electricity | 4.51 | USD/bay/day |
| Daily Net Cash | Revenue - OpEx | 0.44 | USD/bay/day |
| Net Margin | (0.44 ÷ 4.95) × 100 | 8.89 | % |
| Monthly Net Cash | 0.44 × 30 | 13.20 | USD/bay/month |
| CapEx per Bay | Rack + Install | 320.00 | USD/bay |
| Payback Period | 320 ÷ 0.44 | 727 | days (~2 years) |
Key Drivers Analysis¶
What determines swap network profitability?
1. Electricity Throughput (Biggest Driver)¶
| Utilization | Hours | Throughput | Grid Energy | Revenue | Net Cash | Payback |
|---|---|---|---|---|---|---|
| 30% | 12 | 7.2 kWh | 7.74 kWh | $2.97 | -$0.92 | N/A (loss) |
| 40% | 12 | 9.6 kWh | 10.32 kWh | $3.96 | -$0.24 | N/A (loss) |
| 50% | 12 | 12.0 kWh | 12.90 kWh | $4.95 | $0.44 | 727 days |
| 60% | 12 | 14.4 kWh | 15.48 kWh | $5.94 | $1.12 | 286 days |
| 80% | 12 | 19.2 kWh | 20.65 kWh | $7.93 | $2.55 | 125 days |
Impact: Every 10% increase in utilization adds ~$0.17/day net cash and reduces payback by ~90 days.
2. Electricity Markup (Revenue Model)¶
| Markup % | Retail Price | Revenue | Margin | Net Cash | Payback |
|---|---|---|---|---|---|
| 10% | $0.352/kWh | $4.54 | $0.41 | $0.03 | 10,667 days |
| 15% | $0.368/kWh | $4.75 | $0.62 | $0.24 | 1,333 days |
| 20% | $0.384/kWh | $4.95 | $0.82 | $0.44 | 727 days |
| 25% | $0.400/kWh | $5.16 | $1.03 | $0.65 | 492 days |
| 30% | $0.416/kWh | $5.37 | $1.24 | $0.86 | 372 days |
Impact: Every 5% increase in markup adds ~$0.21/day net cash and reduces payback by ~235 days.
3. Activity-Based Cost Efficiency¶
Scenario A: Current (15 bays/station)
Fixed OpEx = ($50 + $100 + $20) ÷ 15 = $11.33/bay/month = $0.38/bay/day
Scenario B: Optimized (25 bays/station)
Fixed OpEx = ($50 + $100 + $20) ÷ 25 = $6.80/bay/month = $0.23/bay/day
Savings = $0.15/bay/day
New Net Cash = $0.44 + $0.15 = $0.59/bay/day
New Payback = 320 ÷ 0.59 = 542 days (185 days faster)
Impact: Increasing bays/station from 15 to 25 improves net cash by 34% and reduces payback by 25%.
4. Labor Cost Reduction¶
| Labor Rate | Cost/Bay/Day | Net Cash | Payback |
|---|---|---|---|
| $150/month | $0.33 | $0.33 | 970 days |
| $100/month | $0.22 | $0.44 | 727 days |
| $75/month | $0.17 | $0.50 | 640 days |
| $50/month | $0.11 | $0.55 | 582 days |
Impact: Every \(25/month reduction in labor adds ~\)0.06/day net cash and reduces payback by ~87 days.
Decision Criteria¶
SNS-Swap-Network-Service Investment Viability:
✅ Favorable Investment if: - SNS_Daily_Net_Cash_KPI > $0.50/bay/day (strong cash flow) - SNS_Payback_Period_KPI < 500 days (~1.4 years) - SNS_Profit_Margin_KPI > 10% (healthy margin) - Bay utilization > 60% (high throughput) - Bays per station ≥ 20 (efficient ABC allocation)
⚠️ Review Investment if: - SNS_Daily_Net_Cash_KPI: \(0.20-\)0.50/bay/day (marginal cash flow) - SNS_Payback_Period_KPI: 500-730 days (1.4-2 years) - SNS_Profit_Margin_KPI: 5-10% (thin margin) - Bay utilization: 50-60% (moderate throughput)
❌ Unfavorable Investment if: - SNS_Daily_Net_Cash_KPI < $0.20/bay/day (insufficient cash flow) - SNS_Payback_Period_KPI > 730 days (> 2 years) - SNS_Profit_Margin_KPI < 5% (unsustainable margin) - Bay utilization < 50% (underutilized infrastructure)
Investment Optimization Strategies:
If profitability is marginal, improve by:
- Increase Throughput (highest impact)
- Increase bay utilization (couple to battery fleet demand)
- Extend operating hours (12h → 18h adds 50% capacity)
-
Higher power chargers (2kW → 3kW adds 50% throughput)
-
Optimize Activity-Based Costs (medium impact)
- Increase bays per station (15 → 25 improves ABC by 40%)
- Reduce labor rate (automation, remote monitoring)
-
Negotiate lower property costs (owned vs rented)
-
Improve Revenue Model (low-medium impact)
- Negotiate higher electricity markup (if market allows)
- Reduce wholesale electricity cost (negotiate with EPS_)
- Add ancillary revenue (battery storage fees, network access)
Interdependencies with Other Models¶
Dependencies FROM Other Models (Bottom-Up Flow)¶
| Source Model | Data Required | Impact | Constraint Type |
|---|---|---|---|
| bss.md | Overhead allocation < $0.40/kWh/day | Current $0.65 too high; requires 38% reduction | Hard constraint |
| bss.md | Battery fleet size & swap frequency | Determines bay utilization rate | Demand driver |
| bss.md | Energy cost sensitivity | Maximum electricity markup tolerance | Revenue constraint |
| eps.md | Wholesale electricity cost | Determines sns_eps_facility_rate input |
Hard constraint |
Dependencies TO Other Models (Requirements Flow)¶
| Target Model | Data Provided | Impact | Requirement |
|---|---|---|---|
| bss.md | Electricity at $0.384/kWh | Battery OpEx = $1.24/kWh/day | Cost allocation |
| bss.md | Infrastructure availability | Battery deployment feasibility | Service enabler |
| bss.md | Network density & coverage | Battery utilization potential | Service level |
| eps.md | Grid demand = 12.90 kWh/bay/day | Power capacity requirements | Load profile |
Current Impact on Battery Asset Model¶
With Current SNS_ Parameters:
| Metric | Battery Asset Model | Impact |
|---|---|---|
| Electricity cost | $0.384/kWh × 2.0 swaps × 4.0 kWh = $3.07/kWh/day | Primary battery OpEx |
| Allocated overhead | Labor (\(0.22) + Property (\)0.11) = $0.33/kWh/day | 21% of battery OpEx |
| Total SNS_ burden | $3.40/kWh/day | 74% of battery OpEx |
| Battery net cash | Revenue (\(2.56) - OpEx (\)1.58) = $0.98/kWh/day | Positive but constrained |
Target: Reduce SNS_ overhead from $0.33 to $0.25/kWh/day (24% reduction)
Current Status & Next Steps¶
Current Model Status¶
Implemented:
- ✅ Unit economics per charging bay
- ✅ Activity-Based Costing (ABC) allocation
- ✅ Electricity throughput and efficiency modeling
- ✅ Revenue model with 20% electricity markup
- ✅ KPI tracking with _KPI suffix convention
Assumptions (Placeholders): - ⏳ Bay utilization (50%) - Will be coupled to battery fleet demand - ⏳ Operating hours (12h/day) - Static assumption; nighttime operations not modeled - ⏳ Wholesale electricity rate ($0.32/kWh) - Referenced from EPS_ model (to be implemented)
Integration Requirements¶
When coupling with BCS_ (Battery Fleet) model:
1. Replace SNS_BAY_UTILIZATION with dynamic calculation:
Bay utilization = (Battery count × Swaps/day × Energy/swap) ÷ (Bay count × Max throughput)
When coupling with EPS_ (EPS-Electric-Power-Service) model:
1. Replace sns_eps_facility_rate hardcoded value with dynamic EPS_ output
2. Model time-of-day pricing (peak vs off-peak electricity costs)
3. Optimize charging schedules to minimize electricity costs
Sensitivity Analysis Roadmap¶
Multi-variable analysis needed: 1. Bay utilization × Electricity markup (revenue optimization) 2. Bays per station × Labor cost (ABC optimization) 3. Operating hours × Charger power (capacity planning) 4. Wholesale rate × Markup % (pricing strategy)
Excel Implementation¶
Workbook Structure¶
Workbook: models/dirac-abs-ecosystem-model.xlsx
Tab Used:
- SNS-Swap-Network-Service - All parameters, calculations, and KPIs
Excel Features¶
- Named Ranges: All parameters and calculated metrics defined as named ranges
- Unit Economics: All calculations based on 1 charging bay for easy network scaling
- Cell Formatting:
- Blue cells (D9E1F2): Input parameters
- Light blue cells (DDEBF7): Calculated metrics
- Pale blue cells (CFE2F3): KPIs
- Gray cells (E7E6E6): Infrastructure parameters
- Formula-Based: All calculations use Excel formulas with named ranges
- Scalability: Multiply per-bay results by
sns_total_baysto get network totals - KPI Suffix Convention: All KPIs use
_KPIsuffix to avoid circular references
Key Formula Examples¶
Throughput:
=sns_charger_power*sns_operating_hours*sns_bay_utilization
// 2kW × 12h × 50% = 12 kWh/bay/day
ABC Allocation:
=sns_property_cost/sns_bays_per_station
// $50 ÷ 15 bays = $3.33/bay/month
Revenue:
=sns_grid_energy_consumed*sns_elec_price_to_bf
// 12.90 kWh × $0.384/kWh = $4.95/bay/day
Version History¶
| Version | Date | Changes | Author |
|---|---|---|---|
| 1.0 | 2025-11-15 | Complete swap network model with unit economics, ABC allocation, electricity markup model, and KPI tracking | OVES Team |
Bottom-Up Modeling Sequence: 1. ✅ Rider Model: Established 30% savings requirement → Max swap price = 0.80 USD/day 2. ✅ Battery Asset Model: Analyzed profitability → Required overhead < $0.40/kWh/day 3. ✅ SNS-Swap-Network-Service Model: Infrastructure economics → Current overhead = \(0.33/kWh/day (needs optimization) 4. ⏳ **Next: EPS-Electric-Power-Service Model** - Must provide electricity at competitive rates vs grid (\)0.32/kWh)