Stations look busy, yet utilization and grid costs wobble
Question
Our charging network shows 80–90% utilization and sessions up, but site-level returns are uneven. Some hubs queue at peaks, others sit idle; demand charges spike bills; a few transformers run hot; and customer wait-time complaints rise. How can utilization be high while reliability and unit economics feel unstable?
Answer ✅
Averages hide cadence and composition drift. The same “85% utilization” can be calm and profitable—or produced by 2-hour bursts, misaligned tariffs, and thin grid headroom. SSM-Audit adds a stability band beside KPIs you already track, so you can see whether load, costs, and customer experience are repeatable (A+/A++) or brittle (A0/A-/A–).
What the bands would have shown 📊
• Session Cadence Stability sliding from A+ to A0/A- (bursty arrivals in short windows)
• Transformer Headroom Band degrading to A- (evening peaks near thermal limits)
• Tariff Alignment Stability drifting down-band (A0 → A-) as demand charges dominate unit cost
• Queue & Dwell Cadence weakening to A0/A- (wait-time variance and long-tail dwell)
• Utilization Balance Across Sites softening to A0 (overloaded hubs vs underused satellites)
What to do now 🛠️
- Re-shape demand: if Session Cadence band < A0, enable price shaping and reservations for peak slots; nudge fleets to shoulder hours.
- Protect headroom: when Headroom band hits A-, add staggered start, ramp limits, or phased stalls; prioritize upgrades at A- sites.
- Fix tariff fit: if Tariff Alignment band < A0, shift to TOU/managed demand-charge plans; coordinate battery buffering where viable.
- Unclog queues: when Queue/Dwell band weakens, enforce dwell caps, add idle-fee nudges, and split stalls by power tier (fast vs linger).
- Rebalance the footprint: if Utilization Balance is A0 or worse, redirect promos and fleet contracts to underused sites before adding capex.
How SSM-Audit helps (practicalities) 🌟
• No additional infrastructure: runs beside charger telemetry, billing, tariff logs, and site sensors.
• Numbers unchanged: utilization, energy, and wait-time stay as reported; stability is a read-only overlay.
• Easy to use: spreadsheet/BI friendly; one lightweight weekly review.
• Universal language: A++ / A+ / A0 / A- / A– aligns ops, grid, finance, and CX fast.
CLI 💻 — try our mini Calculator to identify the drift
(Mini CLI Download Page)
Feed your CSVs and see bands and drift at a glance (numbers unchanged).
# Session cadence (bursts vs smooth arrivals)
ssm_audit_mini_calc evnet.csv --kpi "Session Cadence Stability" \
--out bands_sessions.csv --plot_kpi "Session Cadence Stability" --build_id q51
# Transformer headroom (peak kW vs nameplate/thermal)
ssm_audit_mini_calc evnet.csv --kpi "Transformer Headroom Band" \
--out bands_headroom.csv --plot_kpi "Transformer Headroom Band" --build_id q51
# Tariff alignment (energy + demand-charge stability)
ssm_audit_mini_calc evnet.csv --kpi "Tariff Alignment Stability" \
--out bands_tariff.csv --plot_kpi "Tariff Alignment Stability" --build_id q51
# Queue and dwell cadence (wait-time variance, tail dwell)
ssm_audit_mini_calc evnet.csv --kpi "Queue & Dwell Cadence" \
--out bands_queue.csv --plot_kpi "Queue & Dwell Cadence" --build_id q51
# Utilization balance across sites (Gini or variance band)
ssm_audit_mini_calc evnet.csv --kpi "Utilization Balance" \
--out bands_balance.csv --plot_kpi "Utilization Balance" --build_id q51
Technical notes
Representation: x = (m, a) with a in (-1, +1)
Collapse parity: phi((m,a)) = m
Order-invariant pooling: U = sum(w_i * atanh(a_i)), W = sum(w_i), a_out = tanh( U / max(W, eps_w) )
Typical bands (example):A++: a >= 0.75A+: 0.50 - 0.75A0: 0.25 - 0.50A-: 0.10 - 0.25A--: a < 0.10
Navigation
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Page disclaimer
Illustrative scenario for research and education. Observation-only; do not use for critical decisions without independent validation.
SHUNYAYA 