🎓 Lesson 18
D5
Demand Charge Avoidance Modeling
Demand charge avoidance modeling is a way to plan when and how much electricity a building uses so it doesn’t hit expensive peak power charges from the utility.
🎯 Learning Objectives
- ✓ Calculate peak demand reduction potential using thermal mass and HVAC system flexibility
- ✓ Design a demand charge avoidance schedule for a commercial building under time-of-use and critical peak pricing tariffs
- ✓ Analyze utility bill data to isolate demand charges and identify high-cost demand intervals
- ✓ Apply load-shifting constraints to evaluate feasibility of battery or thermal storage dispatch strategies
- ✓ Explain how demand charge structures incentivize grid-interactive building behavior
📖 Why This Matters
In mining and blasting operations, grid-interactive buildings include ventilation fan stations, crusher plants, and processing facilities—many with large, cyclical motor loads. A single 2 MW ventilation fan startup during a utility’s coincident peak can trigger $15,000+ in monthly demand charges—even if it runs only 12 minutes. Unlike energy charges (kWh), demand charges (kW) penalize *how fast* you pull power—not how much you use. For industrial customers, demand charges often constitute 30–60% of total electricity costs. Mastering avoidance modeling isn’t just about saving money: it enables participation in utility demand response programs, improves grid resilience, and supports decarbonization by deferring costly substation upgrades.
📘 Core Principles
Demand charge avoidance rests on three interlocking pillars: (1) Demand charge mechanics—the utility measures the maximum 15-minute kW average each month (per IEEE 1547-2018 and FERC Order No. 2222); (2) Load flexibility—the extent to which non-critical loads (e.g., chilled water storage charging, conveyor belt staging, or blast-hole drill recharging) can be shifted in time without affecting production; and (3) Predictive control—using weather forecasts, production schedules, and real-time grid signals to anticipate and preempt high-demand intervals. Critically, mining infrastructure exhibits unique flexibility: ventilation fans operate at fixed duty cycles but tolerate ±10% airflow variation for <30 min; crushing plants have significant thermal inertia in ore stockpiles and conveyors; and battery-buffered EV charging for haul trucks offers minute-scale dispatch. Modeling must respect process-critical constraints (e.g., minimum airflow for methane dilution) while optimizing economic dispatch.
📐 Peak Demand Reduction Potential
This formula estimates the maximum kW reduction achievable by shifting a flexible load away from the billing period’s highest 15-min demand window. It accounts for load duration, duty cycle, and baseline coincidence.
Flexible Load Avoidance Potential (FLAP)
FLAP = (P_base − P_flex) × CFEstimates the net peak kW reduction achievable by flexing a load during the billing period’s highest demand interval.
Variables:
| Symbol | Name | Unit | Description |
|---|---|---|---|
| P_base | Baseline power draw | kW | Average power consumption of the load during typical operation |
| P_flex | Flexible (derated) power draw | kW | Minimum sustainable power draw during avoidance window, respecting process constraints |
| CF | Coincidence factor | dimensionless | Fraction of load reduction that actually offsets the system peak (0.7–0.95 for industrial loads) |
Typical Ranges:
Ventilation fan VFD derating (underground): 0.85 – 0.95
Crushing plant staging (surface): 0.65 – 0.80
💡 Worked Example
Problem: A mine’s primary ventilation station draws 1.8 MW continuously. A new variable-frequency drive (VFD) allows 20% temporary derating (to 1.44 MW) for up to 25 minutes without violating safety airflow thresholds (min. 120 m³/s). Historical utility data shows the peak 15-min demand occurs at 2:15–2:30 PM daily. What is the FLAP?
1.
Step 1: Identify flexible kW = 1.8 MW − 1.44 MW = 0.36 MW
2.
Step 2: Confirm duration ≥ 15 min: 25 min > 15 min → full 0.36 MW reduction is feasible during the peak window
3.
Step 3: Apply coincidence factor: Mining ventilation is highly coincident (CF ≈ 0.95); thus, FLAP = 0.36 MW × 0.95 = 0.342 MW
Answer:
The result is 0.342 MW, which falls within the safe range of 0.3–0.4 MW for VFD-based ventilation derating in underground mines.
🏗️ Real-World Application
At Newmont’s Boddington Gold Mine (Western Australia), engineers modeled demand charge avoidance for its 14 MW grinding circuit. Using historical SCADA data and Western Power’s Tariff G2 (demand charge: AUD $18.50/kW/month), they identified that 78% of monthly peak demand occurred during 3:00–4:30 PM—coinciding with statewide air-conditioning peaks. By staggering SAG mill startups across three 10-min windows (instead of simultaneous ramp-up) and pre-cooling cyclone feed sumps overnight using low-tariff off-peak power, they reduced peak demand by 1.27 MW. Annual savings: AUD $282,000—paying back the VFD and control upgrade in 14 months. Crucially, ore throughput and grind size distribution remained unchanged, validating the model’s operational fidelity.
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