🎓 Lesson 19
D5
Iterative Hosting Capacity Calculation Using Time-Domain Sweep
It's a step-by-step computer simulation method that tests how much renewable energy a power grid can safely absorb at different times of day by repeatedly running time-based stability models.
🎯 Learning Objectives
- ✓ Calculate hosting capacity limits using time-domain simulation outputs for a given feeder configuration
- ✓ Design a time-domain sweep test plan including scenario selection, timestep resolution, and convergence criteria
- ✓ Analyze voltage deviation and reverse power flow trends across 24-hour simulation results to identify constraint-binding conditions
- ✓ Explain how inverter reactive power support settings influence iterative convergence and HC outcomes
- ✓ Apply IEEE 1547-2018 ride-through and reactive power requirements to interpret simulation pass/fail criteria
📖 Why This Matters
As mines deploy solar microgrids and battery storage to decarbonize operations, engineers must ensure these resources don’t destabilize critical AC/DC distribution networks—especially during rapid load shifts (e.g., crusher startup) or cloud-induced PV ramping. Unlike generic utility studies, mining grids face unique challenges: weak system strength, unbalanced feeders, harmonic-rich VFDs, and islanded operation. Iterative time-domain sweep is the only method capable of capturing these fast transients and control interactions—making it essential for safe, reliable, and compliant renewable integration in mining infrastructure.
📘 Core Principles
Hosting capacity is not a single number—it’s a function of time, location, and operational context. The time-domain sweep method treats the problem as a sequence of deterministic simulations: first, a base-case load-generation profile is constructed using 15-min or 1-sec resolution data; then, renewable penetration is incrementally increased (e.g., 5% steps) while re-running full time-domain simulations for each step; at each increment, all IEEE 1547-2018 compliance metrics (voltage band ±5%, frequency response, anti-islanding, reactive power dispatch) are evaluated across every timestep. Convergence is declared when any constraint violation occurs in ≥3 consecutive timesteps—or exceeds 1% of total simulation duration—defining the HC limit. The iteration loop includes automatic adjustment of inverter Q(V) and Q(f) curves to explore mitigation potential before declaring failure.
📐 Hosting Capacity Limit (HCL) via Iterative Sweep
The HC limit is determined by binary search over penetration levels, where each iteration solves a time-domain stability constraint satisfaction problem. The core decision metric is the maximum allowable penetration λ_max such that all time-domain constraints remain satisfied throughout the sweep window.
💡 Worked Example
Problem: Given: 12.47 kV radial mine feeder with 4.2 MW peak load; base PV penetration = 0%; sweep interval = 5% increments; time-domain simulation (EMT) run for 24h at 10-ms timesteps; constraint threshold = voltage > 1.05 pu for >60 s cumulative per 24h. At 35% PV penetration, cumulative overvoltage = 72 s; at 30%, = 18 s.
1.
Step 1: Initialize λ_low = 0%, λ_high = 100%; run simulation at λ = 50% → violation detected → set λ_high = 50%
2.
Step 2: Run at λ = 25% → no violation → set λ_low = 25%; run at λ = 37.5% → violation → set λ_high = 37.5%
3.
Step 3: Run at λ = 31.25% → no violation (18 s overvoltage < 60 s threshold); run at λ = 34.375% → violation (72 s > 60 s). Final λ_max = 31.25%.
4.
Step 4: Verify result against IEEE 1547-2018 Section 5.2.2.1: voltage must remain within 0.95–1.05 pu for ≥99% of 24h period — confirmed.
Answer:
The hosting capacity limit is 31.25% PV penetration, satisfying both cumulative overvoltage and IEEE 1547 compliance thresholds.
🏗️ Real-World Application
At Newmont’s Boddington Gold Mine (Western Australia), engineers used PSCAD EMT time-domain sweeps to assess 15 MW solar + 10 MWh battery integration on its 33 kV mine internal grid. They modeled 32 representative days (summer/winter, clear/cloudy, high/low ore throughput), ran 10,000+ iterative simulations across 0–120% PV penetration, and identified transformer saturation and VFD tripping—not voltage—were binding constraints during morning cloud-ramp events. By adjusting inverter Q(V) slope from 2% / 0.01 pu to 4% / 0.01 pu and adding 500 kvar STATCOM, HC increased from 41% to 68%. This directly informed procurement specs and grid-code waiver submissions to AEMO.