Overview
Our forward pricing model integrates industry-leading forecasts from Aurora Energy Research with real-time
AEMO market data to provide bankable revenue projections for battery energy storage systems (BESS) in the
National Electricity Market (NEM).
Aurora Energy Research Forecasts
Aurora Energy Research is the globally recognized authority on power market analytics, trusted by over 400
organizations including major banks, infrastructure funds, and energy companies. Their Australian power market
forecasts are considered the gold standard for project finance and investment decisions.
Key features of Aurora's methodology:
- Fundamental market modeling: Bottom-up simulation of all generation assets, demand patterns, and network constraints
- Policy integration: Incorporates federal and state renewable energy targets, capacity mechanisms, and regulatory changes
- Technology evolution: Models the impact of increasing renewable penetration, battery deployment, and grid-forming inverters
- Scenario analysis: Central case calibrated against futures markets with sensitivity scenarios for key uncertainties
Data Integration Hierarchy
Our platform seamlessly blends multiple data sources to provide optimal forecast accuracy across all time horizons:
0-2 hours: AEMO P5 Predispatch (5-minute granularity)
2-48 hours: AEMO PD30 Predispatch (30-minute granularity)
Beyond 48 hours: Aurora Energy Research seasonal forecasts
This hierarchical approach ensures maximum accuracy for near-term optimization while maintaining robust
long-term projections aligned with market fundamentals.
Storage Spread Calculation
Battery arbitrage opportunities are quantified through rolling window spread calculations, consistent with
industry-standard project finance models:
0.5-hour spread (S₀.₅): max(price) - min(price) within single interval
1-hour spread (S₁): max(avg₂) - min(avg₂) for 2-interval rolling windows
2-hour spread (S₂): max(avg₄) - min(avg₄) for 4-interval rolling windows
4-hour spread (S₄): max(avg₈) - min(avg₈) for 8-interval rolling windows
These spreads directly correlate with BESS revenue potential for different duration configurations,
enabling accurate feasibility assessment and optimized system sizing.
Intraday Price Formation
Aurora's annual wholesale prices and storage spreads are translated into realistic 30-minute price patterns
using NEM-specific characteristics:
- Duck curve dynamics: Solar-induced midday price depression (10:00-15:00 AEST)
- Evening peak premiums: Demand-driven price elevation (17:00-21:00 AEST)
- Overnight baseload: Stable low prices during minimum demand periods
- Volatility events: Statistically distributed price spikes and negative pricing periods based on historical frequency analysis
Bankability and Risk Assessment
The forward curves include P10/P90 confidence bands derived from:
- Historical volatility patterns adjusted for changing market dynamics
- Aurora's scenario analysis for policy and technology uncertainties
- Weather-driven demand and renewable generation variability
- Forced outage rates and network constraint probability distributions
This probabilistic approach enables comprehensive risk assessment for debt sizing, including:
- Debt Service Coverage Ratio (DSCR) calculations under P90 downside scenarios
- Revenue stability analysis for contracted vs merchant exposure
- Sensitivity testing for key market drivers
Validation and Calibration
Forward prices are continuously validated against:
- ASX Energy quarterly base futures for near-term periods
- Recent AEMO spot price outcomes and predispatch accuracy
- Observed storage cycling patterns from operational BESS assets
- Power Purchase Agreement (PPA) pricing from recent transactions
Regulatory Compliance
All projections incorporate current and announced regulatory frameworks including:
- Capacity Investment Scheme (CIS) tender parameters
- Renewable Energy Zone (REZ) development timelines
- Frequency Control Ancillary Services (FCAS) market co-optimization
- Five-minute settlement and Global Settlement implementation
Note: This model is designed for preliminary feasibility assessment and strategic planning.
Detailed investment decisions should incorporate site-specific factors, connection studies, and formal
independent market reports as required by project finance lenders.
