How generation capacities and output are modeled across WECC
Capacity buildout
Description
Capacity additions are determined by our proprietary Capacity Expansion Model based on techno-economic criteria. The maximum and minimum buildout limits per technology are constrained based on historical observations and timeline estimations of past projects in the interconnection queue.
Plant retirements are incorporated based on publicly announced shutdowns where available. In the absence of such announcements, retirements are projected using technology-specific lifespan assumptions, drawing from the EIA-860 generator inventory and the WECC ADS generator list.
Forecast
Policy drivers
- California’s SB 100 requires 100% clean electricity by 2045
- Storage mandates and procurement targets drive significant battery buildout
- Once-through cooling regulations are driving thermal plant retirements
Assumptions and caveats
- Build decisions are informed by the Capacity Expansion Model and queue analysis
Data sources
| Source | Description | Link |
|---|---|---|
| CPUC IRP | Renewable capacity factors | CPUC SERVM |
| EIA-860 | Asset-level data on generation technology, operational status, and age; used for retirement assumptions | EIA-860 |
| NREL ATB | CAPEX/OPEX assumptions for CEM investment decisions | NREL ATB |
| WECC ADS | Generator inventory and wheeling tariffs | WECC ADS |
Short-run marginal costs
Description
Short-run marginal costs (SRMCs) are estimated for all generation technologies in the system, including thermal and renewable assets. These values are derived primarily from fuel prices and heat rate assumptions. Fuel prices are sourced from the CPUC SERVM commodity forecasts and the EIA AEO for long-run gas escalation. Heat rates are calculated from EIA-923 fuel receipts and WECC ADS thermal IO curves. Carbon costs are incorporated using CPUC GHG allowance price projections. Where available, commodity prices, start costs, and outages are calculated on a plant-specific basis.
For variable renewable technologies such as wind and solar, SRMCs are adjusted to reflect tax credits, which can result in negative marginal costs.
Policy drivers
- Production tax credits (PTC) and investment tax credits (ITC) for wind and solar are reflected in SRMCs.
Assumptions and caveats
- Technology-average heat rates are used for future or unbuilt units.
Data sources
| Source | Description | Link |
|---|---|---|
| CPUC GHG | Carbon allowance price projections | CPUC SERVM |
| CPUC SERVM | Forecast commodity prices (fuel price trajectories) | CPUC SERVM |
| EIA AEO | Long-run gas price escalation | EIA AEO Data |
| EIA-923 | Fuel receipts and costs for heat rate calculations | EIA-923 |
| WECC ADS | Thermal IO curves for heat rates | WECC ADS |
| WECC ADS | Emissions and allowance data (EmissionFuel, EmissionAllowance) | WECC ADS |
Start costs
Description
Startup costs are modeled for thermal technologies that require discrete commitment decisions. Nuclear, solar, wind, and storage are assumed to be continuously available and do not incur startup costs in the model.
Start cost values are derived from WECC ADS thermal curves and EIA-923 fuel receipts, imputed using forecast commodity prices to estimate time-varying startup costs.
Assumptions and caveats
- Startup costs are only applied to technologies that require explicit unit commitment.
- No modeling of hot vs. cold start cost differences.
Data sources
| Source | Description | Link |
|---|---|---|
| EIA AEO | Inform variation in startup costs over time via fuel price forecasts | EIA AEO Data |
| EIA-923 | Fuel receipts and costs | EIA-923 |
| WECC ADS | Thermal IO curves for deriving startup cost parameters | WECC ADS |
Renewable capacity factors and outages
Description
Both load factors and outages profiles are modeled using CPUC SERVM capacity factors and WECC ADS hourly profiles. Each generator’s available capacity is expressed as a percentage of its nameplate capacity to calculate an empirical load factor. Nuclear outage factors are derived from NRC power status data.
For existing wind and solar generators, this observed load factor is held constant throughout the forecast horizon. New build generators are assigned load factors based on the regional average for the same technology class.
Assumptions and caveats
- Load factors and outages rates are based on a historical weather year and do not evolve over time.
- New builds inherit regional average load factors for their technology class.
Data sources
| Source | Description | Link |
|---|---|---|
| CPUC IRP | Renewable capacity factors | CPUC SERVM |
| CPUC SERVM | Capacity factors for solar and wind | CPUC SERVM |
| EIA-860 | Used to match generators to nameplate capacities | EIA-860 |
| NRC | Nuclear power status for plant outage factors | NRC Power Status |
| WECC ADS | Hourly profiles for hydro and pumped storage | WECC ADS |
Demand response
Description
Demand response is modeled as price-responsive load that can be curtailed when system conditions warrant it. Each demand response resource has a bid price derived from the marginal cost of interrupting that load — reflecting the CapEx and OpEx of the underlying facility.
The model includes seven categories of demand response:
- Data center — AI/ML
- Data center — colocation
- Data center — hyperscale
- Data center infrastructure — modeled separately because facilities can pre-cool in anticipation of curtailment, allowing cooling systems to be turned off for short periods
- EV charging infrastructure
- Hydrogen production — small volumes, highly flexible
- Bitcoin mining — fully interruptible
Assumptions and caveats
- Demand response is dispatched economically based on bid price — it enters the merit order like any other supply resource.
- Curtailment durations and volumes are constrained per resource type.