Our system-wide WECC simulation runs a day-ahead market at hourly granularity across the entire modeling horizon. As such, outputs such as price, generation output, transmission flows, etc. are all determined at the hourly level. Our modeling horizon extends to 2050.
The model uses zonal modeling throughout, covering 13 WECC Balancing Authorities plus a number of smaller utilities, with a particular focus on SCE, SDGE, and PG&E.
Inputs
The table below summarizes the key input types to our model, and provides a high-level description of how each input is constructed alongside key data sources used to inform our assumptions. Further details for each of these inputs can be found at the links provided.
| Input Type | Input | Summary | Key Data Sets |
|---|---|---|---|
| Generation | Capacity buildout | Capacity values are determined by our Capacity Expansion Model and buildout constraints are informed from historical Interconnection Queue data | WECC ADS, NREL ATB |
| Generation | Renewable load factors and outages | Renewable resource availability and outage profiles are empirically modeled using historical data to capture seasonal and hourly variability. | CPUC SERVM, WECC ADS, NRC |
| Generation | Start costs | Start costs for thermal technologies are determined empirically based on historical data and forecast fuel prices. | WECC ADS, EIA-923, EIA AEO |
| Generation | Short-run marginal costs | Short-run marginal costs (SRMCs) are empirically estimated for each generation site using historical pricing data combined with forward-looking fuel commodity price forecasts. | WECC ADS, EIA-923, CPUC SERVM, CPUC GHG |
| Demand | Zonal Demand | Zonal demand is modeled hourly at the balancing authority level, combining load zone shapes with growth assumptions extending to 2050. | CPUC SERVM, CAISO OASIS, EIA-930 |
| Transmission | Zonal Transmission Network | The zonal transmission network is modeled as transfer capacities between balancing authorities, reflecting inter-zonal path ratings and constraints. | CPUC SERVM, WECC ADS, NREL NTP |
Modeling
Alongside the core modeling functionality described here, there are additional market features modeled in our representation of the WECC system.
Unit Commitment
Unit commitment refers to the modeling of generator on/off decisions through binary variables that determine whether a generating unit is online or offline at any given hour.
In the model, a binary commitment variable is assigned to each thermal generating unit. Operational limits — specifically minimum and maximum generation levels — are conditional on this commitment status. When a unit is online, it must operate within its defined minimum stable output and maximum output levels. When offline, a unit’s output is constrained to zero.
Reserve Margin
Reserve margin refers to the amount of available generation capacity above expected system demand, maintained to ensure grid reliability in the event of unexpected contingencies such as generator outages or rapid demand spikes.
In the model, reserve margin is proxied by measuring available headroom across dispatchable thermal generation and energy storage assets across the whole system. A fixed system-wide operating margin is enforced, reflecting CAISO’s operating reserve requirements.
Outputs
Macro databook
The Macro Databook summarizes key system-level outputs with yearly granularity, capturing installed generation capacity by technology type, generation volumes, commodity prices, zonal electricity prices, and price spreads. Provided in CSV format, it represents Modo Energy’s proprietary view on capacity expansion pathways, future commodity prices, and market dynamics.
Site specific databook
The site specific databook provides detailed monthly and annual performance metrics for individual battery assets, including cycling behavior, merchant, and ancillary service revenues. Cycling counts and prices are averaged over each period, while total revenues are also presented on a per MW basis, to facilitate asset benchmarking and investment evaluation.