End-Use Model
Overview
The US-REGEN end-use model represents trade-offs between end-use technologies and fuels for a wide range of disaggregated sectors and activities with economy-wide coverage. The model includes structural detail across several dimensions relevant for fuel and technology choice, such as building size, type, and vintage, climate zone and location, and vehicle ownership and driving intensity. Within each structural category, service demand may be met with a range of options, characterized as combinations of fuels and technologies. The model evaluates the total cost of each option in each new vintage based on assumed technology cost and performance, fuel prices, structural attributes of service demand, and non-economic factors. The resulting allocation across the options is based on a logit model translating relative costs to equilibrium market shares, with a lagged process to simulate a gradual transition toward the model's calculated equilibrium shares. The model then calculates annual and hourly fuel use by region as a function of the resulting mix of end-use technologies. The electricity demand profile is provided as input to the electric sector model, the solution of which generates updated prices that are returned to the end-use model (wholesale electricity prices from the electric model are translated to end-user retail prices assuming existing rate structures). This process is iterated to convergence.
There are three main elements to the model: a buildings model describing dual-fuel building uses (e.g. space heating and cooling, water heating, cooking, and clothes-dryers); a passenger vehicles model describing light-duty vehicles for personal transportation; and a more generalized end-use model describing electric-only building uses (e.g. lighting, electronics, appliances, and ventilation), industrial energy use, and heavy-duty transportation.
A full break-out of the sectors, activities, end-uses, and technologies included the model is shown in Figure 3‑1.
Interaction with Electric Model
Once the end-use model has projected energy demands across the economy over the model time horizon for each of the individually modeled structural classes within each region, an hourly load shape for electricity demand is calculated for each end-use.
For space heating and cooling, the load shape is based on the hourly temperature profile for a given year. All load shapes, as well as renewable resource profiles, are based on the same representative year to ensure that the joint distribution is captured appropriately. In the buildings model, energy use for each temperature band was calculated to inform long-run average annual energy use. These same calculations are used to derive hourly energy consumption in the representative year.
For vehicle charging, the load shape is constructed as described above as a linear combination of three exogenous charging patterns. These patterns are specified for 24 diurnal hours, which are mapped onto the corresponding 8760 hours of the representative year. This same hourly profile is assumed to apply to non-passenger transportation uses of electricity.
For other building uses, including lighting, water heating, electronics, and appliances, and a generic industrial end-use, EPRI has developed a load shape library to describe typical diurnal profiles by season and day type (i.e. weekday vs. weekend)—see Figure 3‑17 for examples. These profiles are similarly mapped to the corresponding 8760 hours to generate annual load shapes.
These calculations result in a different aggregate load profile for each region in each time period as the load mix across end-uses changes. For this reason, the representative hour procedure described in the electric model's Design of Aggregated Segments is repeated for each time step, generating a time-dependent set of representative hours to capture the changing relative distribution of load vs. wind and solar.
Distributed Energy Resources
The electric sector model is designed to represent investment and dispatch in a competitive wholesale market in equilibrium. In contrast, distributed energy resources (DER) compete in the retail market, which is linked to wholesale markets but operates differently. These differences motivate the representation of DER adoption in a separate module within the integrated US-REGEN model.
The DER retail market penetration model simulates potential adoption of distributed technologies over time given assumptions are the rate structures faced by residential and commercial consumers. At present, the model represents rooftop solar PV adoption only and assumes the current rate environment by default where installing behind-the-meter generation offsets retail purchases at flat volumetric rates. DER investments are considered from the perspective of retail customers using price outputs from electric sector runs. As described below, DER adoption is characterized as a gradual diffusion toward a potential adoption rate based on payback period calculations with heterogeneity across customers. The deterministic model examines fundamental DER economic and behavioral drivers at a high level and includes variation in the value of DER to customers based on state-level retail prices, available incentives, resource quality, attitude toward self-generation, and time preference.