2.1 Overview
The US-REGEN electric sector model is a detailed dispatch and capacity expansion model of the US electric system. It includes a partially disaggregated representation of both existing generation unit capacity and the hourly profiles of load, wind speed, and solar flux. These details allow the model to explicitly evaluate dispatch decisions (when and for how long installed capacity operates) as distinct from capacity decisions (new investment, retrofit, or retirement).
Several unique features of the electric sector make the treatment of such details essential to accurately model these decisions and the impact of new policies:
The "shape" or hourly profile of end-use demand and variable resource availability is crucial for appropriately characterizing the operational patterns and profitability or value of different types of capacity.
These patterns and hence the value of generating assets are also dependent on the mix of installed capacity in a region (and in neighboring regions).
Capital investments in generating capacity tend to be long-lived, creating a strong link between dispatch and investment decisions across time periods.
The electric sector model is formulated as an optimization over several time periods balancing the costs incurred by electric sector producers with the value to electricity consumers. The decision variables include both levels of capacity by region and technology type and the dispatch of these "blocks" of capacity across a range of "segments" that represent the intra-annual profile of load and variable resource availability. Each segment is a block of time that is "representative" of anywhere from one hour to over two hundred hours out of the 8760 hours in a given year. The hours represented by one segment are usually not contiguous. In addition, power may flow between adjacent regions during each segment subject to available bilateral transfer capacity.
The costs incurred by producers include variable costs that scale with dispatch (mainly fuel and variable operating and maintenance (VOM) costs), fixed operating and maintenance (FOM) costs that scale with installed capacity, and investment costs associated with new capacity additions (of both generating and inter-region transfer capacity). The optimization considers the time paths of each of these variables and their associated costs simultaneously, subject to a discount rate reflecting the opportunity cost of capital, even though the costs themselves are incurred on very different schedules.[1]
Electricity demand in any given iteration of the electric sector model is treated as a fixed exogenous quantity. Typically, the load profile is specified as an output of the end-use model, though the electric model can also be run in stand-alone mode with any exogenous load profile (e.g. historical or observed data). The electric sector model outputs electricity prices that serve as an input to endogenous demand decisions in the end-use model. Demand elasticity is simulated by allowing the price output of the electric sector model and the quantity output of the end-use model to converge over multiple iterations, which provides a richer representation of the responsiveness of demand to prices than a simple elasticity. When running the electric sector model in stand-alone mode, elastic demand can be approximated with a linear demand function calibrated to given reference point (e.g. price / quantity pair across regions and time steps in a reference run with fixed demand).
The model optimizes by minimizing the costs of meeting the given level of demand (see Figure 2‑1) in each segment. These costs are summed across regions and time periods and discounted to present value. Importantly, the requirement that demand is met in every segment, in addition to a reserve margin constraint on local firm capacity, simulates the clearance of both an energy market and a capacity market. That is, by requiring that sufficient electricity be produced in each segment to meet the prescribed load, this constraint also stipulates indirectly that sufficient investment in capacity occur such that electricity for the prescribed load in the "peak segment" will be available for dispatch, plus a reserve margin. As will be discussed in more detail below, this stipulation applies even with large deployment of variable renewable capacity which is known to have low coincidence with peak demand, such as wind.
The electric sector model is a partial equilibrium model, meaning that the optimization extends only to the electric sector and does not explicitly account for choices and feedbacks in related markets. These interactions are incorporated through the iterative process outlined above and described in detail in Chapter 3.
When the price elasticity of demand is assumed to be zero, the electric sector model minimizes (the present value across time and regions of) total producers' costs, represented by the area labeled A. This demand can be an output of the end-use model, or an exogenous projection can be used.
Dispatch in the dynamic electric model is by increasing order of marginal generation cost; i.e. units with the lowest variable costs per MWh are dispatched first. This omits unit commitment constraints, due to both computation constraints on including integer constraints in a linear optimization, and to unit aggregation rendering constraints such as ramp rates less meaningful. A unit commitment variant of the US-REGEN electric model can be used to explore the impact of these constraints in more detail for a single year, using the capacity mix from a dynamic electric model scenario with identical assumptions. This unit commitment variant is described in Section 2.8, and in more detail in EPRI publication 3002004748 (EPRI, 2015).
Note that investment is assumed to be uniformly distributed across the years within each 5-year time period. ↩︎