NREL: Regional Energy Deployment System (ReEDS): Qualitative model description

ReEDS minimizes systemwide costs of meeting electric loads, reserve requirements, and emission constraints by building and operating new generators and transmission in 23 two-year periods from 2006 to 2050. The primary outputs of ReEDS are the amount of capacity and generation of each type of prime mover—coal, natural gas, nuclear, wind, etc.—in each year of each two-year period. Figure 1 shows an example of ReEDS capacity estimates for the United States for different generation technologies over the 44 year evaluation period.

Time in ReEDS is also subdivided within each two-year time period; each year is divided into four seasons, and each season into four diurnal time-slices. There is also one superpeak time-slice. These 16 annual time-slices (spring has only three time-slices) allow ReEDS to capture the intricacies of meeting electric loads that vary throughout the day and year both with conventional and renewable generators.

While ReEDS includes all major generator types, it has been designed primarily to address the market issues of greatest significance to carbon-constrained scenarios—renewable portfolio standards (RPS), carbon taxes, and carbon caps. As a result, renewable and carbon-free energy technologies are a focus.

Diffuse resources, such as wind and solar power, come with concerns that conventional dispatchable power plants do not have, particularly regarding transmission and resource variability. The ReEDS model examines these issues primarily by using a much higher level of geographic disaggregation than other models: 356 different regions in the continental United States. These 356 resource supply regions are then grouped into four levels of larger regional groupings— balancing authorities, regional transmission operators (RTO), North American Electric Reliability Council (NERC) regions, and national interconnect regions. States are also represented for the inclusion of state policies.

Much of the data inputs to ReEDS are tied to these regions and derived from a detailed GIS model/database of the wind and solar resource, transmission grid, and existing plant data. The geographic disaggregation of renewable resources allows ReEDS to calculate transmission distances, as well as the benefits of dispersed wind farms or CSP plants supplying power to a demand region. Both the wind and solar supply curves are broken up into five resource classes, based on the quality of the resource—strength and dependability of wind or solar insolation—that are further described in the appropriate sections of this document.

Regarding resource variability and grid reliability, ReEDS also allows electric storage to be built—either co-located with wind farms or sited at load centers—and used for load shifting, resource firming, and ancillary services. Three varieties of storage are supported: pumped hydropower, batteries, and compressed air energy storage.

Along with wind and solar power, ReEDS has supply curves for biomass and geothermal resource and allows biopower and geothermal plants to be built in each balancing authority. The geothermal supply curve is in MW of recoverable capacity while the biomass supply curve is in MMBtu of annual feedstock production.

Other carbon-reducing options are considered as well. Nuclear power is an option, as is carbon capture and sequestration (CCS) on some coal and natural gas plants. For now, CCS is treated simply, with only an additional capital cost for the extra equipment and an efficiency penalty to account for the parasitic loads of the separation process. In the future, it is intended that ReEDS will have geographically varying costs for CCS as well as piping and sequestering constraints on the CO₂.

The major conventional electricity generating technologies considered in ReEDS include: hydropower; both simple- and combined-cycle natural gas; several varieties of coal; oil/gas steam; and nuclear. These technologies are characterized in ReEDS by their:

Renewable and storage technologies are governed by similar parameters, accounting for fundamental differences, of course. For instance, heat rate is replaced with round-trip-efficiency for storage technologies, and the dispatchability parameters—fuel cost, heat rate, turndown ratio, quickstart, and operating reserve capability—are not used for non-dispatchable wind and solar.

The model includes consideration of distinguishing characteristics of each conventional generating technology. For example, there are several types of coal-fired power plants within ReEDS, including gasification, biomass cofiring, and CCS options. Any of these plants can burn either high-sulfur or, for a cost premium, low-sulfur coal. Generation by coal plants is restricted to be base- and intermediate load with cost penalties (representing ramping/spinning costs) if power production during peak load periods exceeds production in shoulder-peak hours. New coal plants are assumed to be able to provide more spinning reserve capability than older units. Combined-cycle natural-gas plants are considered to be able to provide some operating/spinning reserve and quick-start capability, while simple-cycle gas plants can be cheaply and easily used for reserves and quickstarts. Nuclear power is considered to be base load. Hydroelectricity is not allowed to increase in capacity, due to resource and environmental limitations. Hydropower is also energy-constrained, due to water resource limitations, but is assumed to be able to provide both quick-start capability and operating/spinning reserve.

Retirements of conventional generation can be modeled either through exogenous specification of planned retirements (currently used for nuclear, hydro, and oil/gas steam plants), economic retirements, or as a fraction of remaining capacity each period. All retiring wind turbines are assumed to be refurbished or replaced immediately—because the site is already developed with transmission access and other wind farm infrastructure, and the cost of wind energy technology is only getting cheaper relative to mature technologies while the fuel cost of conventional generation is generally assumed to continue to climb. Similarly, any storage at the wind site is assumed to be replaced immediately upon retirement while grid-sited storage retires automatically when its assumed lifetime has elapsed but is not automatically replaced.

ReEDS tracks emissions from both generators and storage technologies of carbon, sulfur dioxide, nitrogen oxides, and mercury. Caps can be imposed at the national level on any of these emissions (and constraints could be writted to impose caps at state or regional levels as well). There is also the option of applying a carbon tax instead of a cap; the tax level and ramp-in pattern can be exogenously defined.

ReEDS is a national electric capacity expansion model, not a general equilibrium model. To define each time period of the optimization, the model requires that the scenario be exogenously specified in terms of fuel costs and electric loads for each NERC region over the 44-year time horizon of ReEDS. To allow for the evaluation of scenarios that might depart significantly from the scenario used to develop the input fuel prices and electricity demands, there are price elasticities of demand and demand elasticities of fuel prices integrated into the model. For demand, the exogenously defined demand escalation is adjusted up or down based on the price of electricity; while for coal and natural gas, the price is adjusted based on how the calculated fuel usage compares to the usage assumed in the inputs.

Background of Model

Qualitative model description

Supporting Documents