Electricity Delivery and Storage
Inter-Regional Transmission
The electric model allows for inter-regional transfers of power using a bubble-and-spoke representation. In each segment or dispatch period, the amount of power transfer between a pair of regions is limited by the total transmission capacity between them.[1] The source for base year data is currently the inter-regional transmission capacity used by the National Renewable Energy Laboratory's ReEDS model (NREL 2017), except for lines starting or ending in New York, which are informed by NYISO's 2016 Reliability Needs Assessment (NYISO, 2016). An alternative set of assumptions derived from EPA's IPM 5.13 model (EPA 2017) is occasionally used to test the sensitivity of model results to transmission assumptions. These data are mapped to the model regions used by US-REGEN. Figure 2‑4 shows the existing power transfer capacity between the default 16 regions. Power flows between regions are subject to line losses based on the distance between the two regions. For every 100 miles of long-distance transmission, US-REGEN assumes 0.5% power losses. US-REGEN allows additional transmission capacity to be installed between regions at a cost of $3.85 million per mile for a notional high voltage line (e.g. 500kV AC or 800kV DC) to transfer 6400 MW of capacity.
The electricity transmission system is complex in terms of planning, operation, and organization. In many scenarios, including the reference scenario, additional build limits are imposed to reflect difficulties with siting or public acceptance. These limits have been generated in conjunction with experts from EPRI's Power Delivery and Transmission sector and take two forms. The first is a national constraint on total new transmission builds in GW-miles, equal to a 10% increase in the first decade, a 15% increase in the second decade, and a 20% increase in the third decade and beyond, relative to 2010 transmission capacity. There is an optimistic version of this constraint which doubles these percentages. These numbers are drawn from considering historical build rates for new transmission capacity. The second constraint is a limit on the amount of new transmission capacity that can be built between any two regions, by time. This is equal to 1GW by 2020, 4GW by 2025, 8GW by 2030, 16GW by 2035, and unlimited (but totals still subject to the national constraint) thereafter.
The EIA State Energy Data System (EIA November 2015) provided data on historical electric energy flows between states and regions, and data on international exports and imports, in addition to regional prices. These data were used in the model calibration process. In the current version of the model, international imports and exports of electricity are assumed to hold constant over time, at the most recently available historical levels determined from SEDS (2015). This includes electricity traded with Canada and Mexico. Figure 2‑5 shows the 2015 net trade positions (after accounting for transmission and distribution losses) for the default 16 regions in US-REGEN.
Intra-Regional Transmission and Distribution
While inter-regional transmission capacity and dispatch is modeled explicitly, most of the delivery system for electricity entails intra-regional transmission and distribution. US-REGEN does not explicitly resolve the electricity network below the level of model regions, but it does include estimated costs for expanding and maintaining the grid. These estimates are based partly on the extent of wind and solar deployment, but more generally they scale with electricity demand from the end-use sectors.
New wind and solar capacity incurs a one-time charge of $250 per kW and $100 per kW respectively to reflect the incremental transmission investment required to incorporate generally remotely located wind and solar capacity within a region. This number is based on a combination of discussions with internal and external transmission experts and a review of the relevant literature (for example see Mills et al. (2009), Jaske (2010)). There is no added transmission charge for repowered wind (i.e. new wind turbines replacing existing turbines at existing sites). An incremental distribution charge for distributed PV is included as described in the Distributed Energy Resources section.
General expenditures on transmission and distribution within a region are captured as a component of the retail price for delivered electricity. The levelized costs of delivery from the wholesale power market to end-use sectors are based on observed differences in wholesale and retail prices in current EIA data. These costs are summarized in Table 1, denominated in both kWh and mmbtu for comparison with non-electric fuel delivery costs.
| Residential / Home Charging | Commercial / Public/Fleet Charging | Industry | |
|---|---|---|---|
| cents / kWh | 6.7 | 4.4 | 1.6 |
| $ / mmbtu | 19.6 | 12.9 | 4.6 |
Storage
US-REGEN represents the key structural features of electricity storage. The model endogenously determines investment levels and dispatch of storage on an hourly basis. Storage investment, charge, and discharge decisions are co-optimized with other technology investment and dispatch decisions. By default, US-REGEN represents four possible storage technology classes, and other technologies can easily be added. These storage classes include pumped hydro, compressed air, concentrated solar power, and a variety of configurations of battery storage. Each technology carries a charge penalty, which represents the ratio of input to output energy. Only compressed air has greater output than input because it also takes a natural gas input (1.44GJ/MWh) that converts at a loss to electricity. Each technology has an assumed lifetime for new and existing builds. No new pumped hydro is considered, due to lack of resource data. Concentrated solar includes the costs for the power block as well as the solar field and receiver and the storage unit must charge from its own field.
EPC stands for 'Engineering, Procurement, and Construction'. CAGR stands for 'Compound Annual Growth Rate'.
US-REGEN's characterization of battery costs is based on the EPRI Energy Storage Technology and Cost Assessment of the state of electricity storage costs (EPRI, 2018) which includes a comparison of multiple analyses and specifies cost ranges for lithium ion and flow batteries. Battery cost projections include costs of the system, grid integration equipment, fixed and variable maintenance, and system decommissioning. As illustrated in Figure 2‑13 above, the report finds that total costs for a 4-hour battery system could fall to around $840/kW in 2030, with further declines over time. In US-REGEN, battery storage costs are represented as a linear function of both nominal output or power capacity (the "door"), expressed in $/kW, and nominal energy capacity (the "room"), expressed in $/kWh, so the total cost projections from the report are disaggregated into these "door" and "room" costs for use in the model. Unless specifically fixed for a given technology, the model can endogenously choose the ratio of energy capacity to output capacity, i.e. the duration of the system. Carried charge is assumed to have a loss rate of 10 percent per month.
| Pumped Hydro | Compressed Air | Concentrated Solar Power | Battery | |
|---|---|---|---|---|
| Indicative 2030 “Door” Cost [$/kW] | N/A | $1,500 | $900 (power block) | $100 |
| Indicative 2030 “Room” Cost [$/kWh] | N/A | $100 | $15 (storage); also costs for solar field and receiver | $100 |
| Duration [hours] | 20 | Endogenous | Endogenous | Endogenous |
| Charge Penalty | 1.2 | 0.8* | 1% loss per day | 1.1 |
| Lifetime [years] | 100 | 30 | 60 | 20 |
| Notes | No new investment considered | Natural gas input (1.44 GJ/MWh) | Must charge from its own field | Loss rate for carried charge (10%/month) |
*Additional natural gas input means <1MWh electricity needed for 1MWh of output
US-REGEN's dynamic formulation uses an aggregation of representative hours into load segments to significantly speed up computation.[2] This creates challenges for representing storage effectively, as chronology is lost by construction. Storage technologies are therefore typically only turned on for static model runs that use all 8760 hours. EPRI is currently testing possible approaches to represent storage in a smaller number of segments. However, the static model with full 8760 hourly resolution continues to offer the best assessment of the constraints and economic potential of integrating storage.
This approach is also known as a pipeline model, albeit with a very high level of aggregation. It does not take into account the network effects inherent in Kirchoff's laws. ↩︎
See Section 2.5 Design of Aggregated Segments for more details. ↩︎