1. Reducing Variable Generation Curtailment through Flexible Transmission Expansion and Operation in the United States
Yinong Sun and Wesley Cole
35th USAEE/IAEE North American Conference, Houston, TX
Nov. 14, 2017

2. Curtailment as a potential problem with increasing variable generation
Curtailment: “Surplus Generation”
The intentional reduction in generation from Variable Generation (VG, mainly wind and solar technologies) when generation exceeds loads
Load
Net Load w/ curtailment
Minimum Gen
Curtailment
VG Profile
Net Load

3. Reasons for curtailment: Transmission infeasibility as a key driver
Causes for curtailments
Insufficient transmission capacity to export surplus power
Transmission market barriers making it uneconomical to export
Inability to store surplus energy
Fail to ramp down generation from committed thermal units …
Mitigation options for curtailments
Transmission capacity expansion
Reducing inter-regional transmission market ‘friction’
Incorporate storage technology for VG
Decrease minimum generation level of thermal units …
 What is the relationship between curtailments, transmission systems, and overall power sector capacity expansion?

4. Questions this work wants to solve
How do different levels of VG deployment, transmission expansion, and inter-regional transmission cooperation impact VG curtailment and the overall electricity sector capacity expansion?
Method:
Use a high resolution power sector capacity expansion model (ReEDS) to examine technology deployment to the year 2050
Perform scenario analyses considering different VG penetration future, transmission expansion availability, and transmission hurdle rates
Summarize results on curtailments, capacity and generation mix and total electricity system costs

5. Analysis uses the Regional Energy Deployment System (ReEDS)
Minimizes cost of 2010–2050 U.S. electric sector capacity expansion and operation
Satisfies energy and capacity requirements under resource, transmission, policy, and power system constraints
Spatial resolution
356 Wind/solar regions
134 Balancing Areas (BAs)
18 regional transmission organizations (RTOs)
Temporal resolution: 2-year sequential solution steps with 17 time-slices
Full suite of generation and storage technologies with transmission expansion
Linearized AC power flow approximation (DC power flow) for transmission representation
Statistical representation of renewable resource variability
Informative Only - Do Not Cite or Distribute

6. Transmission Expansion Transmission Hurdle Rate
Scenarios exploring the role of transmission in reducing VG curtailments
VG Penetration Future
Reference
High VG
New Transmission Allowed
No New Transmission Allowed
New Transmission Allowed
No New Transmission Allowed
Transmission Expansion
$0, $5, $10, $15/MWh hurdle rate
$0, $5, $10, $15/MWh hurdle rate
$0, $5, $10, $15/MWh hurdle rate
$0, $5, $10, $15/MWh hurdle rate
Transmission Hurdle Rate
VG Penetration Future:
Reference: assumes a business-as-usual power system evolution considering default physical, technological, and policy constraints
High VG: prescribes the level of national VG to be 10% of total generation in 2020, 25% in 2030, 40% in 2040, and 55% in 2050.
Transmission hurdle rates: represent the bilateral trading transaction costs, wheeling charges, and other transmission-related limitations among RTOs
In total 16 scenarios (2x2x4)

7. Reference capacity expansion showing increase in renewable
Growth in VG and natural gas, with declining coal and nuclear
Higher total capacity under High VG scenario due to lower capacity factors of renewable technologies relative to conventional technologies

8. Lower hurdle rates increase transmission expansion and utilization
Cumulative transmission capacity is higher under the HiVG scenario than the corresponding Reference scenario
Higher hurdle rates result in lower transmission investment and lower utilization
Transmission utilization rates are higher when transmission expansion is allowed

9. Curtailment levels are similar across scenarios
VG curtailments are higher under HiVG scenario conditions
Specific regions have much higher curtailment levels than national median
However, curtailment levels are quite similar under different transmission expansions and hurdle rates for a given VG penetration

10. Increasing marginal curtailment level with higher VG penetration
Marginal curtailment level indicates the curtailment resulting from additional unit of wind or solar capacity into grid
Higher marginal curtailment rates with increasing VG penetration

11. Capacity and generation difference from no hurdle rate case in 2050
ReEDS model changes capacity and generation mix as transmission is increasingly constrained
With increasing hurdle rates, natural gas combined cycle (NG-CC) and PV capacity are displacing wind and natural gas combined turbine (NG-CT) capacity.
Reduction in coal generation lowers the minimum generation level of coal plants and increases the flexibility of the system

12. Higher system cost with more constrained transmission systems
Total system cost defined as the present value of total cost for the entire electricity system from 2016 to 2050 at 3% discount rate
Total system cost increases as hurdle rate grows, even though the curtailment levels for the different scenarios are similar

13. Transmission cost accounts for a small percentage of total cost
Transmission capital costs only accounts for a minor portion of total system cost
When transmission expansion is allowed, higher hurdle rates indicate more difficulties in transferring power, resulting in lower transmission investments

14. Summary
VG Curtailment increases as VG penetration grows, while overall curtailment levels remain relatively low
Curtailments under different transmission assumptions are very similar
Change in capacity and generation mix – more NG-CC and PV displacing wind, NG-CT and coal – counterbalances the transmission availability and mitigates curtailment levels
More constrained transmission systems require higher cost local generation and thus higher total system cost
Additional regional cooperation has the potential to increase the system efficiency and reduce economic losses created by limitations in the ability to reduce curtailment through exports

15. Acknowledgement
NREL team: Kelly Eurek, Trieu Mai, Daniel Steinberg, Doug Arent
Project supported by U.S. DOE, Energy Efficiency and Renewable Energy

16. Thank you! Yinong.sun@nrel.gov

17. Appendix

18. ReEDS approach: transmission power flow
Pipe flow:
Power flows from one region to another without respect to the rest of the network
Approximate DC flow:
Power flow: obeys Kirchhoff's voltage law, flows are determined by generation, load, and line susceptances
DC: real power only; ignores reactive power
Linear: approximation that phase angle differences are small—necessary for use in linear optimization.
Pipe Flow: ReEDS chooses route.
Approximate DC Flow: Route is determined by transfers and network.

19. Approximate DC Flow vs. Pipe Flow in ReEDS
Eq.
Node balance
𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑖𝑜 𝑛 𝑗 −𝐿𝑜𝑎 𝑑 𝑗 = 𝑖 𝐹𝑙𝑜 𝑤 𝑖,𝑗
(1)
𝐹𝑙𝑜 𝑤 𝑖,𝑗 = 𝐴𝑛𝑔𝑙 𝑒 𝑖 −𝐴𝑛𝑔𝑙 𝑒 𝑗 ×𝑆𝑢𝑠𝑐𝑒𝑝𝑡𝑎𝑛𝑐 𝑒 𝑖,𝑗
(2)
Flow constraint
𝐹𝑙𝑜 𝑤 𝑖,𝑗 ≤𝐿𝑖𝑛𝑒 𝐶𝑎𝑝𝑎𝑐𝑖𝑡 𝑦 𝑖,𝑗
(3)
Equation (1) models Kirchhoff’s current law
Equation (2) is the difference between approximate DC flow and pipe flow: approximate DC flow represents power flowing in a transmission line to be a linear function of its susceptance times the angle difference between sending and receiving nodes
In approximate DC flow, more susceptible lines attract more flows
Equation (3) is the flow limit constraint

20. Transmission parameter calculation
𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑓𝑙𝑜𝑤= 𝑝,𝑚 𝑛 𝐹𝑙𝑜𝑤 𝑛,𝑝,𝑚 −𝐹𝑙𝑜𝑤 𝑝,𝑛,𝑚 ×𝐻𝑚
𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒, 𝑓𝑙𝑜𝑤 𝑏𝑎𝑠𝑒𝑑= 𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑓𝑙𝑜𝑤 (𝑇𝑊ℎ) 𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑇𝑊ℎ) = 𝑝,𝑚 ( 𝑛 𝐹𝑙𝑜𝑤 𝑛,𝑝,𝑚 −𝐹𝑙𝑜𝑤 𝑝,𝑛,𝑚 ×𝐻𝑚) 𝑝 ( 𝑛 𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑛,𝑝) ×8760)
* 𝐹𝑙𝑜𝑤(𝑛,𝑝,𝑚) represents the power flow tranferred from node n to p at time slice m
* 𝐻 𝑚 represents the hours in each time slice in ReEDS, where m is one of 17 time slices per year in ReEDS
* Transmission losses are not accounted in the calculation of transmission flow and net imports

21. Curtailment level in the U.S.
Curtailment levels in the U.S. by regions,
source: Bird, Cochran, and Wang 2014

22. ReEDS current curtailment method
Statistical estimate
Difference in surplus between a system with VG and a system without
Total Surplus with VG
Total Surplus without VG −

23. ReEDS approach: curtailments
We want to know the amount of surplus associated with VRRE, which can be approximated as the difference in surplus between a system with VRRE and a system without.
Define surplus for a system without VRRE as a random variable S that equals the must-run baseload generation M minus load L
S = M – L
Assuming S is normally distributed, the total surplus can be calculated as the area underneath the probability density function of S, f(s), such that s>0.
𝑆 𝑇 = 0 ∞ 𝑓 𝑠 𝑑𝑠
Next, define surplus for a system with VRRE R’ as a random variable S’
S’ = M – L + R’
Assuming S’ is normally distributed, with a probability density function g(s’), the total surplus the system with VRRE is
𝑆 ′ 𝑇 = 0 ∞ 𝑔 𝑠 ′ 𝑑𝑠 ′
The surplus for VRRE is the difference of 𝑆 ′ 𝑇 and 𝑆 𝑇
Total Surplus without VRRE ST
Total Surplus with VRRE
S’T

24. Curtailments
Increase in energy below zero-power corresponds to VG curtailments.

25. Regional curtailment level

26. Regional Wind Capacity Change

27. Regional Solar Capacity Change

28. Curtailment by wind and solar

29. Additional system cost from $0 hurdle rate case (percentage)