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

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

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?

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

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flow) for transmission representation Statistical representation of renewable resource variability Informative Only - Do Not Cite or Distribute

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)

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

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

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

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

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

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

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

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

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

Thank you! Yinong.sun@nrel.gov

Appendix

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.

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

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

Curtailment level in the U.S. Curtailment levels in the U.S. by regions, 2007-2012 source: Bird, Cochran, and Wang 2014

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 −

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

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

Regional curtailment level

Regional Wind Capacity Change

Regional Solar Capacity Change

Curtailment by wind and solar

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