The curtailment paradox in the transition to high solar power systems

Abstract

•Curtailment varies by thermal flexibility, operating reserve rules, and other factors•Thermal generator flexibility matters most at mid-PV (25%–40% penetration) levels•System cost and curtailment decline when VRE and storage provide operating reserves•PV gens suppress their revenue potential from operating reserves when providing them The adoption of PV and battery storage has accelerated globally in recent years, driven by rapid cost declines. A corresponding increase in curtailment is also anticipated as PV growth continues. Although excessive curtailment can affect resource financial viability, economic curtailment is a new normal in grid operations by providing flexibility to ensure grid reliability. This study systematically explores the effect of other flexibility options on curtailment levels as PV penetrations grow. These include battery storage, the operational flexibility of thermal generators, transmission, and allowing VRE and storage to provide operating reserves, among others. This study provides specific insights to (1) grid planners and operators on the particular importance of thermal generator operations at mid-PV penetration levels (25%–40%) and (2) market designers on the potential need to revise operating reserve eligibility rules and compensation structures as PV penetrations increase. Rising penetrations of variable renewable energy (VRE) in power systems are expected to increase the curtailment of these resources because of oversupply and operational constraints. We evaluate the effect on curtailment from various flexibility approaches, including storage, thermal generator flexibility, operating reserve eligibility rules, transmission constraints, and temporal resolution, by using a highly resolved realistic system. Results reveal two aspects of a curtailment paradox as the system evolves to higher solar penetration levels. First, thermal generator parameters, especially in restricting minimum operating levels and ramp rates, affect VRE curtailment more in mid-PV penetration levels (∼25%–40%) but much less at lower (∼20%) or higher (∼45%) PV penetration levels. Second, although allowing VRE and storage to provide operating reserve results in significant operating costs and curtailment benefits, the price suppression effect from these resources reduces incentives for PV to provide operating reserves with curtailed energy. Rising penetrations of variable renewable energy (VRE) in power systems are expected to increase the curtailment of these resources because of oversupply and operational constraints. We evaluate the effect on curtailment from various flexibility approaches, including storage, thermal generator flexibility, operating reserve eligibility rules, transmission constraints, and temporal resolution, by using a highly resolved realistic system. Results reveal two aspects of a curtailment paradox as the system evolves to higher solar penetration levels. First, thermal generator parameters, especially in restricting minimum operating levels and ramp rates, affect VRE curtailment more in mid-PV penetration levels (∼25%–40%) but much less at lower (∼20%) or higher (∼45%) PV penetration levels. Second, although allowing VRE and storage to provide operating reserve results in significant operating costs and curtailment benefits, the price suppression effect from these resources reduces incentives for PV to provide operating reserves with curtailed energy. IntroductionA common attribute of power systems with increasing penetration levels of variable renewable energy (VRE) is a corresponding—and often non-linear—increase in the frequency and magnitude of curtailed energy.1Jenkins J.D. Luke M. Thernstrom S. Getting to zero carbon emissions in the electric power sector.Joule. 2018; 2: 2498-2510Abstract Full Text Full Text PDF Scopus (99) Google Scholar, 2Sepulveda N.A. Jenkins J.D. de Sisternes F.J. Lester R.K. The role of firm low-carbon electricity resources in deep decarbonization of power generation.Joule. 2018; 2: 2403-2420Abstract Full Text Full Text PDF Scopus (185) Google Scholar, 3Sun Y. Wachche S.V. Mills A. Ma O. 2018 Renewable Energy Grid Integration Data Book. National Renewable Energy Laboratory, 2020Google Scholar, 4Frew B. Cole W. Denholm P. Frazier A.W. Vincent N. Margolis R. Sunny with a chance of curtailment: operating the US grid with very high levels of solar photovoltaics.iScience. 2019; 21: 436-447Abstract Full Text Full Text PDF PubMed Scopus (21) Google Scholar, 5Bird L. Lew D. Milligan M. Carlini E.M. Estanqueiro A. Flynn D. Gomez-Lazaro E. Holttinen H. Menemenlis N. Orths A. et al.Wind and solar energy curtailment: a review of international experience.Renew. Sustain. Energy Rev. 2016; 65: 577-586Crossref Scopus (274) Google Scholar, 6Frew B.A. Becker S. Dvorak M.J. Andresen G.B. Jacobson M.Z. Flexibility mechanisms and pathways to a highly renewable US electricity future.Energy. 2016; 101: 65-78Crossref Scopus (109) Google Scholar, 7Hitaj C. Location matters: the impact of renewable power on transmission congestion and emissions.Energy Policy. 2015; 86: 1-16Crossref Scopus (31) Google Scholar, 8Golden R. Paulos B. Curtailment of renewable energy in California and beyond.Electr. J. 2015; 28: 36-50Crossref Scopus (64) Google Scholar, 9Bird L. Cochran J. Wang X. Wind and solar energy curtailment: experience and practices in the United States.https://www.nrel.gov/docs/fy15osti/63054.pdfDate: 2014Google Scholar Curtailment is a reduction in scheduled energy delivery when generation exceeds demand and/or system conditions impose operational constraints that preclude all the available energy from being utilized.3Sun Y. Wachche S.V. Mills A. Ma O. 2018 Renewable Energy Grid Integration Data Book. National Renewable Energy Laboratory, 2020Google Scholar,5Bird L. Lew D. Milligan M. Carlini E.M. Estanqueiro A. Flynn D. Gomez-Lazaro E. Holttinen H. Menemenlis N. Orths A. et al.Wind and solar energy curtailment: a review of international experience.Renew. Sustain. Energy Rev. 2016; 65: 577-586Crossref Scopus (274) Google Scholar,9Bird L. Cochran J. Wang X. Wind and solar energy curtailment: experience and practices in the United States.https://www.nrel.gov/docs/fy15osti/63054.pdfDate: 2014Google Scholar Curtailment of renewables results from oversupply and a lack of system flexibility, which can include transmission congestion, minimum generation levels of thermal generators or hydropower, or back-feeding in the distribution system.10Lew, D., Bird, L., Milligan, M., Speer, B., Wang, X., Carlini, E.M., Estanqueiro, A., Damian, F., Emilio Gomez-Lazaro, N.M., et al. (2013). Wind and solar curtailment. Preprint. In (NREL CP-5500-60245).Google Scholar, 11Denholm P. Brinkman G. Mai T. How low can you go? The importance of quantifying minimum generation levels for renewable integration.Energy Policy. 2018; 115: 249-257Crossref Scopus (24) Google Scholar, 12Bistline J.E. Turn down for what? The economic value of operational flexibility in electricity markets.IEEE Trans. Power Syst. 2018; 34: 527-534Crossref Scopus (23) Google Scholar, 13Jorgenson J. Mai T. Brinkman G. Reducing wind curtailment through transmission expansion in a wind vision future.https://www.nrel.gov/docs/fy17osti/67240.pdfDate: 2017Google Scholar, 14O’Shaughnessy E. Cruce J.R. Xu K. Too much of a good thing? Global trends in the curtailment of solar PV.Sol. Energy. 2020; 208: 1068-1077Crossref PubMed Scopus (32) Google ScholarThe large quantity of economic curtailment that is observed in grid integration studies with very high VRE penetration levels and is also suggested by empirical evidence reflects a possible paradigm shift in how future power systems will operate. Curtailment might be a “new normal” for everyday operations,4Frew B. Cole W. Denholm P. Frazier A.W. Vincent N. Margolis R. Sunny with a chance of curtailment: operating the US grid with very high levels of solar photovoltaics.iScience. 2019; 21: 436-447Abstract Full Text Full Text PDF PubMed Scopus (21) Google Scholar,15E3. (2014) Investigating a Higher Renewables Portfolio Standard in California (Energy and Environmental Economics). https://www.ethree.com/wp-content/uploads/2017/01/E3_Final_RPS_Report_2014_01_06_with_appendices.pdf.Google Scholar as the ability to curtail output from VRE sources is an important source of flexibility by helping to maintain supply-and-demand balance and system frequency. It is also increasingly seen as a potential source for operating reserves.16Nelson J. Kasina S. Stevens J. Moore J. Olson A. Morjaria M. Smolenski J. Aponte J. Investigating the economic value of flexible solar power plant operation.https://www.ethree.com/wp-content/uploads/2018/10/Investigating-the-Economic-Value-of-Flexible-Solar-Power-Plant-Operation.pdfDate: 2018Google Scholar This new normal idea is supported by utility planning and operations that account for a certain level of curtailment, or availability, of VRE resources.17California I.S.O. Managing oversupply.http://www.caiso.com/informed/Pages/ManagingOversupply.aspxDate: 2019Google Scholar,18APS 2017 integrated resource plan.https://www.aps.com/-/media/APS/APSCOM-PDFs/About/Our-Company/Doing-business-with-us/Resource-Planning-and-Management/2017IntegratedResourcePlan.ashxDate: 2017Google ScholarAlthough there is a general acknowledgment that a lack of system flexibility leads to curtailment, there is no clear understanding of the importance of individual system contributors to curtailment, particularly in systems with high VRE penetration levels. Previous work has shown that curtailment can be substantially reduced by changing the operational practices of solar photovoltaic (PV) plants or by changing the flexibility of thermal plants.16Nelson J. Kasina S. Stevens J. Moore J. Olson A. Morjaria M. Smolenski J. Aponte J. Investigating the economic value of flexible solar power plant operation.https://www.ethree.com/wp-content/uploads/2018/10/Investigating-the-Economic-Value-of-Flexible-Solar-Power-Plant-Operation.pdfDate: 2018Google Scholar,19Palchak D. Denholm P. Impact of generator flexibility on electric system costs and integration of renewable energy.https://www.nrel.gov/docs/fy14osti/62275.pdfDate: 2014Google Scholar Several works have highlighted the importance of minimum generation levels of thermal units, demonstrating that reducing these levels can result in favorable changes to not only VRE curtailment but also to plant operating hours, startups, maintenance costs, system-wide operating costs, and net revenues.11Denholm P. Brinkman G. Mai T. How low can you go? The importance of quantifying minimum generation levels for renewable integration.Energy Policy. 2018; 115: 249-257Crossref Scopus (24) Google Scholar,12Bistline J.E. Turn down for what? The economic value of operational flexibility in electricity markets.IEEE Trans. Power Syst. 2018; 34: 527-534Crossref Scopus (23) Google Scholar,19Palchak D. Denholm P. Impact of generator flexibility on electric system costs and integration of renewable energy.https://www.nrel.gov/docs/fy14osti/62275.pdfDate: 2014Google Scholar For example, reducing minimum generation levels of thermal plants by 25% and 50% (from baseline levels) allows those generators to stay online for more hours across the year, resulting in an overall reduction in startup costs by 21% and 32%, respectively.20Schill W.-P. Pahle M. Gambardella C. Start-up costs of thermal power plants in markets with increasing shares of variable renewable generation.Nat. Energy. 2017; 2: 17050Crossref Scopus (61) Google Scholar Furthermore, coupling a reduced minimum generation level with thermal energy storage yields similar curtailment, startup, and operating costs benefits, while also reducing operating reserve violations and unserved load.21Wang Y. Lou S. Wu Y. Wang S. Flexible operation of retrofitted coal-fired power plants to reduce wind curtailment considering thermal energy storage.IEEE Trans. Power Syst. 2020; 35: 1178-1187Crossref Scopus (36) Google Scholar Conversely, other work has shown how increasing these minimum generation levels by a factor of about 2 results in non-linear increases in curtailment for systems with moderate VRE penetrations (33%–40% VRE), and it also suggests that reducing minimum generation levels might be potentially more effective in reducing curtailment than storage.11Denholm P. Brinkman G. Mai T. How low can you go? The importance of quantifying minimum generation levels for renewable integration.Energy Policy. 2018; 115: 249-257Crossref Scopus (24) Google Scholar Other work has demonstrated how minimum generation levels, startup and shutdown cost, and must-run generators (potentially including self-scheduled generators) can significantly increase curtailment, even when multiple storage technologies are available.22de Boer H.S. Grond L. Moll H. Benders R. The application of power-to-gas, pumped hydro storage and compressed air energy storage in an electricity system at different wind power penetration levels.Energy. 2014; 72: 360-370Crossref Scopus (145) Google Scholar Among these studies, the annual PV energy penetration levels were generally in the 5%–20% range, with some scenarios reaching 28%.11Denholm P. Brinkman G. Mai T. How low can you go? The importance of quantifying minimum generation levels for renewable integration.Energy Policy. 2018; 115: 249-257Crossref Scopus (24) Google Scholar,16Nelson J. Kasina S. Stevens J. Moore J. Olson A. Morjaria M. Smolenski J. Aponte J. Investigating the economic value of flexible solar power plant operation.https://www.ethree.com/wp-content/uploads/2018/10/Investigating-the-Economic-Value-of-Flexible-Solar-Power-Plant-Operation.pdfDate: 2018Google Scholar,19Palchak D. Denholm P. Impact of generator flexibility on electric system costs and integration of renewable energy.https://www.nrel.gov/docs/fy14osti/62275.pdfDate: 2014Google Scholar,20Schill W.-P. Pahle M. Gambardella C. Start-up costs of thermal power plants in markets with increasing shares of variable renewable generation.Nat. Energy. 2017; 2: 17050Crossref Scopus (61) Google Scholar Other studies did not include any PV (i.e., only wind),21Wang Y. Lou S. Wu Y. Wang S. Flexible operation of retrofitted coal-fired power plants to reduce wind curtailment considering thermal energy storage.IEEE Trans. Power Syst. 2020; 35: 1178-1187Crossref Scopus (36) Google Scholar,22de Boer H.S. Grond L. Moll H. Benders R. The application of power-to-gas, pumped hydro storage and compressed air energy storage in an electricity system at different wind power penetration levels.Energy. 2014; 72: 360-370Crossref Scopus (145) Google Scholar and the largest reported penetration was 50% PV in one scenario with limited exploration of thermal generator sensitivity to only minimum generation levels and startup costs.12Bistline J.E. Turn down for what? The economic value of operational flexibility in electricity markets.IEEE Trans. Power Syst. 2018; 34: 527-534Crossref Scopus (23) Google ScholarMore broadly throughout the literature, studies looking at both planning and operational considerations have made high-level observations about the interaction of the available flexibility of the system and curtailment.23Mileva A. Johnston J. Nelson J.H. Kammen D.M. Power system balancing for deep decarbonization of the electricity sector.Appl. Energy. 2016; 162: 1001-1009Crossref Scopus (102) Google Scholar,24de Sisternes F.J. Jenkins J.D. Botterud A. The value of energy storage in decarbonizing the electricity sector.Appl. Energy. 2016; 175: 368-379Crossref Scopus (224) Google Scholar For example, Sepulveda et al. show that VRE curtailment can be reduced from nearly 60% to less than 15% of the available resources by utilizing deployable low-carbon resources in a fully decarbonized system.2Sepulveda N.A. Jenkins J.D. de Sisternes F.J. Lester R.K. The role of firm low-carbon electricity resources in deep decarbonization of power generation.Joule. 2018; 2: 2403-2420Abstract Full Text Full Text PDF Scopus (185) Google Scholar Others have noted significant investment decision effects from the representation of operational flexibility (e.g., inter-hour, operating reserve, and maintenance constraints), temporal resolution, and system curtailment, highlighting the important interplay of operational constraints and curtailment.25Palmintier B.S. Webster M.D. Impact of operational flexibility on electricity generation planning with renewable and carbon targets.IEEE Trans. Sustain. Energy. 2016; 7: 672-684Crossref Scopus (138) Google Scholar, 26Helistö N. Kiviluoma J. Holttinen H. Lara J.D. Hodge B.-M. Including operational aspects in the planning of power systems with large amounts of variable generation: a review of modeling approaches.WIREs Energy Environ. 2019; 8: e341Crossref Scopus (51) Google Scholar, 27Nicolosi M. The importance of high temporal resolution in modeling renewable energy penetration scenarios.https://escholarship.org/uc/item/9rh9v9t4Date: 2010Google ScholarThis paper adds a novel contribution to the literature in two ways. First, it provides a more extensive exploration of operational parameters that can affect curtailment by using a highly detailed and resolved production cost modeling (PCM) database that is informed by capacity expansion modeling (CEM). And second, it explores generally higher PV penetration systems that also include significant levels of wind and storage with some demand response; the highest VRE penetration system satisfies load with 44% PV penetration. This scenario also has 31% annual generation from wind and a 36% storage penetration in relation to peak demand on a capacity basis. Although the use of CEMs and PCMs is not new, the full suite of experiments we have designed has not been reported in the literature for a realistic, highly resolved system systematically across the PV penetration levels we are exploring. Our results reveal a novel framing of a solar curtailment “paradox” relating to the role of thermal generator flexibility on curtailment as a function of PV and thermal generator penetration levels, as well as a misalignment of the system value provided versus potential compensation for PV providing operating reserves in a competitive wholesale market context. Here, we focus on PV for two reasons: (1) it is poised to provide the largest share of new VRE deployed in the United States28Cole W. Corcoran S. Gates N. Mai T.,D. Das P. 2020 standard scenarios report: a U.S. electricity sector outlook.https://www.energy.gov/eere/analysis/downloads/2020-standard-scenarios-report-us-electricity-sector-outlookDate: 2020Google Scholar,29EIAAnnual energy outlook 2020.https://www.eia.gov/outlooks/ieo/Date: 2020Google Scholar and many other countries,30International Energy AgencyWorld energy outlook 2020.https://www.iea.org/reports/world-energy-outlook-2020Date: 2020Google Scholar and (2) it shows a more rapid increase of curtailment with penetration because of its coincident nature. Furthermore, the growth of PV paired with battery storage across our scenarios, as determined by the CEM, is consistent with the current status of many U.S. interconnection queues, which have very large amounts of these technologies.31Wiser R.H. Bolinger M. Gorman W. Rand J. Jeong S. Seel J. Warner C. Paulos B. Hybrid power plants: status of installed and proposed projects.https://emp.lbl.gov/publications/hybrid-power-plants-status-installedDate: 2020Google ScholarOur analysis leverages multiple modeling tools to mirror the investment-operations sequence often used in utility planning practices. We begin with the use of a CEM to establish least-cost future build-out scenarios with increasing penetration levels of VRE resources that are dominated by PV across the study footprint. CEMs optimize the build-out and retirement of generators, transmission, and storage resources across multiple decades, subject to the economic outlook for each resource type and a wide range of system constraints, including load balancing, operating reserves, planning reserve, and policy targets, among others. However, CEMs do not provide a granular representation of system operations, so we then employ a utility-grade PCM that optimizes the least-cost chronological economic unit commitment and dispatch of generation and transmission to assess the detailed operation of each future build-out scenario across the study footprint. PCMs optimize operations in a highly resolved temporal and spatial manner, and they account for the many operational and cost considerations when scheduling the system. These include generators-specific variable operations and maintenance costs, fuel costs paired with a heat rate curve, startup and shutdown costs, minimum and maximum operating levels, minimum up and down times, and ramping limits, among others. Given that PCMs only evaluate system operations, each of the CEM build-outs is provided as an input. See experimental procedures for more details on these modeling tools and methods.Our analysis uses a system that is roughly based on the Los Angeles Department of Water and Power (LADWP) generation and transmission system, and it leverages data sets developed for the LA100 study.32National Renewable Energy LaboratoryCochran J. Denholm P. LA100: the los angeles 100% renewable energy study. National Renewable Energy Laboratory, 2021https://maps.nrel.gov/la100/reportGoogle Scholar More details on this system are provided in experimental procedures. This system is an area with rapidly growing levels of PV and is therefore likely to experience increasing curtailment. Because LADWP acts as an independent balancing authority, and for the sake of computational tractability, we model the operations of this footprint as an islanded system with all energy derived from utility-owned or contracted resources throughout the Western Interconnection, but with no additional short-term market purchases or sales. We evaluate power system operation under six scenarios of future PV deployment, which are shown in Figure 1. Because PV is the dominant source of generation and a main driver of curtailment, we refer to the different build-outs by their PV penetration level.This study has two objectives: (1) determine which operational factor or factors most contribute to curtailment in these high PV futures and (2) quantify the potential value of PV providing operating reserves with this curtailed energy (i.e., reserves in the up direction, or “raise”) or in PV further curtailing in order to provide down direction (i.e., “lower”) operating reserves. We evaluate these questions by assessing several sensitivities. For operational factors, we explore bookend sensitivities related to thermal plant flexibility (including ramp rates, minimum generation levels, and minimum up-and-down times), as well as other operational constraints, such as transmission network constraints, the deployment of storage, and the use of 5-min resolution dispatch. We also evaluate sensitivities related to operating reserve eligibility, specifically whether utility-scale VRE resources and/or storage can provide operating reserves (distributed PV is precluded from providing operating reserves in all scenarios). The goal of these scenarios is to provide a guide regarding which class of operational factors might be most important to enhance or better manage as systems progress to higher PV penetration levels.The PCM determines the least-cost schedule for energy and operating reserves across all eligible generators for each time step. Eligible generators might provide operating reserves up to their operating limits (i.e., within ramping, maximum resource availability, and online status constraints). In scenarios where reserves are provided by VRE, the model ensures the upward reserve capacity is available on the basis of the forecasted availability. VRE is allowed to only provide relatively short duration reserve products, typically requiring only 30 min of response. In all scenarios except DA-RT, this scheduling is done assuming 24 h of perfect foresight of load and VRE availability. Assuming perfect foresight might underestimate the flexibility needs of the system caused by forecast errors. Our results, thus, likely underestimate curtailment levels and the effect of our sensitivity cases on curtailment. We note that our DA-RT scenario is intended to explore the role of forecast errors; results yielded very little difference from the Base case with perfect foresight, but future work should explore varying lookahead horizons and resolutions as wells as varying degrees of forecast accuracy.These sensitivity scenarios are outlined in Table 1. We evaluate each sensitivity for each of the six PV penetration levels, which yields 84 total scenarios.Table 1Sensitivity scenarios grouped by category of the parameters they adjust (thermal plant flexibility, operating reserve provision, or operational constraints)CategorySensitivityDescriptionBaselineBasehourly resolution real-time operations with Base values; utility-scale VRE eligible to provide operating reserves (distributed PV cannot provide reserves)Thermal plant flexibilityZero Min Genminimum generation levels for online dispatchable generators set to zero2× Min Genminimum generation levels for dispatchable generators increased to double the base value, up to a maximum of 1 (as a fraction of nameplate capacity)Zero Up/Down Timeminimum on/off times for dispatchable generators set to zero1.1× Up/Down Timeminimum on/off times for dispatchable generators set to 1.1 times Base value10% Rampmaximum ramp Up/Down rates for dispatchable generators set to 10% of Base value2× Rampmaximum ramp Up/Down rates for dispatchable generators set to double Base valueEligibility of VRE and storage resources to provide operating reservesNo VRE Reservesutility-scale VRE (stand-alone and VRE portion of hybrid systems) ineligible to provide operating reservesNo Storage Reservesbattery storage (stand-alone and battery portion of hybrid systems) and PSH ineligible to provide operating reservesNo Storage or VRE Reservesall utility-scale VRE and battery and PSH storage ineligible to provide operating reservesOther operational constraints5-Min5-min resolution real-time operations; other cases use hourly resolutionDA-RTunit commitment for certain units occurs in day-ahead (DA) simulation using forecasted wind and solar time series, with final dispatch determined by a real-time (RT) simulation with actual wind and solar time seriesNo Storageall storage (battery, PSH, and CAES) replaced with equivalent capacity of gas-CT; serves as counterfactual caseCopperplatetransmission limits not enforcedThese scenarios are run for each of the six PV penetration levels, resulting in 84 model runs.Dispatchable generators include natural gas combined cycle (Gas-CC), steam (Gas-ST), and combustion turbine (Gas-CT); coal; geothermal; and biopower. PSH, pumped-storage hydropower; CAES, compressed air energy storage. Open table in a new tab Results and discussionThe PCM results for each scenario were analyzed for curtailment, operating costs, generation and storage operations, and operating reserve price trends. Results were also evaluated for unserved load and operating reserve violations, which are key metrics of grid reliability and resource adequacy. The load was met in all time-steps in all scenarios.Table 2 summarizes key statistics for the Base sensitivity case across the six build-out levels. The table reveals the three main dimensions analyzed in this study: PV penetration level, storage penetration level, and the resulting curtailment. The six build-out levels evaluated are based on least-cost build-outs from a CEM with increasing levels of PV and storage, though we note that these build-outs represent only a small subset of possible generator combinations and, thus, do not exhaustively represent the full PV-storage-curtailment spectrum. We emphasize that, although these build-outs are based on the least-cost CEM results for this test system under the study assumptions, they do not necessarily represent the ideal combination of PV and storage for any system under any set of policy or economic assumptions. In other words, these build-outs reflect one plausible pathway to higher penetrations of both PV and storage. Furthermore, the No Storage scenario provides a fixed level of storage (i.e., no storage) to highlight how increasing levels of PV penetration affect curtailment. As a point of reference, in real power systems, annual average curtailment rates from 2013 to 2018 across the U.S. ISO market areas were approximately 6% for wind and 1.5% for solar.3Sun Y. Wachche S.V. Mills A. Ma O. 2018 Renewable Energy Grid Integration Data Book. National Renewable Energy Laboratory, 2020Google ScholarTable 2Summary statistics for the Base scenarios, which are based on least-cost build-outs from the CEMRenewable penetration annual avg (max instantaneous)% of total annual generationCapacity penetration% of peak loadCurtailmentannual avg (max instantaneous)% of available resourcePVVREREStorageVREPV21% (71%)28% (79%)38% (84%)6%0.1% (28%)0.1% (21%)26% (81%)40% (90%)52% (92%)8%1.1% (36%)1.0% (43%)30% (87%)44% (92%)56% (95%)10%2.8% (46%)3.0% (50%)33% (88%)51% (93%)63% (96%)11%6.7% (40%)5.7% (50%)38% (94%)63% (96%)76% (96%)24%5.8% (47%)6.8% (54%)44% (96%)75% (96%)86% (97%)37%8.2% (57%)9.9% (65%)Renewable penetration values are shown for PV resources only, which include utility-scale, stand-alone, and hybrid PV systems, as well as distributed PV resources; VRE resources, which include wind and PV; and all renewable energy (RE) resources, which include VRE, biopower, geothermal, and hydropower. Instantaneous curtailment levels shown are for hours with available VRE generation of at least 1% of installed capacity. Open ta