Pacific Gas and Electric Company EPIC Final Report: Attachment Program Electric Program Investment Charge (EPIC) EPIC 2.03A: Test Smart Inverter Enhanced Capabilities Project – Photovoltaics (PV): Smart Inverter Modeling Report Reference Name EPIC 2.03A: Customer Cited Smart Inverters EPIC 2.03A: Smart Inverters Department Grid Integration & Innovation Executive Sponsor Roy Kuga Project Sponsor Mark Esguerra Business Lead (Modeling Fedor Petrenko Subproject) Technical Lead Mike McCarty (Modeling Subproject) Contact Info [email protected] Date February 8, 2019 Version Type Final EPIC 2.03A: Smart Inverters: Modeling Report EPIC 2.03A Project December 2018 ELECTRIC POWER RESEARCH INSTITUTE 3420 Hillview Avenue, Palo Alto, California 94304-1338 . PO Box 10412, Palo Alto, California 94303-0813 . USA 800.313.3774 . 650.855.2121 . [email protected] . www.epri.com EPIC 2.03A: Smart Inverters: Modeling Report DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES THIS DOCUMENT WAS PREPARED BY THE ORGANIZATION(S) NAMED BELOW AS AN ACCOUNT OF WORK SPONSORED OR COSPONSORED BY THE ELECTRIC POWER RESEARCH INSTITUTE, INC. (EPRI). 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EPIC 2.03A: Smart Inverters: Modeling Report ACKNOWLEDGMENTS The Electric Power Research Institute (EPRI) prepared this report for Pacific Gas and Electric Company (PG&E). EPRI Principal Investigators: Miguel Hernandez Jouni Peppanen Tanguy Hubert Jeremiah Deboever PG&E Principal Investigators: Mike McCarty, Fedor Petrenko, Olivia Trinko The authors would also like to recognize the contributions of Matthew Deakin from the University of Oxford, who supported part of the modeling and analysis presented in this report during an internship with EPRI. iii EPIC 2.03A: Smart Inverters: Modeling Report EXECUTIVE SUMMARY This modeling effort explored the technical impacts and economic value of several of the smart inverter (SI) functions defined in California Electric Rule 21 (“CA Rule 21”) and Hawaiian Electric Rule 14 (“HI Rule 14”). The modeling effort objectives were twofold: (1) inform PG&E on the successful utilization and configuration of residential SI to mitigate PV-driven impacts and expenditures; and (2) provide an understanding of the economic impact of SIs from various perspectives: PV customers activating SI functions, ratepayers, utility, and society. As part of this modeling effort, six representative PG&E feeders were modeled and validated. In particular, while planning modeling methodologies usually focus exclusively on modeling the primary system (i.e., medium voltage), this modeling effort modeled low-voltage (LV) secondary circuits in great detail. Quasi-static time-series (QSTS) simulations explored 15,183 different scenarios parametrized by multiple technology penetration levels (PV and storage), load conditions, and PV generation profiles. Conclusions from this modeling effort assume a highly distributed PV penetration across each circuit since simulation models were focused on residential installations. While these six distribution feeders were carefully selected to inform on the possible benefits of activating SI functions, they only represent 0.2% of PG&E feeders. For each of the six feeders, the PV-driven impacts and expenditures on the distribution grid operation were first analyzed, focusing on residential PV systems. Two strategies aiming to accommodate higher PV penetration levels were then evaluated and compared: one strategy relying on conventional distribution upgrades, the other on SI Volt-VAR and Volt-Watt functions. The scope of this modeling effort was limited to analyzing the effectiveness of Volt-VAR and Volt-Watt functions to specifically address PV-driven voltage violations. Traditional upgrades were triggered by decision rules reflecting potential thermal overloads and voltage rise issues, closely following PG&E’s design and engineering practices. A critical evaluation of these practices suggested that, while thermal violations were always properly addressed, voltage issues could sometimes be left undetected as they can occur before the aggregate inverter nameplate exceeds the service transformer’s kilovolt-ampere (kVA) nameplate. The strategy leveraging SI Volt-VAR and Volt-Watt functions was shown to reduce, but not entirely suppress overvoltage conditions. Still, the reduction observed was generally comparable, and sometimes superior to the level of performance obtained with conventional upgrades. Active power curtailment, resulting from the activation of SI functions, appeared extremely limited: across all combinations of feeders, functions, inverter densities, and PV and load conditions considered, only 45 of the 8,414 PV installations modeled experienced active power curtailment greater than 1% across any of the analyzed 24-hour periods. The increase in inverter utilization appeared negligible. The economic impact of activating SI functions was evaluated across four cost categories: (1) the increased electricity cost at feeder heads; (2) the bill increases to participants; (3) the avoided secondary voltage rise upgrades; and (4) the avoided secondary voltage rise studies, all resulting from activating SI functions. These cost categories were mapped to four standard cost tests, reflecting various stakeholder perspectives: PV customers activating SI functions, ratepayers, utility, and society. Time- differentiated annual energy usage profiles were constructed for each individual PV customer, and an algorithm emulating PG&E’s billing system for three relevant retail electricity tariffs provided detailed v EPIC 2.03A: Smart Inverters: Modeling Report estimates on potential bill increases. Several other key sensitivities influencing the results were explored. The economic impacts were first evaluated for the six feeders selected. The approach was comparative in nature: differences impacting the cost categories according to which strategy was considered, conventional upgrades or SI functions, were analyzed; equipment upgrades required under both strategies were excluded from this comparative analysis, since they could not lead to any cost differences between the two strategies. The activation of SI functions generally yielded a net positive economic impact across the six feeders considered when compared to the traditional upgrades. Yet, this benefit appeared to be relatively small: Total Resource Cost (TRC) values, assuming a linear PV penetration increase over time, ranged from a total Net Present Value (NPV) of -$4/customer (net cost) to $57/customer1 (net benefit) over 10 years (in $2018). The benefits of activating SI functions generally increased at higher PV penetration levels, reflecting a larger number of transformer upgrades and secondary voltage rise studies avoided. The savings resulting from these avoided costs are expected to benefit electric ratepayers, interconnecting customers, and PV developers. For each of the six feeders studied, an analysis of the “customer outliers” experiencing bill increases higher than the average PV customer was also conducted. Among 354,096 customer cases involving an annual bill increase higher than $3 (out of 474,633 customer cases), only 0.748% of the customer cases returned an annual bill increase higher than 3%. A possible two-step approach was identified to drastically limit the (already very small) number of customer outliers in practice: first, detect circuit locations prone to overvoltage conditions early; second, proactively implement distribution upgrades at these locations to ensure that nearby PV customers do not experience excessive active power curtailment, when compared to the average PV customer. As a part of this modeling effort, an extensive literature review of relevant