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[font size=5]1 Introduction[/font]

[font size=3]Deployment of distributed solar photovoltaics (PV) has expanded rapidly in the United States, growing by over 400% since 2010 in terms of total installed capacity and averaging 40% year- over-year growth in capacity additions (GTM and SEIA 2015). This rapid growth has been fueled by a combination of steeply declining costs, the advent of innovative financing options, and supportive public policies at the federal, state, and local levels. Key among the supportive policies has been net energy metering (or simply net metering or NEM), which typically compensates each unit of PV generation at the customer’s prevailing retail electricity rate. Net metering allows homes and businesses with onsite PV systems to offset their electricity consumption regardless of the temporal match between PV production and electricity consumption. As state incentive programs and federal tax credits are phased out, net metering has become increasingly pivotal to the underlying customer economics of distributed PV.

The rapid growth of net-metered PV has provoked concerns about the financial impacts on utilities and ratepayers (Accenture 2014, Kind 2013, Brown and Lund 2013, Eid et al. 2014). Central to these concerns is the contention that net metering at the full retail electricity price allows PV customers to avoid paying their full share of fixed utility infrastructure costs, thus requiring the utility to raise retail prices, including for non-PV customers, to recover those costs in full (Borlick and Wood 2014). Compounding that concern is the possibility of the feedback effect where increased retail electricity prices accelerate distributed PV adoption, resulting in even higher prices as fixed utility infrastructure costs are spread over an ever-diminishing base of electricity sales (Cai et al. 2013, Costello and Hemphill 2014, Felder and Athawale 2014, Graffy and Kihm 2014).

A wide array of corrective measures – ranging from incremental changes to utility rate design to fundamental changes to utility business and regulatory models – has been suggested to address concerns about under-recovery of fixed costs associated with distributed PV and other demand- side resources (Bird et al. 2013, Fox-Penner 2010, Harvey and Aggarwal 2013, Jenkins and Perez-Arriaga 2014, Lehr 2013, SEPA and EPRI 2012, McConnell et al. 2015). Proposals to modify rate designs for PV customers come in many varieties (Faruqui and Hledik 2015, Linvill et al. 2013, Glick et al. 2014). Frequently they entail reallocating a portion of cost recovery from per-kilowatt-hour volumetric charges to fixed customer charges and/or per-kilowatt demand charges (NC Clean Energy Technology Center 2015), while other proposals involve replacing net metering with alternate mechanisms that compensate PV customers for all or some PV generation at a price different than the retail electricity rate (e.g., using a feed-in tariff or value- of-solar tariff; Blackburn et al. 2014).

Decision-making on these issues, however, is hampered by several key informational gaps. Fundamentally, significant disagreement exists about whether, or the extent to which, net- metered PV under existing rate designs causes retail electricity rates to increase. One aspect of that disagreement revolves around the question of feedback effects: Does distributed PV lead to ever-spiraling rate increases as each successive rate increase further accelerates PV adoption? Prior studies of this issue have generally remained conceptual and hypothetical; few have sought to quantitatively examine the magnitude or likelihood of effects, with the notable exceptions of Cai et al. (2013), Chew et al. (2012), and Costello and Hemphill (2014). Furthermore, analyses and discussions of retail rate feedback effects have focused only on the possible positive feedback associated with under-recovery of fixed costs. A separate – and potentially offsetting – feedback may occur when increasing PV penetration causes a shift in the temporal profile of wholesale electricity prices (see Table 1). Numerous studies have demonstrated that the capacity value and wholesale market value of PV erode as penetrations increase (Mills and Wiser 2013, Hirth 2013, Gilmore et al. 2015), and Darghouth et al. (2014) explored the implications of this effect for time-based retail rates and the customer-economics of PV systems. No studies to our knowledge, however, have estimated the impact of this effect on the deployment of distributed PV or contrasted it with the fixed-cost feedback mechanism that is the focus of current broader literature.

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