Compensating Solar Prosumers Using Buy-All, Sell-All as an Alternative to Net Metering and Net Purchasing: Total Use, Rebound, and Cross Subsidization.

AuthorSchwarz, Peter M.

List of Abbreviations:

AC: Air conditioner BASA: Buy-All, Sell-All CDD: Cooling degree days DD: Degree days EU: European Union EV: Electric vehicle FIT: Feed-in-tariff GM: Gross metering IBR: Increasing block rate kWh: Kilowatt-hour NM: Net metering NP: Net purchasing PV: Photovoltaic VOS: Value of solar 1. INTRODUCTION

While there is growing evidence of the effect of rates on household adoption of solar photovoltaic systems (PV), there is limited empirical evidence on the effects of solar pricing on electricity use once those systems have been purchased. Such evidence is particularly urgent given opposition by electricity providers to net metering (NM), the predominant U.S. compensation system currently used in 40 of the 50 US states plus the District of Columbia, with five of the 40 states transitioning to policies other than NM. (1) Under NM, solar customers known as "prosumers" can self-consume what they generate or export to the grid at the retail rate. In effect, the electricity meter moves forward whenever they purchase electricity from the grid, and backward when they sell electricity.

Most U.S. utilities argue that NM results in lower revenues due to reduced grid purchases, but not necessarily lower capital costs. (2) This "missing money" problem leads to a second argument against net metering; it may be necessary to increase rates to offset the decrease in purchases. As a result, non-solar customers disproportionately bear the effect of higher rates since they still make all their purchases from the grid. Solar advocates disagree with these arguments, pointing to reduced need to build additional grid capacity and environmental benefits from reduced emissions.

NM may also lead to a solar rebound effect, whereby customers generating solar will reduce grid purchases by less than the full amount of solar generation. While these effects would actually lessen the missing money problem, they would also lessen the environmental benefits of solar electricity. Solar advocates have alternatively proposed a conservation effect, whereby prosumers become more environmentally aware, and so reduce their total use of electricity. Another reason why total electricity use may decrease is that the prosumer would then have more generation to sell to the grid.

In this article, we focus on an alternative to NM known alternatively as Buy-All, Sell-All (BASA) or Gross Metering (GM). Under this rate, prosumers sell all of their solar generation to the utility and buy all of their electricity from the grid. Typically, they are compensated based upon the value of solar (VOS) rather than the retail rate. In 2012, Austin Energy, a community-owned energy provider and therefore not subject to rate-of-return regulation, was the first US utility to switch from NM to BASA. (3) Among the justifications is that it eliminates the "missing money" problem, since solar households still rely on the grid for 100% of their electricity purchases. Furthermore, there are no cross-subsidies since utilities do not need to adjust their retail rate as there is no decrease in contributions towards capital costs. Finally, BASA eliminates at least one of the reasons for the rebound effect, since customers can no longer self-consume, eliminating the possible substitution effect of viewing self-consumed electricity as cheap or free. Solar advocates have opposed BASA primarily because they fear that VOS will be below the retail rate. They also oppose BASA for denying solar households the ability to be self-sufficient.

In this paper, we examine two major claims in favor of BASA as compared to NM, which are that there are no rebound effects and no cross-subsidies. To examine rebound, we use data from the Pecan Street Dataport for the Mueller Street neighborhood of Austin Energy's service territory to examine if solar generation increases total electricity consumption. Pecan Street provides appliance-specific data, so we also can examine electricity used for air conditioning, the appliance most likely to exhibit a rebound effect in Austin's hot weather months. We can also account for electric vehicle (EV) ownership. EVs would increase electricity demand, but that increase would not be a rebound effect. We estimate rebound allowing for both the amount of solar generated as well as the compensation rate for solar.

Our second objective is to examine the cross-subsidization issue. While we do not have data on net-metered customers, we do know Austin Energy's retail rate and can calculate revenues for BASA as compared to a simulated NM rate, with lower revenues implying a larger cross subsidy. We also simulate a third rate, net purchasing (NP), which according to Gautier, Jacqmin and Poudou (2018) is the most widely used solar compensation rate in the EU. As with NM, customers can self-consume the electricity they generate, thus reducing their purchases from the grid. But unlike NM, the rate they receive for the electricity they export to the utility can reflect VOS. As Austin Energy has increasing block rates (IBRs) where the rate is higher for higher consumption blocks, we also show how that rate scheme affects cross-subsidization as compared to flat rates.

In Part 2 of the paper, we review literature on NM, NP, and BASA, as they pertain to solar rebound and cross-subsidies. Part 3 presents theoretical underpinnings and corresponding propositions for the three rates. Part 4 describes the data, methods, and effects of BASA on energy consumption and rebound, with emphasis on air conditioning. Part 5 develops a simulation of NM and NP based on the actual BASA rate to compare cross-subsidies. Part 6 contains conclusions and policy implications.


    We begin with theoretical studies. NM leads to welfare losses when compared with more cost-reflective rates (Brown and Sappington 2017). NM leads to substantial cross-subsidies from non-solar to solar customers and these worsen with increased solar penetration (Picciariello et al. 2015). Under NM utility revenue declines at a rate greater than cost so that utilities can only offset this loss by increasing average retail rates for all consumers (Satchwell, Mills and Barbose 2015, Satchwell, Mills and Barbose 2015). At the extreme, it could lead to a death spiral where consumers continue reducing dependence on the grid in favor of solar energy, which further reduces the utility's customer base forcing them to further increase retail rates (Castaneda et al. 2017).

    Gautier et al. (2018) compare NM and NP. They derive propositions showing that NM leads to too many prosumers, lower bills for prosumers at the expense of non-solar customers, and a lack of incentives to synchronize solar production and self-consumption. NP improves upon NM by all three measures. Their emphasis is on the case where NP pays a premium above the retail rate, reflective of EU feed-in-tariffs (FITs), but not of the U.S., where the trend is to pay prosumers less than the retail rate. Schittekatte, Momber and Meeus (2018) compare NM and NP under four scenarios of low or high levels of PV penetration and low or high costs of battery storage. They find that NM does not recover grid costs under any scenario. As battery adoption increases, NP performs best. Oliver, Moreno-Cruz and Beppler (2019) provide a theoretical development and a stylized example of solar rebound effects for NM and GM. They model rebound as a pure income effect and their model suggests that rebound results from the availability of a zero-marginal-cost supply of power to the household.

    Yamamoto (2012) provides a theoretical framework for a FIT analogous to the GM/BASA approach, NM, and NP (which he refers to as net purchasing and sale). GM leads to higher social welfare than the other two rates when the change in total electricity consumption is small. NM and NP lead to higher electricity rates when households have relatively homogeneous demand characteristics. He does not consider the possibility of rebound effects.

    We turn next to empirical studies. Qiu, Kahn and Xing (2019) use data for a Phoenix, Arizona utility that employs NM and find that when solar generation increases by 1 kWh, total electricity consumption increases by 0.18 kWh, a rebound effect of 18%. (4) They attribute rebound to perceived lower average rates, adopting Ito's (2014) finding that customers base behavior on average and not marginal rates. They also find lower cross-subsidization due to the increased consumption.

    Using half-hourly PV generation and electricity consumption for 80 households in Sydney Australia, Oliva, Macgill and Passey (2016) examine NM and GM for customers who were switched from a generous GM rate to NM. They found that, relative to GM, NM encouraged households to self-consume solar. This led to revenue losses for the grid.

    Deng and Newton (2017) also empirically examine GM for Ausgrid. They hypothesize rebound effects because customers compensated by GM receive a more visible payment than under NM. (5) Using quarterly observations of electricity use and solar PV generation for almost five thousand solar households, they find that rebound may reduce C[O.sub.2] savings by as much as twenty percent, but do not include the actual prices. Examining 300 PV households in Australia under GM, Motlagh et al. (2015) suggest using differentiated tariff offerings, such as for customers who use appliances in the evening.

    La Nauze (2019), who examined customers in Victoria, Australia, found that one dollar of electricity income from the sale of solar increased electricity expenditure by 23 cents, a much larger effect than a standard income response. She describes the rate as a FIT, which here is closest to NP; customers can self-consume, and can be paid a rate above or below the retail rate for exported solar. The study uses computed rather than actual consumption data, based on characteristics of the solar system, weather, and...

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