There will likely be no utility death spiral due to rooftop solar – but the wrong kind of rate changes could do rooftop solar a lot of harm, according to U.S. national lab researchers.
Solar can’t cause utilities long term harm because at a certain level of solar deployment, its value will drop and people will stop installing it, especially under certain rate structures, cutting utility revenue losses, new research shows.
The real problem is for solar. “Retail rate design changes can have very substantial effects on distributed solar deployment,” explained Lawrence Berkeley National Laboratory (LBNL) Senior Scientist Ryan Wiser. “Understanding the possible magnitude of those effects can be useful for utility regulators.”
Too much of the attention on this report may go to the relationship between the two feedback mechanisms, said Wiser, co-author of "Net Metering and Market Feedback Loops: Exploring the Impact of Retail Rate Design on Distributed PV Deployment."
But its “first order finding is that rate design matters and can have a substantial impact on the deployment of customer-sited solar,” Wiser said.
Its “second order finding” is that it shows – with “quantitative muscle” – that reports of the utility death spiral are inaccurate, he added. “We look under the hood to understand the degree to which two feedback mechanisms drive the impacts of solar on utility revenues, and we find that because they operate in opposition to one another, they are not as significant as one might think.”
The study’s primary audience is state-level utility regulators, Wiser said. They are facing major decisions about retail electricity rates and net energy metering (NEM) because, in part, of rapidly increasing penetrations of distributed solar and other distributed energy resources.
This research brings “quantitative clarity” to impacts of rate design changes on solar deployment and to the two inter-related feedback effects.
The first is “sometimes described as the utility death spiral” and the other “uses time-of-use or real time pricing,” Wiser explained. “We found that with these two opposing mechanisms there is no evidence there would be an out-of-control spiral.”
The feedback mechanisms
Some have speculated that with net energy metering (NEM), rooftop solar owners’ reduced bills could lead to “under-recovery of fixed utility costs” that would force utilities to increase electricity prices. That could result in “a feedback loop of increasing retail prices that accelerate PV adoption and further rate increases,” the study explains.
But where utilities and regulators have instituted time-of-use or real time (TOU/RT) rates, “a separate and opposing feedback loop could offset this,” the LBNL study reports. Such TOU/RT rates increase the price of electricity when demand is high.
With more installed solar meeting electricity needs during the day, peak demand shifts to the late afternoon and evening when sunlight is dwindling. The benefits of solar ownership diminish. “At progressively higher solar penetrations, utility bill savings from having rooftop solar will also progressively decline,” Wiser explained.
“At the aggregate national level, the two feedback effects nearly offset one another,” the study shows, "although their magnitude and direction vary by customer segment and by state.”
“The two feedback effects very closely oppose one another so that the aggregate feedback is small,” Wiser said. “We generally found the two effects largely cancel each other out at the state level, too.”
The biggest surprise to come from the research was that neither mechanism’s impact was especially big, he said. “There are some states that have an aggregate feedback of plus 5% or minus 5% but that was about the largest we could find.”
Even absent the pricing feedback, the first solar feedback was “basically plus 8%,” Wiser said.
“That’s not zero or miniscule, but it doesn’t seem to be a death spiral either.”
First order findings
The LBNL researchers integrated their data on feedback mechanisms into the National Renewable Energy Laboratory’s Solar Deployment System modeling tool to understand rooftop solar economics and predict deployment, Wiser said.
“Future adoption of distributed PV is highly sensitive to retail rate structures,” the study reports. “Flat, time-invariant rates with net metering lead to higher aggregate national deployment levels than" when time of use or real time rates are utilized.
There is a second key conclusion. “Rate structures with higher monthly fixed customer charges or PV compensation at levels lower than the full retail rate can dramatically erode aggregate customer adoption of PV (from -14% to -61%, depending on the design).”
And, finally, a time-varying rate, “may accelerate near and medium-term deployment (through 2030), but is found to slow adoption in the longer term (-22% in 2050).”
The study provides solar deployment paths for eight scenarios. Cumulatively, they show PV deployment to be “highly sensitive to rate design choices and PV compensation mechanisms.”
Of the eight scenarios modeling different rate designs, only a flat rate or a high value of solar/feed-in tariff increase solar deployment in 2050, the study finds.
With “all residential and commercial customers on a time-invariant flat rate with no fixed or demand charges, PV deployment would increase by 5%,” it reports. A tariff of $0.15 per kWh would also increase deployment above business-as-usual, but a $0.07 per kWh tariff leads to a 79% drop in deployment.
The 22% drop in deployment in 2050 driven by the TOU/RT rates verifies the study’s finding about the utility death spiral mechanism: Solar deployment, under variable rates, has a self-limiting aspect that works against any “existential threat” from it.
It also verifies the study’s finding about rate design’s potentially powerful impact on solar deployment. By 2050, “a $10 per month charge applied to residential customers reduces total cumulative deployment by 14%, and a $50 per month charge reduces deployment by 61%,” the study reports.
An NEM remuneration for solar at the utility’s avoided cost for traditional generation and below the current retail rate “reduces deployment by 31%,” the study reports, because it reduces average compensation and increases the payback time for installing PV.
Regional and state-level impacts vary. “For the two fixed-charge scenarios, the range is relatively small, primarily reflecting differences in the average residential retail rate and average annual customer load across states,” the study reports.
The flat rate scenario creates only a “modest” increase because flat rates are already the norm.
A time varying rate causes substantial variations in deployment. “For about 75% of states, switching all customers to a time-varying rate reduces cumulative PV in 2050.”
The effect is most significant where PV deployment is highest and where PV’s energy and capacity values erode the most. Where PV penetration is low, compensation remains higher than the average rate in 2050 and so deployment remains higher.
For the PV compensation mechanisms modeled, “it depends entirely on what the price is,” Wiser said. “There are probably some things that go beyond just economics but if the price is above retail, it is likely to accelerate deployment and it if is below, it is likely to slow deployment.”
Beyond economics
One aspect of the compensation mechanism “goes beyond economics to politics,” Wiser stipulated. The amount of the compensation mechanism is the primary driver of solar deployment, “but if that tariff level is changing all the time and swinging in the political winds, it will be hard to establish a durable business model for the solar industry.”
The major contribution of the study is in quantifying the impacts of rate design changes and feedback mechanisms on solar deployment. Some of the numbers are “sizeable,” Wiser said.
“We are not here to say customer fixed charges should or should not be applied. Utility regulators have plenty of considerations beyond solar deployment. But we have demonstrated that some rate design changes, whether fixed customer charges or a move away from standard retail net metering, could have significant implications.”