The residential solar market has slowed in key U.S. markets. There’s no shortage of reasons for the stagnation.
Fewer early adopters, the impact of Section 201 tariffs, changing state policies and persistently high customer-acquisition costs are all contributing to the decline in the number of U.S. households choosing to go solar.
The tepid performance of residential solar — GTM Research reports that the market contracted 15 percent between 2016 and 2017 — means that some in the industry cheered the news of installations being flat, instead of down, in the first quarter of 2018.
But the future looks considerably brighter. A combination of ongoing price declines, emerging markets like Florida and Nevada, and California’s mandate that all new homes install solar, are behind GTM’s forecast of steady residential growth from 2019 to 2023.
Home energy data will be key to propelling residential solar growth in the near- and long-term future — particularly as solar-plus-storage becomes more cost-competitive.
Data to drive solar sales
“There is a significant transition coming on the horizon,” said Keith Marett, CEO of Neurio, a Vancouver-based company that provides hardware and software for real-time monitoring and analytics of home electricity production and consumption through the electric panel.
The transition will be powered largely by the availability of data that can be harnessed by solar installers, homeowners and utilities to better understand and capture the potential benefits of solar. This sort of data represents a significant evolution from the generic home energy reports traditionally used by solar installers to calculate system size and return on investment for potential customers. More granular home energy data can allow customers to shift some loads to better align with solar production, take advantage of time-of-use pricing, or consider how energy storage would impact their bills.
“Home energy reports don’t take into consideration the actual behavior of a home, for example when kids and parents come home after school and work or when different loads are consumed at different times of the day or week based on the residence’s habits,” said Geoff Crocker, head of product management at Neurio.
Rather than an educated-guess approach, Neurio utilizes real-time data and analytics to understand the household energy consumption and generation. Solar installers can then leverage these insights to put together a compelling sales package. This can render the decision-making process quicker and easier for the installer and more appealing to the homeowner.
How data helps after a sale
Accurate and customized data may become even more important after a sale. Giving homeowners access to this granular data is an effective way to demonstrate that they’re actually getting the benefits they expected — which is vital to promoting good word of mouth and the references necessary to drive more installations.
Easy access to accurate and personalized data prevents new solar owners from falling into a common trap. “When a home gets solar, they often believe they have endless energy and start cranking up the AC and then they are surprised when they get a bill much higher than they expected,” said Marett. “Analysis of the consumption data can identify if those habits are changing.”
More granular data can also provide benefits to installers, financiers and utilities. For installers, a comparison of baseline or predicted performance will identify systems that aren’t generating as much energy as expected. Granular data also provides an opportunity to calculate the value of installing solar-plus-storage, especially as storage prices continue to decline.
But in certain markets, leveraging the data through sophisticated analytics can make the addition of batteries even more compelling. Forecasting analytics can help customers understand their peak demand needs and leverage storage to cover the entire peak demand.
“In Arizona, for example, if you deplete the battery before peak demand charges are done, it defeats the purpose,” said Marett. “But if you use it to reduce the full peak demand charge, you can save a lot on your utility bill.” Granular data that is processed with machine-learning algorithms will predict the upcoming home energy consumption and adjust the system operating parameters to achieve optimum results for the user.
The benefits of sophisticated analytics go beyond just the customer. Data-plus-analysis will also help financing companies reduce their risk by backing projects that deliver the most financial value to homeowners. Data is also an important component for utilities as they manage the influx of solar onto the grid.
“Part of the data [utilities] need is a lot of information about how the grid is performing at the distribution level and on the feeder level,” said Crocker. “Having data about what is happening at each home around generation and consumption is key for the utility to make good decisions about how to balance the grid.”
Home for sale: Includes south-facing roof
Data will play an even more important role in residential solar growth in the future. In the near term, Crocker sees data enabling intelligent homes that automatically manage the operation of AC units, hot water heaters, EV chargers and other major loads through machine-learning-based predictions that optimize when appliances run in order to maximize comfort and savings.
In the longer term, data-driven automation and analytics will help transform residential solar systems into sources of income for homeowners — and, in the process, change how people evaluate real estate.
“Homeowners will begin to look at a home as a source of revenue. That means they’ll start looking at things like whether there is a south-facing roof, what the past weather patterns have been, and the historical production of solar nearby,” said Marett.
As with any sound financial decision, having the best possible information is critical; the insights available from household energy data are key in making the jump to a homeowner-led energy economy. Homeowners will be able to deploy a home energy controller that can predict their consumption and solar energy production due to weather and combine this with open-market energy pricing models to plan their home energy system behaviors, said Marett. “We are on the upswing of an information age where all of this data is available and can be analyzed in powerful ways.”