Can data hot spots like Pandora's make utilities rock harder?
It's hard to stay profitable if your company doesn't know what's needed where. Locational data holds the key to electrifying performance.
This article first appeared at RMI Outlet.
Last fall Pandora announced that locational listening data would be available to bands. Pandora reasoned that bands could see where they were — and weren’t — popular, and thus schedule more strategic tours accordingly. Bands can use anonymized listener data to plan big arena shows in some cities, play small clubs in others and skip some parts of the country entirely. It’s an approach otherwise known as hot-spotting, which has been applied to everything from neighborhood crime prevention to health care.
Digging through the data that can unveil hot spots enables more optimal deployment of resources to benefit both the industry and fans. The result is more shows in places with high demand, which leads to higher customer satisfaction (plus more revenue from more sold-out shows, which in turn offer the opportunity to sell more merch — CDs, T-shirts, and posters).
Pandora's streaming model gives listeners the ability to customize while giving the company localized data about its listeners' preferences.
This model presents a similar opportunity for electric utilities to leverage data to understand customer usage patterns, concentrated load pockets, distribution system congestion and other forms of electric grid hot spots to better direct investment in distributed energy resources and central grid assets.
3 trends utilities and Pandora have in common
Pandora’s decision to release locational data reflects the convergence of three trends with strong parallels to an ongoing evolution in electric service: distributed production; empowered customers; and data everywhere.
The distributed production trend is a shift from purely centralized to a partly distributed model for recording and publishing music. Whereas artists once required the use of a record label’s investment in recording equipment and distribution channels (radio), up-and-coming bands can record professional-quality sound with their own inexpensive, commercially available equipment (Audacity, GarageBand) and distribute it more directly to fans via the Internet.
The second trend is that fans have new platforms — including music-streaming services such as Pandora and Spotify — to find and share new music in addition to what is available from the central model of distribution. Record companies still produce classic albums, play them on the radio, and sell CDs and MP3s. But on streaming services, empowered customers have much more choice in what they listen to, when and how.
The third trend is the massive data collection and analysis enabled by these platforms. Bands (and record labels) have the ability to understand very specific customer listening habits and preferences. This allows bands to promote albums and design tours to better meet fan demand.
Locational hot-spotting for electric utilities
The convergence of these three trends offers an excellent opportunity for utilities, customers, regulators and DER solution providers to rethink the way products, services and the grid are designed to meet the societal goals of safe, reliable, affordable, resilient and clean electricity for all. This is especially evident when it comes to locational hot spotting.
In the case of music, Pandora is trying to help artists go toward hot spots. But with the electric grid, the idea is to target hot spots to alleviate them.
For a long time, the lack of data on distribution system hot spots didn’t matter. DERs were not competitive and the ability to measure and communicate granular usage and price data was prohibitively expensive. If hot spots did matter, it was via a simple relationship: if there was a feeder circuit nearing capacity or other congested distribution infrastructure, that asset could be upgraded to meet growing needs. But now a new option has the potential to defer those upgrades: DERs.
Further, as DERs’ installed costs decrease and performance improves, options to change the way customers buy, sell and use electricity increase and the platform by which customers and the grid interact must evolve. DERs still require a platform — the grid — to operate, create value and transact. But without access to locational data, significant value is left on the table because customers cannot optimize DER performance to contribute value to the grid in addition to the behind-the-meter benefits.
A rooftop solar array is good on its own, but it's more powerful when its data lets the grid operate better.
One way to add value, as discussed in the eLab report "Rate Design for the Distribution Edge," is for utilities to offer locational price signals. Much like listener data that tells bands where their music is more and less popular, the electricity distribution system has high- and low-value locations for distributed energy resources such as rooftop solar and battery energy storage. If utilities release this data, customers and DER solution providers much more effectively could design and deploy products and services that can lower customer bills, reduce emissions and improve grid operations.
Growing use of smart meters and other sensors on the distribution system enables utilities to collect similar data about customer behavior and system operations. This data could be used to design and deploy solar, combined heat and power systems, storage and even vehicle-to-grid technology to high-value locations and reduce incentives to deploy DERs to locations with less value (while still maintaining the customer ability to install generation behind the meter). Much like the algorithms that enable Pandora to play new music you might like, customer utility data can be leveraged to create the optimal bundle of products and services to maximize value on both sides of the meter.
Other uses for locational data
Beyond distributed generation, locational data could be combined with other customer data to improve demand response programs. Customers in high-value locations on the distribution system could participate in targeted critical peak pricing or automated load control programs. Spotify is starting to use locational data from Facebook to analyze customer listening patterns and offer customized playlists for listening at work, home and in the car. Utilities similarly could design targeted demand response programs for customers in high-value locations (critical peak pricing tariffs or distributed generation and energy efficiency products that align with customer usage profiles).
But utilities are still generally unwilling or unable to provide this data to customers and distributed energy resources providers. The result is that the economics for solar, CHP or storage are less attractive because a critically important attribute in electricity pricing — locational value — is inaccessible to all but a few utility distribution engineers.
How to use data to optimize DER deployment
Some utilities are beginning to see the value in providing locational data. In Hawaii, Hawaiian Electric Company publishes locational value maps to help guide customers and DER developers considering installations in places that may be more difficult to interconnect. Unfortunately, locations are not tied to price signals to encourage or discourage installations based on system conditions, although this could change as Hawaiian regulators consider new utility business models.
This locational value map from Hawaiian Electric Company shows distributed generation on the island of Oahu.
Even better, the New York Reforming the Energy Vision proceeding proposes a distribution system platform, operated by the utility, that will aggregate system and customer data and provide it to qualified DER providers to guide product development and deployment to high-value locations. While Consolidated Edison long has offered locational incentives for both lighting (PDF) and air conditioning upgrades through its targeted demand response program, it is evaluating proposals for a more innovative Brooklyn-Queens Demand Management (BQDM) program to avoid building a $1 billion substation.
This project provides a prime example of the value of locational pricing. The BQDM project emerged after ConEd identified a 52 MW capacity shortage on several distribution feeders in Brooklyn. Instead of simply proposing to build a new substation, the company seeks location-specific demand-side resources, from efficiency to distributed generation to demand response, that can capture the capacity savings at much lower cost to ratepayers. The demand-side portfolio is projected to cost $200 million (with an additional $300 million in grid-side investments) compared to the $1 billion substation investment.
Elsewhere in the Northeast, both NYSERDA and National Grid are piloting programs that offer installation incentives to customers who install PV in high-value locations (PDF). And on the West Coast, Southern California Edison allocated 160 of 250 MW of energy storage projects in its Local Capacity Requirements RFO to behind-the-meter proposals that must be deployed in high-value locations on the distribution system.
Finally, and potentially most promising for the future of capturing the locational benefits of DERs, the U.S. Department of Energy’s Green Button initiative makes standardized usage data available to customers and, with permission, to DER solution providers. This data can be used to create DER product packages that can save money for customers while improving grid operations.
So the next time you go see your favorite band, remember that the decision to play in your city, at a venue of a specific size, and even how much to charge for the ticket, likely was informed by listener data compiled and shared by music distributors. Utilities can and should follow the trail Pandora blazed with locational data. Who knows? An electric grid hot spot — and an opportunity ripe for DER investment and deployment — could be coming to a neighborhood near you.