Over the past few years, we’ve seen a number of hybrid utility-industry software platforms emerge to help manage distributed energy resources. They’ve started as in-house deployments and grown into commercial platforms for other utilities to use, via joint ventures or other arrangements.
DVI, the AMI-enabled volt/VAR optimization platform owned by Virginia’s Dominion Resources, is a noteworthy example. So is Bit Stew, the startup that cut its teeth on an in-house smart meter rollout for BC Hydro, and was bought for $153 million by investor General Electric in 2016. Pxise, the real-time, closed-loop grid balancing technology owned by Sempra Energy and developed with OSIsoft, is an earlier-stage version of a similar concept.
At this year’s Distributech conference, I spoke to two companies that are quietly working with utility partners on a similar path to market, and to solve similar challenges. But instead of managing electrons on the grid, they’re managing data through the utility planning process in a much richer, faster and more useful way than traditional methods allow.
The trick is to marry all the data coming in from smart meters, grid sensors, DER interconnections, and other points of interest for utilities, with a cloud platform that grid planners can use to plot out hundreds of scenarios in hours or days, rather than a handful of scenarios in weeks or months.
Putting these two technologies together could enable big changes for grid services in a distributed energy-rich environment -- for both utilities and regulators.
Clean Power Research and SMUD
Take WattPlan Grid, the platform launched by Napa, Calif.-based Clean Power Research (CPR) and the Sacramento Municipal Utility District (SMUD) at Distributech last week. This platform, now available under a software-as-a-service subscription at an undisclosed price, got started last summer when the two companies co-created a “solution that doesn’t exist” in the utility space today, according to Morgan Putnam, director of business development at CPR.
The solution: a DER adoption forecasting tool that doesn’t take months to complete, or become obsolete as economic or regulatory factors change.
SMUD’s Distributed Energy Strategies group “was looking for something to forecast customer-side adoption of many different DERs, but do it in a really quick way, and to forecast lots of different scenarios, based on a lot of different utility inputs, such as cost of solar, rate designs, incentives and benefits,” Putnam said.
The typical approach to these forecasts is to hire a consultant to conduct a study that takes at least six months, as with a typical utility integrated resource plan (IRP) process, said Putnam. But because these studies are so labor-intensive, they typically include only a handful of scenarios -- a low-medium-high forecast, or one that adjusts for a limited number of variables. They tend to rely on representative customer classifications and estimation, rather than on hard data. And they’re rendered obsolete by big changes in those variables, such as the cost of solar after the Trump administration imposed its tariffs in January, Putnam noted.
WattPlan, by contrast, uses actual data from SMUD’s 660,000 or so customers to run bill calculations, load-profile analyses, solar simulations, battery charge and discharge simulations, and the like. It also has access to the customer solar analytics of CPR’s popular PowerClerk platform -- although the modeling of other DERs, such as batteries or EV chargers, represents a new foray for the company, he noted.
With the cloud available for running scenarios, grid planners can tinker and adjust their models over and over, with days at most separating them from their next answers, Putnam said. While SMUD has started out focused on DER adoption modeling for its distribution engineering department, for example, it’s also looking ahead to integrated resource planning, not to mention “what their customer interests are, and how they can tailor their programs to meet those customers’ needs.”
SMUD, unlike the state’s investor-owned utilities, doesn’t require the California Public Utilities Commission’s approval to integrate these kinds of changes into how they allocate their spending across these multiple areas. But given the fast pace of change the CPUC is imposing on IOUs to account for DERs as part of their distribution grid investments, “regulators are asking for this kind of information today,” said Putnam.
PowerRunner and Ameren
PowerRunner, a Brentwood, New Hampshire-based company founded by veteran market designers from ERCOT, CAISO and other grid operators, has spent the past five years working with the Illinois utility Ameren to turn its smart meter data into grid intelligence -- even before Ameren started deploying smart meters.
PowerRunner defines itself as a “self-service data platform” to analyze and predict disparate scalar and time-series data sets, running on a computing platform that uses graphical processing units to allow for processing of “millions of points of data through probabilistic scenarios, over and over and over again,” PowerRunner President Jason Iacobucci said in an interview last week.
The original premise for the platform was to “be that transaction hub for the distribution utilities...to the universe of everything that’s going to be connected to the distribution grid,” he said. To support that, it’s linked data from customer information systems, geographic information systems, meter data management, and supervisory control and data acquisition (SCADA) systems.
In the early days working with Ameren, Iacobucci met Keith Hock, who was interested in the capabilities of the startup’s software for long-term transmission planning. Specifically, Ameren called PowerRunner to manage its system loss analysis, a report that plays an important role in recovering the costs of energy lost between generation and consumption.
These reports take 12 to 18 months to generate. "It’s a huge exercise, a lot of manual work -- gathering data from disparate sources,” said Hock, now director of transmission technical support at Ameren, at last week’s Distributech.
That’s why Ameren hadn’t done a transmission analysis in more than a decade when, in 2016, “the regulatory guys came to me and said, ‘We’d like to get one done in the next three months. Do you have any ideas?’”
“I said, ‘Yeah, I do.’"
"If we’re calculating what every customer's load is for every hour, and we know what voltage level every customer is served at, we should be able to figure out what the losses are for each voltage class, for every hour,” said Hock.
With PowerRunner’s platform, “It didn’t take an awful lot of work to build that in the engine, and now we can do a loss study for every hour of the year, in about 20 minutes or so.”
From there, Ameren tapped PowerRunner’s analytics to forecast unexpected changes in load losses for the hour ahead, in order to give the utility more insight into how to hedge against "unaccounted-for energy," Iacobucci said. “We’re correctly allocating where these losses should be going, per the current socialized cost system.”
Finally, Ameren is interested in using PowerRunner’s platform to calculate the value of distributed resources to the grid, under the Illinois Commerce Commission’s NextGrid policy initiative. The concept of replacing net metering with upfront payments based on circuit-by-circuit data takes some heavy number-crunching. "Once we get full AMI, we’ll have every customer's hourly usage data -- and we know the capacity, we know the limiting elements, on each feeder.”
Using some standard profiles for solar already on its system, Ameren has created “proxy assets” to run across each of its 400,000 feeder circuits to “determine how many kilowatts of DERs we could accommodate on every circuit without overloading the circuit -- and, if the circuit is already overloaded, how many kilowatts of DERs could help reduce congestion,” said Hock.
This is the same kind of detailed grid cost-benefit modeling underway in California and New York.
Clean Power Research’s Putnam noted that SMUD is also interested in the ability to value DERs in terms of distribution grid capacity and upgrade costs.
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