Every summer in California, a single degree of heat can decide whether the lights stay on or off. When extreme demand threatens to overload the grid, utilities trigger “demand response events”, calls to action for solar providers and storage systems to release power immediately. But historically, the systems responsible for reporting whether those resources actually responded have struggled to keep up.
In a field that promised speed, the data was still running on a delay.
Until 2022, even some of the largest solar and battery aggregators still relied on batch reporting, collecting data in chunks, uploading performance metrics hours or even days after an event occurred. This made real-time grid coordination nearly impossible. Regulators couldn’t verify whether energy had been dispatched as promised. Aggregators had to manually align formats, timestamps, and telemetry resolutions from dozens of disparate sites. The process was error-prone, slow, and increasingly incompatible with the urgency of climate-era grid demands.
The state of distributed energy reporting wasn’t just inefficient. It was a liability.
From Lag to Live: How One Dashboard Changed the Rules
At Hanwha Q CELLS, a clean energy company managing over 60 solar and battery sites across California and Texas, engineer Priyam Ganguly was tasked with solving this very bottleneck. The stakes were high: demand response events were growing in frequency, grid compliance rules were tightening, and manual reconciliation was no longer viable.
Ganguly’s answer came in the form of a real-time Virtual Power Plant (VPP) Event Reporting Dashboard, a system that moved clean energy analytics into the moment. Built using Apache Pinot and deployed in 2022, the dashboard replaced batch uploads with live, queryable data from every site in the network.
“The grid can’t wait hours to know if power was dispatched,” Ganguly says. “We needed a system that answered in seconds.”
At the core of his solution was a dual-layer architecture: one layer ingested high-frequency telemetry data at scale, while the second supported lightning-fast, fine-grained queries by internal teams. Grid events could now be tracked as they happened. Site-level performance, participation status, and dispatch verification were available in real time. Compliance analysts no longer had to manually stitch together data; the system did it for them, with accuracy and speed.
Bridging the Divide: From Engineering to Public Infrastructure
What began as an internal project quickly took on a broader significance. In 2024, the California Distributed Solar Government Scheme (DSGS) began adapting Ganguly’s architecture for its internal dashboards, allowing government analysts to monitor grid contributions more confidently during extreme weather. In Texas, ERCOT-participating DER aggregators began using the system’s post-event reporting framework to validate performance data and streamline compliance filings.
This marked a rare transition: an in-house engineering solution, developed for a specific portfolio, became an unofficial standard across multiple states and regulatory ecosystems.
“The real breakthrough wasn’t just speed,” Ganguly explains. “It was flexibility. The system dynamically supported different aggregator formats, telemetry resolutions, and naming conventions. We built it to adapt, not to dictate.”
That adaptability made it usable not only across diverse solar programs, but also in policy briefings and long-term planning conversations. It proved that DER coordination didn’t have to be reactive or fragmented. It could be transparent, responsive, and trustworthy.
Why This Matters Beyond the Grid
At first glance, a reporting dashboard might not sound like the kind of invention that shapes communities. But when you consider the impact of more reliable grid coordination, especially during blackouts, peak loads, and weather-driven surges, the public benefit becomes clear.
Every minute saved in verifying energy dispatch means fewer outages. Every instance of standardized reporting reduces the risk of double counting or missed compliance. For low-income households in California that rely on subsidized solar power, or for municipalities balancing energy loads across schools and hospitals, these are not minor gains, they’re foundational.
A 2023 report from Energy Central noted that most virtual power plant (VPP) programs were still relying on interval-based data uploads, often with minimal ability to reconcile real-time telemetry. In contrast, Ganguly’s platform set a new bar: queryable metrics with sub-second latency, aligned to the exact timestamps of grid event triggers.
It wasn’t just about modernizing systems. It was about earning the trust of regulators, aggregators, and everyday consumers.
Technical Innovation Without the Jargon
For engineers, what Ganguly accomplished is notable. He used Apache Pinot, a real-time distributed OLAP datastore known for its high performance, and configured it with a dual-layer data model uncommon in DER reporting tools. His system managed both scale and latency, ensuring that massive volumes of incoming data didn’t compromise the speed of queries.
He also built in flexibility for ingestion across varying input sources, handling everything from API-based telemetry to file drop zones, making it vendor-agnostic and program-compliant. These features weren’t just architectural wins; they addressed the exact problems that had long plagued distributed energy programs: inconsistent data inputs, time drift, and inflexible schema requirements. But the story doesn’t rest in engineering. It rests in the fact that grid reliability improved, and that others followed his lead.
Setting the Stage for What’s Next
Today, as U.S. energy policy shifts toward broader decentralization, encouraging households, buildings, and cities to generate and store their own power, the need for real-time coordination is only growing. Grid programs like California’s DSGS and Texas’s ERCOT aren’t just managing larger volumes; they’re managing greater diversity. More vendors. More technologies. More data. In this environment, systems like the one Ganguly built don’t just serve internal teams. They serve an ecosystem.
Looking ahead, Ganguly sees new challenges still to be solved: expanding these systems to integrate not just dispatch metrics but also predictive analytics, and ensuring that energy storage is just as visible and verifiable as generation. He also sees potential for national-level coordination standards, a vision where states don’t have to reinvent dashboards from scratch, but can start from a template proven to work in real-time conditions.
“The energy grid is getting smarter,” he says. “But the real question is: can our data systems keep up?” If his dashboard is any indication, the answer might finally be yes.
