Smart Grid Innovations in Energy and Analytics Take Root in San Diego—Previewing Xconomy’s Smart Energy Event

Over the next decade, San Diego Gas & Electric (SDG&E) and other public utilities in California must undergo a massive transformation in the ways they generate and transmit electricity to meet aggressive regulatory requirements for renewable energy.

We’re starting to see some of those changes today. In less than two years, SDG&E is expected to complete the installation of “smart meters” for more than 1.4 million of its customers. Once activated, the system will act much like a wireless computer network in which millions of devices regularly update their status and transmit their data to the utility’s operating center. The smart meter technology enables the utility to measure its customers’ energy use in detail (eliminating the need for meter readers), and the network will alert operators to outages and other problems.

Once the smart meters are switched on, SDG&E and other utilities also are expected to adopt so-called dynamic pricing that sets electric rates higher during mid-day periods of peak energy demand—and gives customers strong financial incentives to save energy based on their “time of day” usage.

renewable-energyBut many of the most important changes for both utilities and energy consumers haven’t been invented yet—which is one of the major themes running through the Xconomy Forum on “smart energy,” which is set to begin at 1:30 p.m. tomorrow at U.C. San Diego (Online information and registration is here.)

There’s a wide variety of companies in the San Diego area working on smarter ways of generating, distributing, and conserving energy. But one group that hasn’t received much attention yet are the companies in San Diego’s predictive analytics cluster that are now focusing on new ways of analyzing and predicting energy use and other smart grid data.

As the power grid gets “smarter,” innovations will be needed to help meet regulatory requirements under which 33 percent of the power California utilities distribute must come from renewable energy sources by the year 2020. The essential problem, though, is that the electricity generated by solar panels, wind power, and other renewables is intermittent—it increases and decreases as clouds pass overhead and as the winds rise and fall.

Until now, the power grid has operated as a centralized power distribution system, and the key to understanding the problem is in knowing that the system cannot easily store energy (innovation needed!)—so power generation must exactly match consumer demand. As energy demand soars on a hot summer day, the grid operator must incrementally increase power production (typically by adding electricity generated by expensive gas-fired turbines) to exactly match power generation with demand—what’s known as “balancing the load.” In less than a decade, however, a third of the grid’s electricity will be generated by renewable energy sources that fluctuate throughout the day—which means that both energy demand and production will be moving targets. So it will be far more difficult for utilities to balance power generation with demand.

Managing the future power grid is expected to require extensive new capabilities in sensor networks to monitor weather conditions, as well as added IT capabilities for data collection, storage, and real-time data mining and analytics. In San Diego, as it turns out, several companies have been moving to address the need for such technologies.

Teradata (NYSE: TDC): The Dayton, OH, company spun out by NCR three years ago, has been developing new applications at its San Teradata 10gDiego-based engineering development center for its core database software, data warehouse appliances, and analytics. “We really did not have a presence in utilities until about a year and a half ago,” Terry Burns, a Teradata executive consultant in energy and utilities, told me earlier this year. “All of a sudden, with the smart grid, utilities are in the process—or will be in the process of gathering lots of information.” Through a partnership with Itron (NASDAQ: ITRI), a leading smart meter manufacturer in Liberty Lake, WA, Teradata is creating a software platform designed to help utilities conduct advanced analytics of energy use, power generation, and grid management. Teradata already provides similar technology that helps wireless carriers optimize their network performance, and Burns said electric utilities can use Teradata’s analytics capabilites to take a more holistic view of grid management by analyzing and modeling both tactical and strategic programs to determine which demand-response initiatives would optimize energy use and efficiencies.

EDSA: The San Diego-based software developer’s move into software analytics for complex electrical power systems began about six years ago, CEO Mark Ascolese told me. After developing a computer-aided design program (CAD) needed to develop fail-safe power systems for FAA flight control facilities, Ascolese said EDSA realized its software also edsa_pa_logo2could be used to model the optimal operating status for every component in a complex electric power system. The software can be used by grid operators to predict outages and other problems by pinpointing devices that show deteriorating performance. Last month, EDSA said it is collaborating with Viridity Energy of Conshohocken, PA, to develop real-time “master controller” software to operate a campus-wide electric power “microgrid” at the University of California, San Diego. UCSD’s microgrid includes two 13.5 megawatt gas turbines, a 3 megawatt steam turbine and a 1.2 megawatt solar-cell installation that together supply 82 percent of the annual power needs for the 1,200-acre, 450-building campus.

Zementis: The San Diego-based software analytics startup—which will be presenting at tomorrow’s Xconomy forum on smart energy—announced last October that it was working with Virginia-based defense contractor SAIC to develop real-time predictive analytics technologies zementis_logo_sloganthat utilities can use to identify power grid components at a high risk of failure. By predicting the likelihood of failure, grid operators can prevent power outages by dispatching maintenance crews to replace components before they fail. Zementis CEO Michael Zeller told me the six-year-old company has turned its attention to potential applications in the energy sector after developing its core technology for use in analyzing and predicting outcomes in a host of financial and online merchant applications. “What we do is take models developed in any open source or commercial data mining tool, and integrate them into commercial production systems,” Zeller said.

Detectent: Based in Escondido, CA, privately Detectent initially began six years ago as a research project when ConEdison asked founder Mike Madrazzo to analyze the utility’s customer billing data for signs of energy theft, i.e. identify customers who had illegally tapped into the utility’s Detectent logopower grid. Since then, spokesman Wayne Willis tells me the self-funded company has expanded its capabilities to help analyze the enormous amount of data being generated by smart meters and a utility’s advanced metering infrastructure (AMI). Detectent’s technology can be used to help a utility analyze how customers using their energy—whether a customer is running a high-energy pool pump or air conditioner in mid-day, for example, and to formulate recommendations to shift the time of use or adopt more energy-efficient alternatives. “We just don’t think people will integrate the information they get from their smart meters,” Willis says. “But we do think they will integrate the information and advice they get from their utility.”

Bruce V. Bigelow was the editor of Xconomy San Diego from 2008 to 2018. Read more about his life and work here. Follow @bvbigelow

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