We believe everyone deserves reliable infrastructure

Lack of stable infrastructure is unfairly holding back huge portions of the world’s population from running businesses, preparing food, and accessing safe and reliable healthcare.

We care deeply about bringing the benefits of modern systems, inclusive decision-making, and open information to everyone.

Alexandra, Jackson, and Marguerite preparing sensors for a pilot in the Democratic Republic of the Congo.

Founded at UC Berkeley,
now a global team

In 2017, nLine started in the Electrical Engineering department of University of California, Berkeley where Josh and Noah, two of our co-Founders received their PhDs, and Prabal, our third co-founder, is a faculty member. Since then, we’ve grown both in Berkeley and across the globe with a talented team of people.

Working with the garage door open

Drawing from our academic roots, we try to publish everything we learn - from papers, to conferences, to blog posts. We always love to get in touch with others pushing towards similar goals.

Read our papers→Read our blog→
Avatar for Mohini Bariya
Mohini Bariya

What Can Voltages Tell Us About the Structure of the Grid?

Knowing the structure of the grid—how lines interconnect and what phases loads are on—is vital for efficient grid maintenance and operations, informing applications ranging from fault localization to phase balancing. Yet, grid structures, especially in distribution, can change over time and are often poorly known. This blog starts to explore how nLine’s voltage data could be used to infer grid structure, with a vision toward eventually providing such insight to utilities.
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From Measurements to KPIs: Estimating SAIDI at nLine

How can we estimate SAIDI (System Average Interruption Duration Index)—the average power outage duration experienced across all customers served—from PowerWatch sensor measurements of only a subset of customers? This post describes nLine’s statistical approach to estimate SAIDI from such a dataset. The nLine method has several favorable statistical properties that make it well-suited to calculating SAIDI in the real world where data is generally limited, which traditional SAIDI calculations neglect to consider.
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Margaret Odero and Mohini Bariya

A Clustering Algorithm for Power Outage Detection

nLine installs power sensors at outlets in homes, small businesses, and social infrastructure. How do we estimate the extent of a grid outage from individual sensor reports? And in the real world, where sensors can be unplugged or prepaid credit can run out, how do we separate real grid outages from false outage reports?

Join our team

We’re a small and highly motivated team addressing the most pressing problems in energy infrastructure. If you care about our mission, please apply!

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Get in touch

We’re open to new partnerships, or sharing more with people interested in our work.

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