Better data for better power grids

Across the globe, nearly 800 million people cannot access electricity, while billions live with unreliable and intermittent sources of power.

We’ve built a technology platform that provides utilities, regulators, governments, and funders access to accurate and cost-effective data about power grids, enabling them to better detect issues and prioritize investments.

Turn-key remote monitoring, made possible

With our GridWatch technology, you’ll have access to power quality and reliability data within weeks. More information about the key performance indicators (KPIs) that we use can be found in our brief below.

Flow diagram of the GridWatch platform

Sensor installation and data collection

Our robust sensors are plugged into outlets in residential homes or critical public infrastructure, such as healthcare facilities and collect data about electricity reliability and power quality.

Deployment monitoring

Our team of trained field staff are automatically notified when sensors go down and follow our robust deployment methodology to ensure GridWatch continues to collect high quality data.

Generating high-level KPIs

Sensor data is aggregated and filtered into grid-wide metrics like SAIDI and SAIFI and key power-quality insights about specific infrastructure, all viewable on live-dashboards.

PowerWatch sensors being assembled on a table with the circuit-board exposed.A PowerWatch sensor broken apart. Wiring and a circuit board are shown.A PowerWatch sensor as shown during a project in Accra. It's a white box with a plug and a QR code sticker on the back.

Robust sensors gather power quality and reliability data

Sensors plug into a standard outlet and collect data about power reliability and quality. They report that data over the cellular network using a universal SIM, store the data locally in times of poor network quality, and include a battery so they are ready to collect data even after long outages.

Insight-forward analytics pipeline

Our standard data analysis tools provide grid-wide performance metrics about outages and voltage and display those in live, interactive dashboards.

Data shown from our ongoing project in Accra

How it all fits together

GridWatch gives you all the pieces you need to monitor grids.

Reliable, continuous data

Our sensors have been designed to work in any environment, handling extended outages or real-world complexities like accidental unplugging or periods of low-voltage.

Real-time feedback

Utility providers can get data about the performance of specific infrastructure to better target maintenance and improvements.

Works in any context

Our platform has been tested on large national grids, in healthcare facilities, and on mini- and micro-grids of renewable energy installations.

KPI reporting

Summarize historical data into continuous reporting on SAIFI, SAIDI and others to quickly evaluate the overall health of the grid.

Voltage quality

See average voltage, spikes and sags (brownouts) by district, by neighborhood, and by time period.

Low-touch install and operation

Our sensors are designed to be easy to install and minimize the need for replacements, so initial deployments are easy, and ongoing care is too.

Designed for Sub-Saharan Africa

Unlike generic power measurement platforms, nLine’s methodology is specifically designed to work in Sub-Saharan Africa and handle the operational challenges unique to it.

No modifying existing infrastructure

nLine's sensors can be deployed without any change to existing infrastructure, allowing for independent monitoring of utility companies.

See us in action

We’ve deployed over 2,500 sensors across 9 different countries. Read our case studies to see the impact it’s had for others.

See our ongoing projects
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.
Avatar for Mohini BariyaAvatar for Molly HickmanAvatar for Genevieve Flaspohler

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.
Avatar for Margaret OderoAvatar for Mohini Bariya
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?

Get in touch

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