UC Berkeley

\begin{abstract}Electricity is increasingly considered to be a human right. However, in much of the world, basic data about power outages and voltage quality is not available, making it difficult to ensure reliable service. Smart meters are difficult to deploy and slow to be adopted in lower-resourced areas, the same areas where frequent outages and voltage sags most impede economic growth.

In this work, I present evidence that by aggregating simple measurements from networked sensors installed at outlets in households and businesses, we can detect both large and small power outages and power-quality issues, enabling a utility-independent, agile, high-resolution, and low-cost system well suited for deployment in under-instrumented areas.

I design, deploy, and operate a large network of sensors---called PowerWatch---at outlets in households and businesses across Accra, Ghana. I show that this deployment, when coupled with cloud-based analytics, matches utility-reported rates of high- and medium-voltage outages at a fraction of the cost. Further this methodology provides a good estimate of low-voltage outages, potentially filling a critical data gap present in most countries.

The deployment methodology developed allows for longitudinal data to be gathered independently from the utility. Utility engineers are not required for sensor installation, and permission is not required as utility property is not impacted. I describe a number of novel measurement and analysis opportunities enabled by this independent deployment methodology, many of which are being piloted by \textit{n}Line, the company I co-founded to continue improving this work.

Data from PowerWatch is being used by multiple governments and research institutions, including as a primary source for the Monitoring and Evaluation of the \$315 Million USD MCC led Ghana Power Compact. \end{abstract}