Past Event

How Remote Sensing Can Be Of Value To The Energy Sector

March 24, 2021
4:00 PM - 5:00 PM
Online Event Nairobi.

Recent work has demonstrated how one can use daytime satellite imagery to assist the prediction of individual residential building consumption levels upon connection. Using six years of longitudinal data of electricity consumption for a large cross-section of grid customers from Kenya, we apply convolutional neural networks (CNNs) to daytime satellite images to predict expected levels of residential electricity consumption for individual customers throughout the country.

Achieving universal electricity access through cost-effective use of resources benefits from accurate estimates of expected electricity consumption of the anticipated consumers. While not the only criteria, demand estimates are a crucial input to electrification planning.

Such estimates can be inferred from income or recent utility experience in the area, or scarce survey data, or through indirect but widely available sources such as nighttime lights and satellite images. Leveraging Convolutional Neural Networks (CNNs), this work presents a novel data-driven approach trained on a sample of labeled geo-referenced utility bills to predict demand for individual buildings using daytime satellite imagery. The training dataset consists of 0.01% of Kenya’s residential electricity bills and predictions are made for the entire population using high-resolution satellite imagery of the country. This work shows that richer predictions are obtained with satellite images compared to other widely available

Panelist Bios

Prof. Vijay Modi

Vijay Modi is a professor in the Department of Mechanical Engineering at Columbia University and a member of the Earth Institute faculty. (Ph.D. Cornell 1984, postdoctoral work MIT 1984–1986).

Prof. Modi’s areas of expertise are energy resources/access, energy planning for access and renewable integration, demand estimation, and the role of novel payment systems in breaking barriers to upfront costs. His laboratory, the Quadracci Sustainable Engineering Lab (qSEL), has been responsible for innovations such as a low-cost lead-acid charge/discharge circuit for solar lanterns (2005), fully digital pay-as-you-go (PAYG) minigrids that have been continuously operating as pilots since 2011, battery-less PAYG smallholder irrigation systems (2013-15), and widely used tools such as “Network Planner” for making technology choices under demographic, demand and geographic variations. Finally, a free open-source app called FormHub, used over a million times for assessing field data. Most recently he has worked on larger scale electricity and natural gas networks, their long-term cost/benefits and impact on access to energy, fertilizer, and industrial growth. While his early work was on computational fluid dynamics and micro-electro-mechanical systems, his recent work has been on energy infrastructure design & planning; solar energy; energy efficiency in agriculture, and data analytics spanning from urban settings to remote rural settings. He is currently working closely with city and national agencies/utilities to understand how energy services can be more accessible, more efficient and cleaner. His recent project on minigrids is providing a unique understanding of consumer behavior, demand for energy, and business models for deploying energy solutions and energy efficiency.

Simone Nsutezo Fobi

Simone Fobi is a Ph.D. student in Mechanical Engineering. Her research interests lay at the intersection of developing low-cost energy monitoring devices and data mining to improve electricity provision services in Africa. After her BS in environmental engineering, she obtained her MS from Stanford; which laid the foundations for her interests in energy systems and IT. Prior to joining the Ph.D. program, she worked on Energy and Healthcare projects at IBM Research Africa, Nairobi Kenya.

Jack Bott

Jack Bott is an engineer currently focused on embedded control systems, for solar mini-grids and computer vision, at The Quadracci Sustainable Engineering Lab. He has an MS in Electrical Engineering and a BS in Mechanical Engineering from Columbia University, as well as a BA in Physics from Bard College. Jack has field experience deploying control systems across Africa.