GIS and AI for the recognition and mapping of power grid assets

(1) ESMIA offers expertise in modeling integrated 3E (energy-economy-environment) systems for strategic decision-making at the municipal, regional, national, and global levels. ESMIA’s expertise is recognized by numerous private sector clients and various levels of government in Quebec, Canada, and around the world. ESMIA’s goal is to provide solutions that enable the achievement of energy security and transition objectives while ensuring sustained economic growth.
(2) The energy transition and power system planning increasingly require accurate and up-to-date spatial information on existing infrastructures. Unfortunately, publicly available inventories of power grids, such as transmission lines, substations, and generation facilities, are often confidential, incomplete, heterogeneous, or limited in spatial resolution. The main challenge of this project is to leverage recent advances in artificial intelligence (AI), particularly in image recognition applied to satellite and aerial imagery, to develop and automated, scalable, and reproducible mapping of power grid assets.
(3) The resulting information will serve as valuable input for ESMIA’s strategic and operational optimization models. An accurate mapping will improve the representation of transmission constraints in NATEM (North American TIMES Energy Model), and by identifying the actual routes of transmission lines and the location of substations, the model will better capture regional transfer capacities, potential bottlenecks, and associated losses.

Faculty Supervisor:

Jin Guo;Sylvie Daniel

Student:

Partner:

ESMIA Consultants

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

McGill University

Program: