Constance Crozier


Researcher working on simulation and control of future power systems. Most interested in integration of demand flexibility.

View My GitHub Profile


Public Data and Code

I have a number of projects for which we are able to offer open-source code and/or data to other researchers. Please find the details below.

Coming soon: Global demand data from 2019

Primary developer: Constance Crozier

This is a dataset of the hourly electricity demand in 2019 for 155 geographic regions across the world. It will be published on this website at the release of our article (currently in the later stages of peer review).

GridLearn: Grid-aware Multi-Agent Reinforcement Learning

Primary developer: Aisling Pigott

This package adds functionality to the CityLearn package, which simulates a multi-agent reinforcement learning environment for demand response. Added features include: coupled pandapower grid environment, sub-hourly intervals, phase shift enabled smart inverters, synchronous action selection

You can find the code here.

We request that you cite this paper in any works using the model.

Storage Cost and Optimization of Renewable Electricity Systems (SCORES)

Original developer: Constance Crozier

More recent contributions: Cormac O’Malley, Chris Quarton

This is a modeling framework for simulation and sizing of a renewables based electricity system. The model takes hourly data for weather and demand and can simulate the reliability of a system with given solar, wind, hydro, battery, thermal storage, and hydrogen assets.

You can find the code here.

A user guide is provided here.

We request that you cite this paper in any works using the model. [Bibtex entry]