Gaming for Electric Power Grids

2022 ~ Present | The video games will be complementary to work for the NSF-funded AI Institute for Advances in Optimization (AI4Opt, www.ai4opt.org) and to research efforts at Argonne National Laboratory and Los Alamos National Laboratory.

Goals

The reliability of electric power grids is challenged by the rapidly increasing frequency and severity of natural disasters. To better design and operate power grids during natural disasters and build public acceptance for the disruptive actions needed to mitigate their impacts, this project will develop and publicize video game style simulations that put the player in the role of a power system operator tasked with managing the grid during extreme events. In addition to educating the public about critical infrastructure, data collected from players of the video games will be used to train machine learning algorithms to help engineers better prepare for and respond to actual disaster scenarios.

Issues Involved or Addressed

Operators of electric power systems must address the rapidly increasing frequency of severe natural disasters driven by accelerating climate change. Research efforts have developed many approaches for mitigating the impacts of natural disasters, such as shutting off power lines to avoid igniting wildfires and hardening electric infrastructure by installing seawalls and microgrids as well as undergrounding power lines. However, practical implementations of these approaches require outreach to build public acceptance of the associated disruptive actions and expenses. Another implementation challenge is the lack of detailed datasets containing plausible solutions to resiliency-related optimization problems, which would be valuable for training machine learning models. By developing and publicizing video game simulations for the public, this project will simultaneously address both of these challenges, thus improving the resiliency of our electric infrastructure.

Methods and Technologies

  • Electric power systems, optimization algorithms, video game design and programming, machine learning, public outreach and education

Academic Majors of Interest

  • Computational Media
  • Computer Science
  • Geographic Information Science and Technology
  • Computer Engineering
  • Electrical Engineering
  • Industrial Engineering
  • Machine Learning
  • Literature, Media, and Communication

Preferred Interests and Preparation

Students should have a general interest in energy, sustainability, and electric power. Students with a wide range of backgrounds could contribute to this project. Developing the video game simulations requires a diverse set of expertise, such as power engineering, optimization, software development, user interface design, digital media, etc. Successfully publicizing the video games and achieving the educational goals of this “citizen science” project will require expertise in topics such as public policy, business, media, communications, etc.

Meeting Schedule & Location

Time 
5:00-5:50
Meeting Location 
Klaus 1440
Meeting Day 
Tuesday

Team Advisors

Daniel Molzahn
  • Electrical and Computer Engineering

Partner(s) and Sponsor(s)

The video games will be complementary to work for the NSF-funded AI Institute for Advances in Optimization (AI4Opt, www.ai4opt.org) and to research efforts at Argonne National Laboratory and Los Alamos National Laboratory.

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