We present a prototype simulation game, the OptiPower Game, to introduce basic concepts of power demand optimization to high school students (grades 9-12). Students decide how to allocate limited energy resources while anticipating they must meet power demands under challenging, randomized scenarios generated by the simulation. The team that supplies the most periods, at the least cost, wins the round. There are several learning objectives of the OptiPower Game: introduce students to power systems; teach concepts of supply, demand, and reserves; introduce pros/cons of different energy resources; and illustrate the difficulties of generating optimal power supply to meet uncertain supply and demand. The OptiPower Game, played in teams, is useful for short (1-2 hour) sessions. It was designed using Excel VBA, and has been piloted with 110 high school students as part of two design competitions. Informal feedback was gathered from students to improve future versions of the game.
Joy Chang is an undergraduate student at the University of Michigan studying Industrial and Operations Engineering.
University of Michigan, BS Electrical Engineering '17
Fanny Pinto Delgado is a second year master student and first year PhD. Pre-candidate in Electrical Engineering at University of Michigan. She received her BS in Electrical Engineering from “Universidad Simon Bolivar”, Venezuela, in 2014. Her research interests are primarily in electric machines and drivers, power electronics, and control.
Abdi Zeynu, University of Michigan
Ph. D. Candidate in Electrical Engineering Systems at the university of Michigan.
Johanna Mathieu's research focuses on ways to reduce the environmental impact, cost, and inefficiency of electric power systems via new operational and control strategies. She is particularly interested in developing new methods to actively engage distributed flexible resources such as energy storage, electric loads, and distributed renewable resources in power system operation. This is especially important in power systems with high penetrations of intermittent renewable energy resources such as wind and solar. In her work, she uses methods from a variety of fields including control systems and optimization. She also uses engineering methods to inform energy policy.
Siqian Shen is an Assistant Professor of Industrial and Operations Engineering at the University of Michigan. She obtained a B.S. degree from Tsinghua University in 2007 and Ph.D. from the University of Florida in 2011. Her research interests are in mathematical optimization, particularly in stochastic programming, network optimization, and integer programming. She was named a runner up of the 2010 INFORMS Computing Society Best Student Paper award, was awarded the 1st Place of the 2012 IIE Pritsker Doctoral Dissertation Award, and was a recipient of 2012 IBM Smarter Planet Innovation Faculty Award. She currently serves as an Associate Director in the Michigan Institute for Computational Discovery & Engineering (MICDE).
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