Meeting Energy Needs by Balancing Cost and Sustainability through Linear Programming

Abstract

Greenhouse gases (GHG) trap heat and make the planet warmer, exacerbating global climate change. Energy production is the second largest contributor to climate change [19]. In particular, the production of electricity and use of gas contribute to climate change. Additionally, gas is not renewable and the source of electricity may not be renewable either. How and whether communities transition to renewable and/or cleaner energy sources is dependent on a number of factors, including energy needs, cost, space, emissions, jobs, and materials. In this paper, we explore minimizing the cost of building, operating, and maintaining energy sources. We consider different combinations of cleaner and/or more renewable energy sources to meet energy needed for a given city while keeping total emissions, land use, and energy infrastructure costs low. For specificity, we use the city of Chicago as a test case. If we use a combination of wind and solar energy to meet the total energy needs of Chicago, we find that it is most cost effective to use only wind. However when variable demand and production are included, it is most cost effective to use a combination of wind and solar. If nuclear and geothermal energy are included to decrease overproduction, it is most cost effective to use a combination of wind and geothermal energy.