Minimizing, through a Mixed Integer Nonlinear Programming Program, the Cost of Reaching Hawaii's One Hundred Percent Renewable Energy Goal by 2045

Abstract

Energy is a key topic of debate and study within environmental, political, and economic arenas. Extreme interest in the energy sector can be attributed to the high levels of energy consumption in every aspect of modern life. This consumption has prompted a revolution in the pursuit of cheaper, less internationally dependent, and greener sources of energy. The state of Hawaii, an isolated archipelago state of the U.S., is positioned to lead the revolution through their implementation of House Bill 623.House Bill 623 was signed into action in 2015 by Governor Ige. It set a renewable portfolio standard of one hundred percent renewable energy in Hawaii by 2045. If implemented, this bill would make Hawaii the first state in the U.S. to be run entirely on renewable energy. The caveat of the bill however, lies in a loophole that would allow Hawaii to delay their target RPS deadline if installing renewable energy becomes financially harmful to the public utility company, Hawaiian Electric. Through a mixed integer nonlinear programming problem, this thesis found the minimum cost of Hawaiian Electric implementing House Bill 623 in nine potential economic scenarios. These nine economic scenarios were dependent on various industry estimations of fossil fuel prices and renewable levelized costs of energy over the next twenty-eight years. The results of the mixed integer nonlinear programming problem implied that House Bill’s 2045 deadline was economically feasible through the installation of certain renewables, largely utility scale solar and onshore wind, in each of the nine economic scenarios.