Global warming has triggered waves of public awareness to surface very strongly world-wide, urging to eliminate all greenhouse gas emissions in a timely fashion. Among all feasible approaches to achieving this goal, using renewables to replace fossil fuels and electric vehicles (EVs) to replace conventional internal combustion engine vehicles is arguably a top-priority task. However, there is a severe lack of practical approaches to measuring a proper renewable mix for powering EVs in a large highway network while also considering renewables’ seasonal availability and the possible need to regulate the production and consumption of renewable energy with grid-scale battery arrays installed at certain locations. This urgent need motivates developing the mixed-integer programming model as presented in this paper. Furthermore, a comprehensive case study on Taiwan’s national highways covers such useful knowledge as the process to prepare key numeric data, especially local solar and wind energy and highway traffic, in-depth analysis on model solutions to reveal the overall availability of renewable energy across the highway network, and close measurements on the required investments. These findings support using renewable energy to power EVs on a national highway and reveal the importance of local business involvements. However, a relatively small country, such as Taiwan, can still display significant variations in renewable power availability. In a stand-alone setting for power usage, these variations would result in massive volumes of renewable energy not used by highway travel in some seasons. These details demonstrate the applicability and values of the proposed model in a real situation.