Multi-objective optimization of clean energy and transportation technologies considering economic and environmental objectives

Abstract

Recognizing the heat & electricity and transport sectors as the largest contributors to climate change, we propose to simultaneously optimize energy and transportation systems. Even more so, most entities require both and, when considered jointly, synergies can be exploited. The economic – environmental trade-off calls for multi-objective optimization, aiming to find all Pareto optimal solutions. Economies of scale are considered, implying mixed integer programming. This paper is the first to apply the exact algorithm of Vincent, et al. 2013. To differentiate technological and subsidized optima, the impact of policy on the Pareto front is visualized. We distinguish between minimizing economic life cycle costs (complete rationality) and investment costs (bounded rationality). The approach is illustrated using a Belgian SME with a demand for electricity and transport. Electricity technologies are solar photovoltaics and the grid; transportation technologies are internal combustion engine vehicles, grid powered battery electric vehicles (BEVs), and solar powered BEVs.