Hedging uncertainty in energy efficiency strategies: a minimax regret analysis

A global consensus is growing around the fact that energy efficiency is an effective way to meet the new climate goals. Energy efficiency, forming a hidden giant solution, has been proven more impactful than any other greenhouse gas emissions plan. However, all the energy related processes and the associated factors are fraught with multiple forms of uncertainties and complexities. Hedging against uncertainty, in the present paper we use minimax regret analysis to identify robust strategies towards energy efficiency. Expressing uncertainty through discrete scenarios, we apply robust optimization to meet the optimal mix of energy efficiency measures, performing well, independently of any scenario’s realization, taking into account the employment factor. In particular, we apply the maximin, as well as the minimax regret criterion, to solve the linear stochastic mathematical program. Moreover, a numerical computation on the improvement of the energy efficiency in different sectors is presented.