Demand response versus storage flexibility in energy: multi-objective programming considerations

Intermittent sources of energy represent a challenge for electrical networks, particularly regarding demand satisfaction at peak times. Energy management tools such as load shaving or storage systems can be used to mitigate intermittency. In this work, the value of different mechanisms to move energy through time is examined through a multi-objective programming approach, that aims at minimizing operating costs as well as carbon emissions. Among main achievements, we mention a sensitivity result that provides a novel three-dimensional Pareto front. The new tool complements the traditional curves of indifference costs with a quantitative measure for assessing the relative value of the conflicting objectives. The methodology is assessed on three instances representing typical configurations in Brazil, Germany and France, respectively corresponding to a system that is hydro-dominated, thermo-dominated, and with a balanced mix of hydro and thermal power. The corresponding Pareto fronts show that lowering carbon emissions can also reduce generation costs if the power mix is sufficiently diversified.