Proactive operation of electric vehicles in harmonic polluted smart distribution networks

This study proposes combined framework for proactive operation, i.e. bidirectional active and reactive power management, of the smart distribution network as well as harmonic compensation of non-linear loads using electric vehicles (EVs) equipped with bidirectional chargers. The problem is in the form of non-linear programming (NLP) where the objective function is to minimise the voltage deviation at the fundamental frequency and the total harmonic distortion. The harmonic load flow equations, EVs constraints, system operation and harmonic indexes limits are formulated as problem constraints. The proposed NLP problem is converted to an equivalent mixed integer linear programming (MILP) model using Taylor series and linearisation techniques for AC power flow formulation. Also, the Benders decomposition (BD) algorithm is used to solve the proposed MILP problem that is tested on different distribution test networks to demonstrate its efficiency and performance. The results show that the NLP model can be substituted with the high-speed linear programming model. Moreover, the computation speed is improved by using the BD method. Finally, the network and harmonic indexes improved and charging cost reduced using the proposed idea.