Methodology for technical and economic assessment of electric vehicles integration in distribution grid.

This paper proposes a methodology to design a supervision system (SS) based on Fuzzy and Boolean logics. In the first stage, a graphical modeling tool is used to facilitate the analysis and the determination of Fuzzy-Boolean algorithm linked to the test system. To improve the performance of the proposed SS a genetic algorithm (GA) is implemented in the second stage. The SS objective is used to control electric vehicles (EVs) load in order to minimize the energy transmission costs (ETC) of the distribution system operator (DSO). To achieve this goal, it is necessary to promote local consumption of wind and photovoltaic (PV) power by coordinating them with EVs load, maximize EVs charging during cheaper energy periods and reduce subscribed power exceeding. The performance of the SS is shown by numerical simulation results using Matlab/Simulink. Finally, a Matlab-PowerFactory co-simulation framework is proposed in order to assess supervision system influence on the technical aspects of a real test grid. A generic methodology is proposed to control Electric Vehicles load.A method for obtaining high-performance of Fuzzy-Boolean algorithm was developed.The coordination between Electric Vehicles and Wind-Photovoltaic power is performed.A co-simulation tool assesses supervision algorithm impacts distribution grid.