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Electric Vehicles (EV) can be connected to the grid for power transaction and also serve as distributed resource (DR) or distributed energy storage system (DESS). The concept of connecting group of EVs or gridable EVs (GEV) to the grid is called Vehicle-to-Grid (V2G). V2G is a prominent energy storage system as it is flexible and can be used to support the grid requirements in order to meet the time varying load demand. Optimal placement of GEV aggregation in power distribution network is very challenging and helps in maintaining stability of the power system for a shorter duration of time. In this paper, algorithm is developed for estimating parameters like Ploss, Qloss, Vpu based on past history and wireless access support for Control and Monitoring Unit (CMU) to aggregator agent communication is proposed using Long Term Evolution (LTE) protocol. The load flow studies are carried using MiPOWER software in order to obtain the optimal location for the placement of GEV aggregation in power distribution network. LTE physical layer is modeled using MATLAB/SIMULINK and the performance is analyzed using bit error rate (BER) v/s signal to noise ratio (SNR) curves.

In this paper a multiagent based communication framework for gridable electric vehicle (GEV) aggregation in power distribution network is proposed. Also, multi objective optimization is presented for the minimization of power losses and maximization of voltage. Furthermore multiagent system (MAS) based analytical model is proposed for GEV aggregation. Comprehensive case studies are conducted on IEEE 33 and 69 bus test distribution systems using MATLAB and it is observed that the timely and optimal placement of GEV aggregation in distribution network using multiagent communication (MAC) will lead to reduction in power losses and improvement in voltage profile. MATLAB and MOBILE C were used for the simulation studies and results demonstrate significant benefits of GEV aggregation in distribution network.