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https://idr.nitk.ac.in/jspui/handle/123456789/14270
Title: | Performance Investigation of Applicable Wireless Communication Protocols for Vehicle-to-Grid (V2G) in Smart Grid Environment |
Authors: | Santoshkumar |
Supervisors: | R. Y, Udaykumar |
Keywords: | Department of Electrical and Electronics Engineering |
Issue Date: | 2016 |
Publisher: | National Institute of Technology Karnataka, Surathkal |
Abstract: | The restructuring policy has motivated the private players to participate in power generation and thereby distributed energy resources (DER) such as photovoltaics (PV), wind turbines, micro turbine, fuel cell and internal combustion engine are integrated to the grid. As the sources (PV, wind) and load demand are intermittent in nature, the concept of storage devices aroused. Electrical Vehicles (EV) are one among the storage devices which can serve as a connected load or distributed resource (DR) being a transportation tool. EVs will gradually replace other contemporary vehicles due to serious environmental concerns and growing oil demand. Vehicles are usually parked for 90- 95% of the time in parking stations, residential apartments and office buildings. These EVs can be connected to the grid for power transaction in order to meet the time varying load demand. A single EV can only consume power and may not be appealing but the group of EVs can make a large difference and support the grid requirements. EV connected to home is Vehicle-to-Home (V2H), EV connected to EV is Vehicle-to-Vehicle (V2V) and group of EVs connected to the grid is Vehicle-to-Grid (V2G). V2G can be used for peak shaving, valley filling, load leveling and supplying reactive power to the grid. In comparison to the other existing methods for peak shaving and valley filling, V2G is more efficient and effective. V2G has become a reality with the developments in Power grid and advancement in Vehicle technology. Grid control center (GCC), aggregator and EV are the three key elements in V2G communication. GCC will have the information about the power requirements based on the energy market and it sends this information to the aggregator. Aggregator acts as an interface between GCC and EV and in turn sends the information received by GCC to EVs. Aggregator facilitates EVs to get connected to the grid by providing parking lot and charging slots. EV owner will decide to participate in power transaction with grid based on the State-of-Charge (SOC) of EV battery. The development of wireless communication infrastructure for V2G communication is essential in order to support the V2G operation. The wireless communication link is proposed for GCC to Aggregator communication, Aggregator to EV communication, EV to EV communication and Smart Meter to EV communication. The applicable wireless communication protocols are considered for these links. The end-to-end downlink physical layers of the applicable protocols are modeled using MATLAB/SIMULINK and their performances are investigated using bit error rate and signal–to-noise ratio curves (BER v/s SNR). The suitable channel models (path loss) are analyzed and compared for the applicable protocols considered for V2G communication. The path loss is estimated and suitable path loss models are suggested for V2G communication. Markov chain based queuing model (M/M/m) is developed for EVs connected to the charging slots for power transaction with the grid. The simulation is carried out for the developed model and the idle probability, EVs waiting in system, queue in hours are plotted. A Stochastic model based on Markov chain is developed for EVPL occupancy and the simulation is carried out to estimate the charging slots in EVPL and the time required for EV to charge or discharge. The communication links established will support the in time operation and functioning of V2G and increase its performance and efficiency. This study will help in facilitating the V2G operation in Smart grid environment. |
URI: | http://idr.nitk.ac.in/jspui/handle/123456789/14270 |
Appears in Collections: | 1. Ph.D Theses |
Files in This Item:
File | Description | Size | Format | |
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123042EE12F07.pdf | 4.59 MB | Adobe PDF | ![]() View/Open |
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