Monte Carlo based control algorithm for economic feasibility of v2G applications

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Fen Bilimleri Enstitüsü, Türkiye

Tezin Onay Tarihi: 2019

Tezin Dili: İngilizce

Öğrenci: KIVANÇ ŞAHİNKAYA

Danışman: Ali Nezih Güven

Özet:

The use of electric vehicles (EVs) has been increasing in recent years due to economic and environmental factors. This rapid development makes it necessary to investigate the effects EVs on the power system planning and system participants. The aim of this study is to determine the optimal operating strategy for a microgrid operator which can function as a prosumer with the contribution of vehicle to grid (V2G) application. The connection time, plug-in time and state of charge (SoC) of EVs are stochastic variables and these variables are represented in the algorithm using a respective Gaussian distribution function. The Monte Carlo based algorithm aims to obtain a more accurate result despite these stochastic input values. The developed algorithm controls the battery energy of EVs, updating the decision at every hour, according to the estimated daily load and electricity price curves to minimize the operational cost of a smart grid. The algorithm has been applied to three different cases, which are categorized according to the connection points of EVs (i.e., residential, commercial, both residential and commercial). Uncontrolled charging, controlled charging and discharging scenarios apply to all of these cases to determine and compare the economic contribution of V2G application. These cases are also analyzed in order to evaluate the output of the control algorithm to different tariffs, different load demands and different EV characteristics.