Optimized Integration of Electric Vehicles into the Smart Grid : V2G and Smart Charging Adaptive Algorithm

Electric Vehicles (EVs) reduce dependency on oil and carbon emissions. An upsurge in demand for EVs could lead to negative impacts on the grid. However, charging strategies, such as supporting the grid using vehicle-to-grid (V2G) and smart charging technology, can go a long way to reducing the impacts on the electrical load curve. The thesis presents a number of aspects which relate to the interconnection between EVs and the electric grid for achieving an optimized integration. An adaptive algorithm has been developed to perform load peak shaving by V2G and smart charging, while a hypothetical case study containing several types of EVs in a local grid has been conducted. The aim is to examine the developed algorithm. In conclusion, by using the adaptive algorithm, written in C++, an optimum status has been achieved concerning the electric grid and EV batteries