Scheduling of EV Charging in Grid-Connected Parking Lots with Renewable Sources

The growing concern about environmental issues is leading many countries to take measures that allow a more rational energy usage and for a more sustainable future. The improvement of systems e�ciency and the use of renewable sources are some points to work on to reduce greenhouse gas emissions. That is why electric mobility is drawing the attention of companies, countries and research groups, as an important measure to face the negative consequences derived from the current energy usage. It is clear that the inclusion of electric vehicles will strongly a�ect the operation, management, and planning of current electric power systems. Firstly, an additional load will have to be considered, the electric vehicles charging. In an initial stage, when the deployment of electric vehicles is not signi�cant, special measures will not be required. However, in the future with thousands of vehicles in operation, ad-hoc electric vehicle charging can lead to line congestion or voltage limits violation. Moreover, an update of the current electric power systems regarding more advanced information and communication technologies, better metering devices, as well as the presence of more renewable sources are required for the suitable integration of electric vehicles. The increasing number of electric vehicles (EV) means there is a growing need for charging stations as well. A potential solution to address the need for charging stations is to transform traditional parking lots into smart parking lots. Due to the inherently complex and dynamic environment, a potential obstacle, from a business perspective to the process of transforming parking lots into smart parking lots is the complexity of estimating the pro�t of the smart parking lots owner and, consequently, the length of time required to recover the cost of the initial investment. We propose a simulation approach to estimate the smart parking lot owners pro�t during a certain period of time. Thus, this thesis is intended to cover the problem of signi�cant increase in electric vehicles arriving at the parking lot leading to a challenge for scheduling of vehicles for charging. The primary objective of parking lot owner is to charge more vehicles and increase pro�t. But due to stringent rules from regulators for network upgrades, increase in the number of charging slots is challenging. Installing a distributed generation like solar microgrid will bene�t from allowing many vehicles to charge at the parking lot. This thesis aims in proposing an algorithm called parking lot management system (PLMS) and charging management system (CMS) for scheduling of electric vehicles with the support of solar generation with the objective of minimizing the power drawl from the grid during high peak pricing period. Power drawl from the grid is reduced by using the solar power available. Since the power drawl from the grid is reduced, it is obvious that the pro�t of the parking lot owner is increased. scheduling is done by shifting the cars to the abundant solar power period and reducing the peaks on the grid which helps the utility operator. The proposed algorithm is simulated using MATLAB programming, and the results are presented

On the Evaluation of Plug-in Electric Vehicle Data of a Campus Charging Network

The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed generation and storage units to reduce the stress on the grid and boost sustainable transportation. While prior work has made considerable progress in deriving insights for understanding the adverse impacts of PEV chargings and how to alleviate them, a critical issue that affects the accuracy is the lack of real world PEV data. As the dynamics and pertinent design of such charging stations heavily depend on actual customer demand profile, in this paper we present and evaluate the data obtained from a $17$ node charging network equipped with Level $2$ chargers at a major North American University campus. The data is recorded for $166$ weeks starting from late $2011$. The result indicates that the majority of the customers use charging lots to extend their driving ranges. Also, the demand profile shows that there is a tremendous opportunity to employ solar generation to fuel the vehicles as there is a correlation between the peak customer demand and solar irradiation. Also, we provided a more detailed data analysis and show how to use this information in designing future sustainable charging facilities.Comment: Accepted by IEEE Energycon 201