An improved energy requirement prediction for queueing applications of electric vehicles based on parameter estimation

Download

Berkay Sağlam Tez.pdf

Date

2022-8

Author

Sağlam, Berkay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

231
views

105
downloads

The use of electric vehicles has increased in recent years. Although they have many benefits to the environment such as reduced carbon emissions, charging of vehicles brings some new challenges for power systems such as overloading, reliability problems, etc. Charging of electric vehicles should be managed to overcome these problems. Queueing strategies are one of the management methods. These strategies are applied to obtain a feasible operation that depends on the decisions made considering system properties and the electricity market. Although there are several methods for queueing in the literature, there is a gap in determination of the load demand of the vehicle. The demand of a vehicle is related to the power consumption of that vehicle and can be calculated by using drivetrain models. These models help to calculate the power consumption of the vehicle by using mathematical models which are related to the vehicle parameters. The parameter values change with time due to aging effects. Therefore, they should be estimated to obtain accurate consumption information. This thesis proposes a method to estimate the parameter values and determine the load demand of a vehicle in order to make feasible queue decisions. The proposed method relies on the Least Squares Estimation method for parameters used in the utilized backward simulation based drivetrain model. In addition, the conditions of the route of individuals are concerned while determining the load requirements. Finally, an optimization method is presented for queueing applications to manage the system operation.

Subject Keywords

Parameter estimation for electric vehicles, Energy prediction for charging stations, Electric vehicle drivetrain modelling, Vehicle to grid applications, Linear programming

URI

https://hdl.handle.net/11511/99504

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Monte Carlo based control algorithm for economic feasibility of V2G applications Şahinkaya, Kıvanç; Güven, Ali Nezih; Department of Electrical and Electronics Engineering (2019) 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 va...
Assessment of impacts of electric vehicles on low voltage distribution networks in Turkey Temiz, Armağan; Güven, Ali Nezih; Department of Electrical and Electronics Engineering (2015) The number of Electric Vehicles (EVs) has reached a substantial value all over the globe due to economic and environmental factors. The increasing penetration of EVs to the distribution grids urges the requirement to investigate the impacts of EVs on the planning and operation of distribution networks. Despite the fact that there are numerous studies discussing the impacts of EVs on distribution grids, a particular study concerning the Turkish distribution networks does not exist. Therefore, this study focu...
Multi-objective charging scheduling utilizing electric vehicle load models Güzel, İven; Göl, Murat; Department of Electrical and Electronics Engineering (2022-1) Utilization of electric vehicle (EV) load models can improve the performance of smart charging strategies, which increase the reliability of the grid by harnessing the flexibility of EV loads. This thesis presents methods for utilizing EV load models in real time stochastic charging control with single and finite system-time horizons. First, the drivers’ load models are found with kernel density estimation. A single system time horizon coordinated charging control algorithm is devised to ensure each EV is c...
Some optimal control problems in electric vehicles Ahıska, Kenan; Leblebicioğlu, Mehmet Kemal; Özgören, Mustafa Kemal; Department of Electrical and Electronics Engineering (2016) Conventional internal combustion engine-powered vehicles are the mainstream mean in nowadays private transportation. However, their fuel consumption results in environmental problems. Electric vehicles, on the other hand, have zero pollutant emission and benefit from high highly-efficient electric motor technology. These make the electric vehicles as the most promising alternative in private transportation. However, limitations in current battery technology aggravate the widespread usage of electric cars. T...
An Evaluation of Building Integrated Wind Energy Pekeriçli, Mehmet Koray; Tanyer, Ali Murat (null; 2017-06-07) Electric, hybrid, and petrol vehicles utilize energy saving regenerative brakes to save energy• These systems generally use the same device for both locomotion and power generation (braking)• We can distribute many small aerofoils across the building façade to provide both ventilation and power generation as needed

Citation Formats

B. Sağlam, “An improved energy requirement prediction for queueing applications of electric vehicles based on parameter estimation,” M.S. - Master of Science, Middle East Technical University, 2022.