Multi-objective charging scheduling utilizing electric vehicle load models

Download

Multi-Objective Charging Scheduling Utilizing Electric Vehicle Load Models.pdf

Date

2022-1

Author

Güzel, İven

Metadata

Show full item record

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

Item Usage Stats

379
views

574
downloads

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 charged at least a critical amount given a feasible set of optimization constraints. The coordinated charging algorithm tackles the NP-hardness of single-deadline charging scheduling problems efficiently with a sorting algorithm utilizing the stochastic EV load models. Moreover, the single system-time horizon coordinated charging control algorithm is extended to a scheduling algorithm considering a finite system-time horizon. This approach utilizes the stochastic EV load models in a model predictive control based approach to decrease the complexity of stochastic online charging scheduling problem into a deterministic case. The scheduling algorithm makes assumptions about the future arrivals to the charging station, unlike the classical online EV charging scheduling algorithms, which optimize the load demand revealed at the current time but underestimate the load demand revealed in the future. Findings of the thesis work suggest the individual load models complement smart charging algorithms’ decision process by improving the fairness of charging time allocation and extending the degree of knowledge of future random data for the scheduling algorithm.

Subject Keywords

Plug-in electric vehicles, Load modeling, Smart charging, Charging scheduling, Electric vehicle grid integration

URI

https://hdl.handle.net/11511/98158

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Plug-in electric vehicle load modeling for charging scheduling strategies in microgrids Güzel, Saliha İven; Göl, Murat (2022-12-01) Utilization of plug-in electric vehicle (PEV) load models can improve the performance of smart charging strategies, which increase the reliability of the grid by harnessing the flexibility of PEV loads. This paper presents a method for utilizing personal PEV 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 (KDE). Second, a single system-time horizon coordinated charging control algorithm...
Assessment of Impacts of Electric Vehicles on LV Distribution Networks in Turkey TEMIZ, Armagan; Güven, Ali Nezih (2016-04-08) This study proposes a methodology to analyze the impacts of Electric Vehicles (EVs) on Low Voltage (LV) distribution networks based on probabilistic models developed for the charging process of EVs. In addition to the battery charging characteristics, Gaussian distribution function for EV plug-in times and Weibull distribution function for daily travel times are utilized in simulations. Monte Carlo based load flow simulations are performed in order to evaluate the response of the LV networks to various EV a...
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...
An improved energy requirement prediction for queueing applications of electric vehicles based on parameter estimation Sağlam, Berkay; Göl, Murat; Department of Electrical and Electronics Engineering (2022-8) 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 propert...
Modeling and optimization of hybrid electric vehicles Özden, Burak Şamil; Ünlüsoy, Yavuz Samim; Department of Mechanical Engineering (2013) The main goal of this thesis study is the optimization of the basic design parameters of hybrid electric vehicle drivetrain components to minimize fuel consumption and emission objectives, together with constraints derived from performance requirements. In order to generate a user friendly and flexible platform to model, select drivetrain components, simulate performance, and optimize parameters of series and parallel hybrid electric vehicles, a MATLAB based graphical user interface is designed. A basic siz...

Citation Formats

İ. Güzel, “Multi-objective charging scheduling utilizing electric vehicle load models,” M.S. - Master of Science, Middle East Technical University, 2022.