Browsing by Author "Erden,F."

Now showing 1 - 3 of 3

Citation - Scopus: 1
A Distributed Smart Pev Charging Algorithm Based on Forecasted Mobility Energy Demand
(Institute of Electrical and Electronics Engineers Inc., 2017) Kisacikoglu,M.C.; Erden,F.; Erdogan,N.; Department of Electrical & Electronics Engineering
This study proposes a new distributed control strategy for the grid integration of plug-in electric vehicles. The proposed strategy consists of two stages: (i) an offline process to determine an aggregated reference charge power level based on mobility estimation and base load profile, and (ii) a real-time operation based on the distributed control approach. The control algorithm manages PEV charge load profiles in order to flatten the residential distribution transformer loading while ensuring the desired state of the charge (SOC) level. The proposed algorithm is tested on real distribution transformer loading data, and compared with heuristic charging scenarios. The numerical results are presented to demonstrate the impact of the proposed algorithm. © 2016 IEEE.
Citation - Scopus: 19
Examination of Ev-Grid Integration Using Real Driving and Transformer Loading Data
(Institute of Electrical and Electronics Engineers Inc., 2016) Erden,F.; Kisacikoglu,M.C.; Gurec,O.H.; Department of Electrical & Electronics Engineering
The growing environmental concerns and the increase in oil prices will lead to the proliferation of electric vehicles (EVs) in the near future. The increase in the number of EVs, while providing green and inexpensive solutions to transportation needs, may cause constraints on the operation of the utility grid that should be investigated. In this paper, the real user driving information is collected from individual data tracking devices of passenger vehicle owners instead of assuming randomly distributed trip characteristics. The collected trip data are first analyzed to generate a statistical model of the trip characteristics in terms of home arrival times and state of charge (SOC) levels. The resulting model is then used to simulate and analyze the impact of EV integration in a real grid with different EV penetration levels. For this, real distribution transformer data provided by Başkent Electric Distribution Co. is used. The proposed method produces more realistic results in comparison to the studies assuming random scenarios. © 2015 Chamber of Electrical Engineers of Turkey.
Citation - Scopus: 5
Respiratory Rate Monitoring Using Infrared Sensors
(Institute of Electrical and Electronics Engineers Inc., 2016) Erden,F.; Cetin,A.E.; Department of Electrical & Electronics Engineering
Respiratory rate is an essential parameter in many practical applications such as patient and elderly people monitoring. In this paper, a novel contact-free system is introduced to detect the human breathing activity. The system, which consists of two pyro-electric infrared (PIR) sensors, is capable of estimating the respiratory rate and detecting the sleep apnea. Sensors' signals corresponding to the thoracic movements of a human being are sampled using a microprocessor and analyzed on a general-purpose computer. Sampled signals are processed using empirical mode decomposition (EMD) and a new average magnitude difference function (AMDF) is used to detect the periodicity and the period of the processed signals. The resulting period, by using the fact that breathing is almost a periodic activity, is monitored as the respiratory rate. The new AMDF provides a way to fuse the data from the multiple sensors and generate a more reliable estimation of the respiratory rate. © 2015 Chamber of Electrical Engineers of Turkey.