학술논문

PV assisted Fuzzy based EV charge scheduling for demand side energy management: a case study
Document Type
Conference
Source
2020 IEEE Calcutta Conference (CALCON) Calcutta Conference (CALCON), 2020 IEEE. :486-492 Feb, 2020
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Schedules
Job shop scheduling
Costs
Thermal factors
Smoothing methods
Urban areas
Electric vehicle charging
charge scheduling
EV
fuzzy based scheduling
peak load shaving
Language
Abstract
Targeting a solution for mitigating fossil fuel crisis along with diminishing environmental pollution, rapid adoption of electric vehicles (EV) is taking place. Consequently charging strategy of those vehicles is coming up with great concern. As stochastic charging activities of EVs can greatly stress the distribution system causing grid overloading, peak load increasing, a scheduling of EV charging is needed. On the other side, power system load curve smoothing is needed always for load following, frequency regulation and Voltage regulation. After going through a detailed case study of the city Kolkata, India, a multi aggregator based online fuzzy coordination algorithm (OL-FCA) for charging plug-in electric vehicles (PEVs) in smart grid networks with maximum efficient usage of rooftop PV generation is presented here. It is showed that this kind of harmonization of power industry and transport industry can significantly improve the load factor by 87 percent ensuring proper utilization of clean energy and load ripple reduction.