Local and Central Supervision of Optimal Plug-In Electric Vehicles Energy Dispatching for Load Smoothing within the Innovative Smart Grid

Siwar Khemakhem, Lotfi Krichen

Abstract


This paper deals with optimal Plug-in electric vehicles (PEVs) energy dispatching with electrical grid incorporating cooperative central and local supervision. The Central Supervision Center (CSC) aims to achieve the collaborative power scheduling for numerous Charging Stations (CSs) equipped with PEVs. In the Local Supervision Center (LSC), the PEVs power management has been established to flatten the conventional load for each Charging Station (CS). Consequently, the CSC gathers information taking into account various constraints, including the load of the respective CS and neighboring CSs, the availability of PEVs at the considered CS and among PEVs' neighbors, the initial State Of Charge (SOC) of the PEVs connected to the respective CS and that of PEVs' neighbors, as well as the allowable lower and upper limits for PEVs battery SOC as inputs data. We considered a simulation of the conventional power for three studied CSs in which the supervision strategy appropriately collaborates among them to guarantee their power smoothness thanks to the bi-directional PEVs energy management. The results highlight the load power improvement achieved by valleys filling and peaks shaving in each CS power profile through four distinctive operating modes. Compared to existing methods in the field, these outcomes reveal the effectiveness of this approach in reducing power fluctuations, achieved through both LSC and CSC, with the goal of alleviating stress on the smart grid. While incentivizing the PEVs integration and Vehicle-to-Grid (V2G) profits, dynamics, lifetime, and cost modelling of PEVs batteries might be included into future studies to enhance their charging process.

Full Text:

PDF

References


J. Andrews, and B. Shabani, “Dimensionless analysis of the global techno-economic feasibility of solar-hydrogen systems for constant year-round power supply”, International Journal of Hydrogen Energy, Vol. 37, pp. 6-18. 2012.

N. Akoubi, J. Ben Salem, and L. El Amraou, “Combination of artificial neural network-based approaches to control a grid-connected photovoltaic source under partial shading condition”, International Journal of Renewable Energy Research, Vol. 13, pp. 778-789, 2023.

A. Sahbani, K. Cherif, and K. Ben Saad, “Multiphase Interleaved Bidirectional DC-DC Converter for Electric Vehicles and Smart Grid Applications”, International Journal of Smart Grid, Vol. 4, pp. 80-87, 2020.

R. Tu, Y. Gai, B. Farooq, D. Posen, and M. Hatzopoulou, “Electric vehicle charging optimization to minimize marginal greenhouse gas emissions from power generation”, Applied Energy, Vol. 277, pp. 1-10, 2020.

A. Mustafa Colak, and O. Kaplan, “A Review on the Efficiency Increment in a Power System Using Smart Grid Technologies”, 9th International Conference on Smart Grid (icSmartGrid) Conference, Setubal, Portugal, 29 June- 01 July 2021.

K. Okedu, and W. ALSalmani, “Smart Grid Technologies in Gulf Cooperation Council (GCC) Countries: Challenges and Opportunities”, International Journal of Smart Grid, Vol. 3, pp. 92-102, 2019.

A. Foley, B. Tyther, P. Calnan, and B. Gallachoir, “Impacts of electric vehicle charging under electricity market operations”, Applied Energy, Vol. 101, pp. 93-102, 2013.

L. Jian, Y. Zheng, X. Xiao, and C.C. Chan, “Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid”, Applied Energy, Vol. 146, pp. 150-161, 2015.

J. García-Villalobos, I. Zamora, K. Knezovi?, and M. Marinelli, “Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks”, Applied Energy, Vol. 180, pp. 155-168, 2016.

C. Peng, J. Zou, L. Lian, and L. Li, “An optimal dispatching strategy for V2G aggregator participating in supplementary frequency regulation considering EV driving demand and aggregator's benefits”, Applied Energy, Vol. 190, pp. 591-599, 2017.

S. Khemakhem, M. Rekik, and L. Krichen, “A flexible control strategy of plug-in electric vehicles operating in seven modes for smoothing load power curves in smart grid”, Energy, Vol. 118, pp. 197-208, 2017.

M. Rekik, and L. Krichen, “Double Layer Optimization Approach of Plug-in Electric Vehicle for Participation in Smart Grid Ancillary Services and Energy Markets”, International Journal of Renewable Energy Research, Vol. 11, pp. 1107-1123, 2021.

Z. Yao, Z. Wang, and L. Ran, “Smart charging and discharging of electric vehicles based on multi-objective robust optimization in smart cities”, Applied Energy, Vol. 343, pp. 121185, 2023.

L. Jian, Y. Zheng, and Z. Shao, “High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles”, Applied Energy, Vol. 186, pp. 46-55, 2017.

Y. Shi, H. Duong Tuan, A. V. Savkin, T. Q. Duong, and H. Vincent Poor, “Model Predictive Control for Smart Grids with Multiple Electric-Vehicle Charging Stations”, IEEE Transactions on Smart Grid, Vol. 10, pp. 2127-2136, 2019.

A. Al-Abri, W. Khalil, and K. E. Okedu, “Electricity Sector of Oman and Prospects of Advanced Metering Infrastructures”, International Journal of Smart Grid, Vol. 6, pp. 1-12, 2022.

A. Tiwari, and N. M. Pindoriya, “Automated Demand Response in Smart Distribution Grid: A Review on Metering Infrastructure, Communication Technology and Optimization Models”, Electric Power Systems Research, Vol. 206, pp. 107835, 2022.

A. Al Khas, and I. Cicek, “SHA-512 based Wireless Authentication Scheme for Smart Battery Management Systems”, 8th International Conference on Renewable Energy Research and Applications (ICRERA) Conference, Brasov, Romania, pp. 968-972, 03-06 November 2019.

L. Jiang, Y. Li, J. Ma, Y. Cao, C. Huang, Y. Xu, H. Chen, and Y. Huang, “Hybrid charging strategy with adaptive current control of lithium-ion battery for electric vehicles”, Renewable Energy, Vol. 160, pp. 1385-1395, 2020.

S. Abada, G. Marlair, A. Lecocq, M. Petit, V. Sauvant-Moynot, and F. Huet, “Safety focused modeling of lithium-ion batteries: A review”, Journal of Power Source, Vol. 306, pp. 178-192, 2016.

R. Sadoun, N. Rizoug, P. Bartholomeüs, B. Barbedette, and P. Le Moigne, “Optimal Sizing of Hybrid Supply for Electric Vehicle Using Li-ion Battery and Supercapacitor”, IEEE , Chicago, IL, USA, pp. 1-8, 06-09 September 2011.

O. Tremblay, and L. Dessaint, “Experimental validation of a battery dynamic model for EV applications”, World Electric Vehicle, Vol. 3, pp. 289-298, 2009.

S. Khemakhem, M. Rekik, and L. Krichen, “Plug-in electric vehicle control in smart grid”, 16th international conference on Sciences and Techniques of Automatic control & Computer Engineering (STA) Conference, Monastir, Tunisia, pp. 188-192, 21-23 December 2015.




DOI (PDF): https://doi.org/10.20508/ijrer.v15i1.14710.g9015

Refbacks

  • There are currently no refbacks.


Online ISSN: 1309-0127

Publisher: Gazi University

IJRER is indexed in EI Compendex, SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics)and CrossRef.

IJRER has been indexed in Emerging Sources Citation Index from 2016 in web of science.

WEB of SCIENCE in 2025; 

h=35,

Average citation per item=6.59

Last three Years Impact Factor=(1947+1753+1586)/(146+201+78)=5286/425=12.43

Category Quartile:Q4