Optimizing Energy Supply and Scheduling for a DC Microgrid-Integrated Electric Vehicle Charging Station

Nasri Elmehdi, Tarik Jarou, Wissam Jenkal, Younes EL KOUDIA, Jawad Abdouni, Sofia Idriss

Abstract


The adoption of electric vehicles (EVs) has witnessed a notable surge in recent years, driven by escalating fossil fuel costs and the concurrent increase in carbon dioxide (CO2) emissions. The proliferation of EV-charging stations, reliant on existing utility power grid systems, has, however, imposed heightened stress on the utility grid and escalated load demand at the distribution side. The efficiency of EV charging based on DC grids exceeds that of AC distribution owing to its superior reliability, higher power conversion efficiency, ease of integration with renewable energy sources (RESs), and seamless incorporation of energy storage units (ESUs). To address the strain on the utility grid, storing RES-generated power locally in ESUs emerges as a viable alternative. Furthermore, effective management and control strategies are imperative to sustain EV charging demand at microgrid levels. This paper introduces a real-time energy management framework tailored for EV charging within a DC microgrid encompassing a wind turbine system (WT), photovoltaic system (PV), energy storage unit (ESU), AC load, and EV charging system. The primary objective is to ensure the comprehensive stability of voltage and frequencies across the associated network. The proposed scheme relies on Fuzzy intelligent control of the ESU system to optimize energy flow within the microgrid. Notably, it accommodates the diverse energy flow modes contingent upon the availability of each component within the DC microgrid. Simulation results, conducted using Matlab/Simulink, are presented and deliberated upon in this paper. The model is also applied to a case study involving a microgrid project implemented in the capital of Ethiopia: Addis Ababa.


Keywords


DC microgrid; Fuzzy logic controller; Electric Vehicle (EV); EV charging ; Energy management system; Renewable energy systems (RESs); Energy storage unit (ESU)

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References


J. Woodcock et al., “Public health benefits of strategies to reduce greenhouse-gas emissions: urban land transport,” The Lancet, vol. 374, no. 9705, pp. 1930–1943, Dec. 2009, doi: 10.1016/S0140-6736(09)61714-1.

“Distributed generation: definition, benefits and issues - ScienceDirect.” Accessed: Jan. 26, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0301421503003069

E. Nasri, T. Jarou, J. Abdouni, and Y. Koudia, “Enhancing Energy Reliability and Balance with Fuzzy Logic Controlled Microgrid System,” Jordan J. Electr. Eng., vol. 9, no. 4, p. 591, 2023, doi: 10.5455/jjee.204-1680652201.

E. Nasri, T. Jarou, S. Benchikh, and Y. Elkoudia, “Reliable energy supply and voltage control for hybrid microgrid by pid controlled with integrating of an EV charging station,” Diagnostyka, vol. 24, no. 4, pp. 1–11, Oct. 2023, doi: 10.29354/diag/174145.

R. H. Lasseter and P. Paigi, “Microgrid: a conceptual solution,” in 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), Jun. 2004, pp. 4285-4290 Vol.6. doi: 10.1109/PESC.2004.1354758.

Z. Liu, Y. Chen, R. Zhuo, and H. Jia, “Energy storage capacity optimization for autonomy microgrid considering CHP and EV scheduling,” Appl. Energy, vol. 210, pp. 1113–1125, Jan. 2018, doi: 10.1016/j.apenergy.2017.07.002.

A.-M. Koufakis, E. S. Rigas, N. Bassiliades, and S. D. Ramchurn, “Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 5, pp. 2128–2138, May 2020, doi: 10.1109/TITS.2019.2914087.

“Transactive Energy Management of PV-Based EV Integrated Parking Lots | IEEE Journals & Magazine | IEEE Xplore.” Accessed: Jan. 28, 2024. [Online]. Available: https://ieeexplore.ieee.org/document/9308954

J. Stiasny, T. Zufferey, G. Pareschi, D. Toffanin, G. Hug, and K. Boulouchos, “Sensitivity analysis of electric vehicle impact on low-voltage distribution grids,” Electr. Power Syst. Res., vol. 191, p. 106696, Feb. 2021, doi: 10.1016/j.epsr.2020.106696.

K. Sayed, A. G. Abo-Khalil, and A. S. Alghamdi, “Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources,” Energies, vol. 12, no. 22, Art. no. 22, Jan. 2019, doi: 10.3390/en12224240.

D. S. Abraham et al., “Fuzzy-Based Efficient Control of DC Microgrid Configuration for PV-Energized EV Charging Station,” Energies, vol. 16, no. 6, Art. no. 6, Jan. 2023, doi: 10.3390/en16062753.

K. A. Al Sumarmad, N. Sulaiman, N. I. A. Wahab, and H. Hizam, “Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers,” Energies, vol. 15, no. 1, Art. no. 1, Jan. 2022, doi: 10.3390/en15010303.

M. Ross, R. Hidalgo, C. Abbey, and G. Joós, “Energy storage system scheduling for an isolated microgrid,” IET Renew. Power Gener., vol. 5, no. 2, pp. 117–123, Mar. 2011, doi: 10.1049/iet-rpg.2009.0204.

L. Guo et al., “Energy Management System for Stand-Alone Wind-Powered-Desalination Microgrid,” IEEE Trans. Smart Grid, vol. 7, no. 2, pp. 1079–1087, Mar. 2016, doi: 10.1109/TSG.2014.2377374.

M. A. Hannan, M. M. Hoque, A. Mohamed, and A. Ayob, “Review of energy storage systems for electric vehicle applications: Issues and challenges,” Renew. Sustain. Energy Rev., vol. 69, pp. 771–789, Mar. 2017, doi: 10.1016/j.rser.2016.11.171.

K. Sayed, K. Nishida, H. A. Gabbar, and M. Nakaoka, “A new circuit topology for battery charger from 200V DC source to 12V for hybrid automotive applications,” in 2016 IEEE Smart Energy Grid Engineering (SEGE), Aug. 2016, pp. 317–321. doi: 10.1109/SEGE.2016.7589544.

R. H. Ashique, Z. Salam, M. J. Bin Abdul Aziz, and A. R. Bhatti, “Integrated photovoltaic-grid dc fast charging system for electric vehicle: A review of the architecture and control,” Renew. Sustain. Energy Rev., vol. 69, pp. 1243–1257, Mar. 2017, doi: 10.1016/j.rser.2016.11.245.

J. Liu, X. Huang, Y. Hong, and Z. Li, “Coordinated Control Strategy for Operation Mode Switching of DC Distribution Networks,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 2, pp. 334–344, Mar. 2020, doi: 10.35833/MPCE.2018.000780.

S. Borekci, E. Kandemir, and A. Kircay, “A Simpler Single-Phase Single-Stage Grid-Connected PV System with Maximum Power Point Tracking Controller,” Elektron. Ir Elektrotechnika, vol. 21, no. 4, Art. no. 4, Jul. 2015, doi: 10.5755/j01.eee.21.4.12782.

A. Kushwaha, M. Gopal, and B. Singh, “Q-Learning based Maximum Power Extraction for Wind Energy Conversion System With Variable Wind Speed,” IEEE Trans. Energy Convers., vol. 35, no. 3, pp. 1160–1170, Sep. 2020, doi: 10.1109/TEC.2020.2990937.

M. G. M. Abdolrasol, M. A. Hannan, S. M. S. Hussain, T. S. Ustun, M. R. Sarker, and P. J. Ker, “Energy Management Scheduling for Microgrids in the Virtual Power Plant System Using Artificial Neural Networks,” Energies, vol. 14, no. 20, Art. no. 20, Jan. 2021, doi: 10.3390/en14206507.

“World - Global Horizontal Irradiation (GHI) GIS Data, (Global Solar Atlas) | Data Catalog.” Accessed: Jan. 23, 2024. [Online]. Available: https://datacatalog.worldbank.org/search/dataset/0038645

“Energies | Free Full-Text | Feasibility and Techno-Economic Analysis of Electric Vehicle Charging of PV/Wind/Diesel/Battery Hybrid Energy System with Different Battery Technology.” Accessed: Jan. 23, 2024. [Online]. Available: https://www.mdpi.com/1996-1073/15/12/4364




DOI (PDF): https://doi.org/10.20508/ijrer.v16i3.15373.g9234

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