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Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid

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Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid. / Nasir, Tehreem; Raza, Safdar; Abrar, Muhammad et al.
In: Sensors, Vol. 21, No. 21, 7133, 27.10.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Nasir, T, Raza, S, Abrar, M, Muqeet, HAU, Jamil, H, Qayyum, F, cheikhrouhou, O, alassery, F & Hamam, H 2021, 'Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid', Sensors, vol. 21, no. 21, 7133. https://doi.org/10.3390/s21217133

APA

Nasir, T., Raza, S., Abrar, M., Muqeet, H. A. U., Jamil, H., Qayyum, F., cheikhrouhou, O., alassery, F., & Hamam, H. (2021). Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid. Sensors, 21(21), Article 7133. https://doi.org/10.3390/s21217133

Vancouver

Nasir T, Raza S, Abrar M, Muqeet HAU, Jamil H, Qayyum F et al. Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid. Sensors. 2021 Oct 27;21(21):7133. doi: 10.3390/s21217133

Author

Nasir, Tehreem ; Raza, Safdar ; Abrar, Muhammad et al. / Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid. In: Sensors. 2021 ; Vol. 21, No. 21.

Bibtex

@article{060274ed952a47b7b8e222ac211ebab7,
title = "Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid",
abstract = "High energy consumption, rising environmental concerns and depleting fossil fuels demand an increase in clean energy production. The enhanced resiliency, efficiency and reliability offered by microgrids with distributed energy resources (DERs) have shown to be a promising alternative to the conventional grid system. Large-sized commercial customers like institutional complexes have put significant efforts to promote sustainability by establishing renewable energy systems at university campuses. This paper proposes the integration of a photovoltaic (PV) system, energy storage system (ESS) and electric vehicles (EV) at a university campus. An optimal energy management system (EMS) is proposed to optimally dispatch the energy from available energy resources. The problem is mapped in a Linear optimization problem and simulations are carried out in MATLAB. Simulation results showed that the proposed EMS ensures the continuous power supply and decreases the energy consumption cost by nearly 45%. The impact of EV as a storage tool is also observed. EVs acting as a source of energy reduced the energy cost by 45.58% and as a load by 19.33%. The impact on the cost for continuous power supply in case of a power outage is also analyzed.",
author = "Tehreem Nasir and Safdar Raza and Muhammad Abrar and Muqeet, {Hafiz Abd ul} and Harun Jamil and Faiza Qayyum and omar cheikhrouhou and fawaz alassery and Habib Hamam",
year = "2021",
month = oct,
day = "27",
doi = "10.3390/s21217133",
language = "English",
volume = "21",
journal = "Sensors",
issn = "1424-8220",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "21",

}

RIS

TY - JOUR

T1 - Optimal Scheduling of Campus Microgrid Considering the Electric Vehicle Integration in Smart Grid

AU - Nasir, Tehreem

AU - Raza, Safdar

AU - Abrar, Muhammad

AU - Muqeet, Hafiz Abd ul

AU - Jamil, Harun

AU - Qayyum, Faiza

AU - cheikhrouhou, omar

AU - alassery, fawaz

AU - Hamam, Habib

PY - 2021/10/27

Y1 - 2021/10/27

N2 - High energy consumption, rising environmental concerns and depleting fossil fuels demand an increase in clean energy production. The enhanced resiliency, efficiency and reliability offered by microgrids with distributed energy resources (DERs) have shown to be a promising alternative to the conventional grid system. Large-sized commercial customers like institutional complexes have put significant efforts to promote sustainability by establishing renewable energy systems at university campuses. This paper proposes the integration of a photovoltaic (PV) system, energy storage system (ESS) and electric vehicles (EV) at a university campus. An optimal energy management system (EMS) is proposed to optimally dispatch the energy from available energy resources. The problem is mapped in a Linear optimization problem and simulations are carried out in MATLAB. Simulation results showed that the proposed EMS ensures the continuous power supply and decreases the energy consumption cost by nearly 45%. The impact of EV as a storage tool is also observed. EVs acting as a source of energy reduced the energy cost by 45.58% and as a load by 19.33%. The impact on the cost for continuous power supply in case of a power outage is also analyzed.

AB - High energy consumption, rising environmental concerns and depleting fossil fuels demand an increase in clean energy production. The enhanced resiliency, efficiency and reliability offered by microgrids with distributed energy resources (DERs) have shown to be a promising alternative to the conventional grid system. Large-sized commercial customers like institutional complexes have put significant efforts to promote sustainability by establishing renewable energy systems at university campuses. This paper proposes the integration of a photovoltaic (PV) system, energy storage system (ESS) and electric vehicles (EV) at a university campus. An optimal energy management system (EMS) is proposed to optimally dispatch the energy from available energy resources. The problem is mapped in a Linear optimization problem and simulations are carried out in MATLAB. Simulation results showed that the proposed EMS ensures the continuous power supply and decreases the energy consumption cost by nearly 45%. The impact of EV as a storage tool is also observed. EVs acting as a source of energy reduced the energy cost by 45.58% and as a load by 19.33%. The impact on the cost for continuous power supply in case of a power outage is also analyzed.

U2 - 10.3390/s21217133

DO - 10.3390/s21217133

M3 - Journal article

VL - 21

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 21

M1 - 7133

ER -