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考虑智能电网中电动汽车整合的校园微电网优化调度

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

作者信息

Nasir Tehreem, Raza Safdar, Abrar Muhammad, Muqeet Hafiz Abdul, Jamil Harun, Qayyum Faiza, Cheikhrouhou Omar, Alassery Fawaz, Hamam Habib

机构信息

Department of Electrical Engineering, NFC Institute of Engineering and Technology, Multan 60000, Pakistan.

Department of Electrical Engineering, Bahauddin Zakariya University, Multan 60000, Pakistan.

出版信息

Sensors (Basel). 2021 Oct 27;21(21):7133. doi: 10.3390/s21217133.

DOI:10.3390/s21217133
PMID:34770439
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8588264/
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 () 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.

摘要

高能耗、日益增长的环境问题以及不断枯竭的化石燃料,都要求增加清洁能源的生产。具有分布式能源资源(DER)的微电网所具备的更高弹性、效率和可靠性,已被证明是传统电网系统的一个有前景的替代方案。像机构建筑群这样的大型商业客户,已通过在大学校园建立可再生能源系统,为促进可持续发展付出了巨大努力。本文提出在大学校园整合光伏(PV)系统、储能系统()和电动汽车(EV)。提出了一种最优能源管理系统(EMS),以最优地调度来自可用能源资源的能量。该问题被映射为一个线性优化问题,并在MATLAB中进行了仿真。仿真结果表明,所提出的EMS确保了持续供电,并将能源消耗成本降低了近45%。还观察到了电动汽车作为储能工具的影响。电动汽车作为能源来源时,能源成本降低了45.58%,作为负载时降低了19.33%。还分析了停电情况下对持续供电成本的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/610354913d69/sensors-21-07133-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/9e84f32a2da5/sensors-21-07133-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/610354913d69/sensors-21-07133-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/9380807415d8/sensors-21-07133-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/b88f20ccd1e3/sensors-21-07133-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/9049d778c61f/sensors-21-07133-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/390ba219c4c3/sensors-21-07133-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/c4a09ea0ef66/sensors-21-07133-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/042caca5de58/sensors-21-07133-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/bbb3b597ba77/sensors-21-07133-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/263db1af1973/sensors-21-07133-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/b2a7fd5bb0fe/sensors-21-07133-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/9e84f32a2da5/sensors-21-07133-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b90c/8588264/610354913d69/sensors-21-07133-g012.jpg

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