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Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes

Author

Listed:
  • Hafiz Abd ul Muqeet
  • Hafiz Mudassir Munir
  • Aftab Ahmad
  • Intisar Ali Sajjad
  • Guang-Jun Jiang
  • Hong-Xia Chen

Abstract

Present power systems face problems such as rising energy charges and greenhouse gas (GHG) releases. These problems may be assuaged by participating distributed generators (DGs) and demand response (DR) policies in the distribution system (DS). The main focus of this paper is to propose an energy management system (EMS) approach for campus microgrid ( µ G). For this purpose, a Pakistani university has been investigated and an optimal solution has been proposed. Conventionally, it contains electricity from the national grid only as a supply to fulfil the energy demand. Under the proposed setup, it contains campus owned nondispatchable DGs such as solar photovoltaic (PV) panels and microturbines (MTs) as dispatchable sources. To overcome the random nature of solar irradiance, station battery has been integrated as energy storage. The subsequent nonlinear mathematical problem has been scheduled by mixed-integer nonlinear programming (MINLP) in MATLAB for saving energy cost and battery aging cost. The framework has been validated under deterministic and stochastic environments. Among random parameters, solar irradiance and load have been taken into consideration. Case studies have been carried out considering the demand response strategies to analyze the proposed model. The obtained results show that optimal management and scheduling of storage in the presence of DGs mutually benefit by minimizing consumption cost (customer) and grid load (utility) which show the efficacy of the proposed model. The results obtained are compared to the existing literature and a significant cost reduction is found.

Suggested Citation

  • Hafiz Abd ul Muqeet & Hafiz Mudassir Munir & Aftab Ahmad & Intisar Ali Sajjad & Guang-Jun Jiang & Hong-Xia Chen, 2021. "Optimal Operation of the Campus Microgrid considering the Resource Uncertainty and Demand Response Schemes," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-18, May.
  • Handle: RePEc:hin:jnlmpe:5569701
    DOI: 10.1155/2021/5569701
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    Cited by:

    1. Zheng, Shiyong & Shahzad, Muhammad & Asif, Hafiz Muhammad & Gao, Jing & Muqeet, Hafiz Abdul, 2023. "Advanced optimizer for maximum power point tracking of photovoltaic systems in smart grid: A roadmap towards clean energy technologies," Renewable Energy, Elsevier, vol. 206(C), pages 1326-1335.
    2. Amad Ali & Hafiz Abdul Muqeet & Tahir Khan & Asif Hussain & Muhammad Waseem & Kamran Ali Khan Niazi, 2023. "IoT-Enabled Campus Prosumer Microgrid Energy Management, Architecture, Storage Technologies, and Simulation Tools: A Comprehensive Study," Energies, MDPI, vol. 16(4), pages 1-19, February.

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