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Eco-Emission Analysis of Multi-Carrier Microgrid Integrated with Compressed Air and Power-to-Gas Energy Storage Technologies

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  • Khashayar Hamedi

    (Department of Architectural Engineering, Ayatollah Amoli Branch, Islamic Azad University, Amol 46151-43358, Iran)

  • Shahrbanoo Sadeghi

    (Department of Health, Safety, and Environment, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran 19839-63113, Iran)

  • Saeed Esfandi

    (School of Urban Planning, College of Fine Arts, University of Tehran, Tehran 14174-66191, Iran)

  • Mahdi Azimian

    (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University, Kashan 87159-98151, Iran)

  • Hessam Golmohamadi

    (Department of Computer Science, Aalborg University, 9220 Aalborg, Denmark)

Abstract

Growing concerns about global greenhouse gas emissions have led power systems to utilize clean and highly efficient resources. In the meantime, renewable energy plays a vital role in energy prospects worldwide. However, the random nature of these resources has increased the demand for energy storage systems. On the other hand, due to the higher efficiency of multi-energy systems compared to single-energy systems, the development of such systems, which are based on different types of energy carriers, will be more attractive for the utilities. Thus, this paper represents a multi-objective assessment for the operation of a multi-carrier microgrid (MCMG) in the presence of high-efficiency technologies comprising compressed air energy storage (CAES) and power-to-gas (P2G) systems. The objective of the model is to minimize the operation cost and environmental pollution. CAES has a simple-cycle mode operation besides the charging and discharging modes to provide more flexibility in the system. Furthermore, the demand response program is employed in the model to mitigate the peaks. The proposed system participates in both electricity and gas markets to supply the energy requirements. The weighted sum approach and fuzzy-based decision-making are employed to compromise the optimum solutions for conflicting objective functions. The multi-objective model is examined on a sample system, and the results for different cases are discussed. The results show that coupling CAES and P2G systems mitigate the wind power curtailment and minimize the cost and pollution up to 14.2% and 9.6%, respectively.

Suggested Citation

  • Khashayar Hamedi & Shahrbanoo Sadeghi & Saeed Esfandi & Mahdi Azimian & Hessam Golmohamadi, 2021. "Eco-Emission Analysis of Multi-Carrier Microgrid Integrated with Compressed Air and Power-to-Gas Energy Storage Technologies," Sustainability, MDPI, vol. 13(9), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4681-:d:541316
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    1. Habib, Salman & Aghakhani, Sina & Ghasempour Nejati, Mobin & Azimian, Mahdi & Jia, Youwei & Ahmed, Emad M., 2023. "Energy management of an intelligent parking lot equipped with hydrogen storage systems and renewable energy sources using the stochastic p-robust optimization approach," Energy, Elsevier, vol. 278(C).
    2. Ann-Kathrin Klaas & Hans-Peter Beck, 2021. "A MILP Model for Revenue Optimization of a Compressed Air Energy Storage Plant with Electrolysis," Energies, MDPI, vol. 14(20), pages 1-21, October.
    3. Mahdi Azimian & Vahid Amir & Reza Habibifar & Hessam Golmohamadi, 2021. "Probabilistic Optimization of Networked Multi-Carrier Microgrids to Enhance Resilience Leveraging Demand Response Programs," Sustainability, MDPI, vol. 13(11), pages 1-30, May.

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