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The Potential Role of Hybrid Renewable Energy System for Grid Intermittency Problem: A Techno-Economic Optimisation and Comparative Analysis

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Listed:
  • Muhammad Paend Bakht

    (Centre of Electrical Energy Systems, School of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia
    Department of Electrical Engineering, Balochistan University of Information Technology, Engineering and Management Sciences (BUITMS), Quetta 87300, Pakistan)

  • Zainal Salam

    (Centre of Electrical Energy Systems, School of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia)

  • Mehr Gul

    (Department of Electrical Engineering, Balochistan University of Information Technology, Engineering and Management Sciences (BUITMS), Quetta 87300, Pakistan)

  • Waqas Anjum

    (Department of Electronic Engineering, Faculty of Engineering, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

  • Mohamad Anuar Kamaruddin

    (School of Industrial Technology, Universiti Sains Malaysia (USM), Gelugor 11800, Malaysia)

  • Nuzhat Khan

    (School of Industrial Technology, Universiti Sains Malaysia (USM), Gelugor 11800, Malaysia)

  • Abba Lawan Bukar

    (Centre of Electrical Energy Systems, School of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia
    Department of Electrical and Electronic Engineering, University of Maiduguri, Maiduguri 600104, Nigeria)

Abstract

The renewed interest for power generation using renewables due to global trends provides an opportunity to rethink the approach to address the old yet existing load shedding problem. In the literature, limited studies are available that address the load shedding problem using a hybrid renewable energy system. This paper aims to fill this gap by proposing a techno-economic optimisation of a hybrid renewable energy system to mitigate the effect of load shedding at the distribution level. The proposed system in this work is configured using a photovoltaic array, wind turbines, an energy storage unit (of batteries), and a diesel generator system. The proposed system is equipped with a rule-based energy management scheme to ensure efficient utilisation and scheduling of the sources. The sizes of the photovoltaic array, wind turbine unit, and the batteries are optimised via the grasshopper optimisation algorithm based on the multi-criterion decision that includes loss of power supply probability, levelised cost of electricity, and payback period. The results for the actual case study in Quetta, Pakistan, show that the optimum sizes of the photovoltaic array, wind turbines, and the batteries are 35.75 kW, 10 kW, and 28.8 kWh, respectively. The sizes are based on the minimum values of levelised cost of electricity (6.64 cents/kWh), loss of power supply probability (0.0092), and payback period (7.4 years). These results are compared with conventional methods (generators, uninterruptible power supply, and a combined system of generator and uninterruptible power supply system) commonly used to deal with the load shedding problem. The results show that the renewable based hybrid system is a reliable and cost-effective option to address grid intermittency problem.

Suggested Citation

  • Muhammad Paend Bakht & Zainal Salam & Mehr Gul & Waqas Anjum & Mohamad Anuar Kamaruddin & Nuzhat Khan & Abba Lawan Bukar, 2022. "The Potential Role of Hybrid Renewable Energy System for Grid Intermittency Problem: A Techno-Economic Optimisation and Comparative Analysis," Sustainability, MDPI, vol. 14(21), pages 1-29, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14045-:d:956083
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    References listed on IDEAS

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    1. Sinha, Sunanda & Chandel, S.S., 2015. "Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 755-769.
    2. Khawaja, Yara & Allahham, Adib & Giaouris, Damian & Patsios, Charalampos & Walker, Sara & Qiqieh, Issa, 2019. "An integrated framework for sizing and energy management of hybrid energy systems using finite automata," Applied Energy, Elsevier, vol. 250(C), pages 257-272.
    3. Zhang, Yijie & Ma, Tao & Elia Campana, Pietro & Yamaguchi, Yohei & Dai, Yanjun, 2020. "A techno-economic sizing method for grid-connected household photovoltaic battery systems," Applied Energy, Elsevier, vol. 269(C).
    4. Sultana, U. & Khairuddin, Azhar B. & Sultana, Beenish & Rasheed, Nadia & Qazi, Sajid Hussain & Malik, Nimra Riaz, 2018. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm," Energy, Elsevier, vol. 165(PA), pages 408-421.
    5. Ilinca, Adrian & McCarthy, Ed & Chaumel, Jean-Louis & Rétiveau, Jean-Louis, 2003. "Wind potential assessment of Quebec Province," Renewable Energy, Elsevier, vol. 28(12), pages 1881-1897.
    6. Chin, Vun Jack & Salam, Zainal & Ishaque, Kashif, 2015. "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, Elsevier, vol. 154(C), pages 500-519.
    7. Abraham Alem Kebede & Maitane Berecibar & Thierry Coosemans & Maarten Messagie & Towfik Jemal & Henok Ayele Behabtu & Joeri Van Mierlo, 2020. "A Techno-Economic Optimization and Performance Assessment of a 10 kW P Photovoltaic Grid-Connected System," Sustainability, MDPI, vol. 12(18), pages 1-29, September.
    8. Ruben Zieba Falama & Felix Ngangoum Welaji & Abdouramani Dadjé & Virgil Dumbrava & Noël Djongyang & Chokri Ben Salah & Serge Yamigno Doka, 2021. "A Solution to the Problem of Electrical Load Shedding Using Hybrid PV/Battery/Grid-Connected System: The Case of Households’ Energy Supply of the Northern Part of Cameroon," Energies, MDPI, vol. 14(10), pages 1-23, May.
    9. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
    10. Waqas Anjum & Abdul Rashid Husain & Junaidi Abdul Aziz & Syed Muhammad Fasih ur Rehman & Muhammad Paend Bakht & Hasan Alqaraghuli, 2022. "A Robust Dynamic Control Strategy for Standalone PV System under Variable Load and Environmental Conditions," Sustainability, MDPI, vol. 14(8), pages 1-27, April.
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    1. Maksymilian Homa & Anna Pałac & Maciej Żołądek & Rafał Figaj, 2022. "Small-Scale Hybrid and Polygeneration Renewable Energy Systems: Energy Generation and Storage Technologies, Applications, and Analysis Methodology," Energies, MDPI, vol. 15(23), pages 1-52, December.

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