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Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria

Author

Listed:
  • Tekai Eddine Khalil Zidane

    (School of Electrical Systems Engineering, Universiti Malaysia Perlis, Arau 02600, Malaysia)

  • Mohd Rafi Adzman

    (School of Electrical Systems Engineering, Universiti Malaysia Perlis, Arau 02600, Malaysia
    Centre of Excellence for Renewable Energy (CERE), School of Electrical Systems Engineering, Universiti Malaysia Perlis, Arau 02600, Malaysia)

  • Mohammad Faridun Naim Tajuddin

    (School of Electrical Systems Engineering, Universiti Malaysia Perlis, Arau 02600, Malaysia)

  • Samila Mat Zali

    (School of Electrical Systems Engineering, Universiti Malaysia Perlis, Arau 02600, Malaysia)

  • Ali Durusu

    (Department of Electrical Engineering, Davutpasa Campus, Yildiz Technical University, Istanbul 34220, Turkey)

  • Saad Mekhilef

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
    School of Software and Electrical Engineering, Swinburne University of Technology, Victoria 3122, Australia
    Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Considering the recent drop (up to 86%) in photovoltaic (PV) module prices from 2010 to 2017, many countries have shown interest in investing in PV plants to meet their energy demand. In this study, a detailed design methodology is presented to achieve high benefits with low installation, maintenance and operation costs of PV plants. This procedure includes in detail the semi-hourly average time meteorological data from the location to maximise the accuracy and detailed characteristics of different PV modules and inverters. The minimum levelised cost of energy (LCOE) and maximum annual energy are the objective functions in this proposed procedure, whereas the design variables are the number of series and parallel PV modules, the number of PV module lines per row, tilt angle and orientation, inter-row space, PV module type, and inverter structure. The design problem was solved using a recent hybrid algorithm, namely, the grey wolf optimiser-sine cosine algorithm. The high performance for LCOE-based design optimisation in economic terms with lower installation, maintenance and operation costs than that resulting from the use of maximum annual energy objective function by 12%. Moreover, sensitivity analysis showed that the PV plant performance can be improved by decreasing the PV module annual reduction coefficient.

Suggested Citation

  • Tekai Eddine Khalil Zidane & Mohd Rafi Adzman & Mohammad Faridun Naim Tajuddin & Samila Mat Zali & Ali Durusu & Saad Mekhilef, 2020. "Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria," Energies, MDPI, vol. 13(11), pages 1-28, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2776-:d:365730
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    References listed on IDEAS

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    2. Tomasz Popławski & Sebastian Dudzik & Piotr Szeląg & Janusz Baran, 2021. "A Case Study of a Virtual Power Plant (VPP) as a Data Acquisition Tool for PV Energy Forecasting," Energies, MDPI, vol. 14(19), pages 1-24, September.

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