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Demand side management for remote area power supply systems incorporating solar irradiance model

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  • Al-Alawi, Ali
  • Islam, S.M

Abstract

This paper presents a technique for generating the daily electricity load profile for remote areas in the Middle East from first principles, using diversified demand. The generated load profile includes the energy required to run a small desalination unit to provide the necessary freshwater. Demand side management (DSM) is used in this study to smooth out the daily peaks and fill valleys in the load curve to make the most efficient use of energy resources. Finally, the load profile is compared with real data for six houses collected from Safri area in the Sultanate of Oman. These data may be used as the basis to obtain load profiles of other remote areas of the Middle East since the weather and social factors are similar. The modified hourly variation factor based on weather and economic and social factors of the Middle East is obtained.

Suggested Citation

  • Al-Alawi, Ali & Islam, S.M, 2004. "Demand side management for remote area power supply systems incorporating solar irradiance model," Renewable Energy, Elsevier, vol. 29(13), pages 2027-2036.
    • Handle: RePEc:eee:renene:v:29:y:2004:i:13:p:2027-2036
    DOI: 10.1016/j.renene.2004.03.006
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    References listed on IDEAS

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    1. Alawaji, Saleh & Smiai, Mohammed Salah & Rafique, Shah & Stafford, Byron, 1995. "PV-powered water pumping and desalination plant for remote areas in Saudi Arabia," Applied Energy, Elsevier, vol. 52(2-3), pages 283-289.
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    Cited by:

    1. Mayank Singh & Rakesh Chandra Jha, 2019. "Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization," Energies, MDPI, vol. 12(3), pages 1-25, January.
    2. Rajanna, S. & Saini, R.P., 2016. "Employing demand side management for selection of suitable scenario-wise isolated integrated renewal energy models in an Indian remote rural area," Renewable Energy, Elsevier, vol. 99(C), pages 1161-1180.
    3. Lagorse, Jeremy & Paire, Damien & Miraoui, Abdellatif, 2010. "A multi-agent system for energy management of distributed power sources," Renewable Energy, Elsevier, vol. 35(1), pages 174-182.
    4. Gupta, Ajai & Saini, R.P. & Sharma, M.P., 2011. "Modelling of hybrid energy system—Part III: Case study with simulation results," Renewable Energy, Elsevier, vol. 36(2), pages 474-481.
    5. Yilmaz, Pelin & Hakan Hocaoglu, M. & Konukman, Alp Er S., 2008. "A pre-feasibility case study on integrated resource planning including renewables," Energy Policy, Elsevier, vol. 36(3), pages 1223-1232, March.
    6. Yuan, Shengxi & Kocaman, Ayse Selin & Modi, Vijay, 2017. "Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente," Renewable Energy, Elsevier, vol. 105(C), pages 167-174.
    7. Elisa Peñalvo-López & Ángel Pérez-Navarro & Elías Hurtado & F. Javier Cárcel-Carrasco, 2019. "Comprehensive Methodology for Sustainable Power Supply in Emerging Countries," Sustainability, MDPI, vol. 11(19), pages 1-22, September.
    8. Kallel, Randa & Boukettaya, Ghada & Krichen, Lotfi, 2015. "Demand side management of household appliances in stand-alone hybrid photovoltaic system," Renewable Energy, Elsevier, vol. 81(C), pages 123-135.

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