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Sizing of Hybrid Power System with varying current type using numerical probabilistic approach

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  • Liu, Wen Hui
  • Wan Alwi, Sharifah Rafidah
  • Hashim, Haslenda
  • Lim, Jeng Shiun
  • Mohammad Rozali, Nor Erniza
  • Ho, Wai Shin

Abstract

Power Pinch Analysis is an established method to target the design parameter of a Hybrid Power System. This study aims to develop an extended tool known as Probability-Power Pinch Analysis (P-PoPA) using probability theory to simplify the process of Power Pinch Analysis in considering efficiency losses. The method targets for a Hybrid Power System with various current type from generation to demand, generation to storage, or storage to demand. The procedure of the method is illustrated using an electricity-deficit scenario where both AC–DC generation and AC–DC demand are present. The new methodology which adapts the same concept as the Stand-Alone Hybrid System Power Pinch Analysis utilizes data extracted from an ideal (considering no efficiency losses) graphical Power Pinch Analysis and Power Cascade Table and multiplying the extracted data with a probability factor to obtain an estimated target (considering efficiency losses) for the power system. In this study, three design parameters are determined for a system with 208kWh AC source and 50kWh DC source and 170kWh AC demand and 98kWh DC demand. The external energy that is needed for the system is identified as 38.93kWh and the energy capacity of energy storage is 42.20kWh and power capacity of energy storage is 8.79kW. The result is then compared with the existing cascade analysis, Power Cascade Table and Storage Cascade Table. The determined sizing values have a close estimation to that from cascading analysis (considering efficiency losses), with a maximum percentage difference of 2.3%.

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  • Liu, Wen Hui & Wan Alwi, Sharifah Rafidah & Hashim, Haslenda & Lim, Jeng Shiun & Mohammad Rozali, Nor Erniza & Ho, Wai Shin, 2016. "Sizing of Hybrid Power System with varying current type using numerical probabilistic approach," Applied Energy, Elsevier, vol. 184(C), pages 1364-1373.
    • Handle: RePEc:eee:appene:v:184:y:2016:i:c:p:1364-1373
    DOI: 10.1016/j.apenergy.2016.06.035
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    1. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    2. Klemeš, Jiří Jaromír & Varbanov, Petar Sabev & Walmsley, Timothy G. & Jia, Xuexiu, 2018. "New directions in the implementation of Pinch Methodology (PM)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 439-468.
    3. Tayerani Charmchi, Amir Saman & Ifaei, Pouya & Yoo, ChangKyoo, 2021. "Smart supply-side management of optimal hydro reservoirs using the water/energy nexus concept: A hydropower pinch analysis," Applied Energy, Elsevier, vol. 281(C).
    4. Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír & Cheong, Jing Shenn, 2019. "Probability-Power Pinch Analysis targeting approach for diesel/biodiesel plant integration into hybrid power systems," Energy, Elsevier, vol. 187(C).
    5. Norbu, Sonam & Bandyopadhyay, Santanu, 2017. "Power Pinch Analysis for optimal sizing of renewable-based isolated system with uncertainties," Energy, Elsevier, vol. 135(C), pages 466-475.
    6. Al-Quraan, A. & Al-Mhairat, B., 2024. "Economic predictive control-based sizing and energy management for grid-connected hybrid renewable energy systems," Energy, Elsevier, vol. 302(C).
    7. Mohammad Rozali, Nor Erniza & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír, 2016. "Sensitivity analysis of hybrid power systems using Power Pinch Analysis considering Feed-in Tariff," Energy, Elsevier, vol. 116(P2), pages 1260-1268.
    8. Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    9. Lee, Jui-Yuan & Aviso, Kathleen B. & Tan, Raymond R., 2019. "Multi-objective optimisation of hybrid power systems under uncertainties," Energy, Elsevier, vol. 175(C), pages 1271-1282.
    10. Mohammad Rozali, Nor Erniza & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír, 2016. "Process Integration for Hybrid Power System supply planning and demand management – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 834-842.
    11. Bizon, Nicu, 2018. "Optimal operation of fuel cell/wind turbine hybrid power system under turbulent wind and variable load," Applied Energy, Elsevier, vol. 212(C), pages 196-209.

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