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Transshipment model-based linear programming formulation for targeting hybrid power systems with power loss considerations

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  • Chen, Cheng-Liang
  • Lai, Chieh-Ting
  • Lee, Jui-Yuan

Abstract

This article aims at targeting the minimum electricity outsourced from the grid and the minimum battery capacity for temporal storage of surplus power in a HPS (hybrid power systems) with known power demands and RE (renewable energy) sources. The given continuous or intermittent power demands and RE supplies can be AC (alternating current) or DC (direct current) with known average power ratings without uncertainty. An ETM (expanded transshipment model) is proposed to determine the allocation of electricity generated from RE sources as well as the storage and outsourcing policies for electricity surplus and deficit. This model also considers possible power losses from the conversion between AC and DC, the charging (for storage) and discharging of electricity (to supplement RE supply), and self-discharge during storage. The problem of targeting the electricity outsourcing and storage for an HPS is formulated as a LP (linear program). A literature example is used to demonstrate the application of the proposed ETM. The promising results show that the proposed model can provide preliminary analysis for optimal power management in an HPS, and is an improved method compared to the PPA (power pinch analysis).

Suggested Citation

  • Chen, Cheng-Liang & Lai, Chieh-Ting & Lee, Jui-Yuan, 2014. "Transshipment model-based linear programming formulation for targeting hybrid power systems with power loss considerations," Energy, Elsevier, vol. 75(C), pages 24-30.
    • Handle: RePEc:eee:energy:v:75:y:2014:i:c:p:24-30
    DOI: 10.1016/j.energy.2014.05.059
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    References listed on IDEAS

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    1. Mohammad Rozali, Nor Erniza & Wan Alwi, Sharifah Rafidah & Abdul Manan, Zainuddin & Klemeš, Jiří Jaromír & Hassan, Mohammad Yusri, 2013. "Process integration of hybrid power systems with energy losses considerations," Energy, Elsevier, vol. 55(C), pages 38-45.
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    6. Chen, Cheng-Liang & Lai, Chieh-Ting & Lee, Jui-Yuan, 2014. "Transshipment model-based MILP (mixed-integer linear programming) formulation for targeting and design of hybrid power systems," Energy, Elsevier, vol. 65(C), pages 550-559.
    7. Wan Alwi, Sharifah Rafidah & Mohammad Rozali, Nor Erniza & Abdul-Manan, Zainuddin & Klemeš, Jiří Jaromír, 2012. "A process integration targeting method for hybrid power systems," Energy, Elsevier, vol. 44(1), pages 6-10.
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    Cited by:

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    3. 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.
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    5. Giaouris, Damian & Papadopoulos, Athanasios I. & Patsios, Charalampos & Walker, Sara & Ziogou, Chrysovalantou & Taylor, Phil & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos, 2018. "A systems approach for management of microgrids considering multiple energy carriers, stochastic loads, forecasting and demand side response," Applied Energy, Elsevier, vol. 226(C), pages 546-559.
    6. Abhi Chatterjee & Daniel Burmester & Alan Brent & Ramesh Rayudu, 2019. "Research Insights and Knowledge Headways for Developing Remote, Off-Grid Microgrids in Developing Countries," Energies, MDPI, vol. 12(10), pages 1-19, May.
    7. Silvente, Javier & Aguirre, Adrián M. & Zamarripa, Miguel A. & Méndez, Carlos A. & Graells, Moisès & Espuña, Antonio, 2015. "Improved time representation model for the simultaneous energy supply and demand management in microgrids," Energy, Elsevier, vol. 87(C), pages 615-627.
    8. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2020. "Optimal configuration of battery energy storage system with multiple types of batteries based on supply-demand characteristics," Energy, Elsevier, vol. 206(C).
    9. Nadjemi, O. & Nacer, T. & Hamidat, A. & Salhi, H., 2017. "Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1352-1365.
    10. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    11. Theo, Wai Lip & Lim, Jeng Shiun & Wan Alwi, Sharifah Rafidah & Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Abdul-Manan, Zainuddin, 2016. "An MILP model for cost-optimal planning of an on-grid hybrid power system for an eco-industrial park," Energy, Elsevier, vol. 116(P2), pages 1423-1441.
    12. 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.
    13. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.

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