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A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system

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  • Rana, Md Masud
  • Romlie, Mohd Fakhizan
  • Abdullah, Mohd Faris
  • Uddin, Moslem
  • Sarkar, Md Rasel

Abstract

A novel peak load shaving algorithm has been proposed in this study for peak shaving application in hybrid PV-BESS connected Isolated Microgrid (IMG) system. This algorithm will help an IMG system to operate its generation systems optimally and economically along with PV generation unit. An IMG model has been developed in MATLAB/Simulink environment with actual load data, conventional Gas Turbine Generator (GTG), Photovoltaic (PV) generation system and Battery Energy Storage System (BESS). The proposed algorithm has been tested with the designed IMG model. To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. The simulation results demonstrate that the algorithm can minimize the limitations of the existing methods and it can use the PV generation system effectively. Peak shaving service can be found from this algorithm as a simple and forcible way. A comparative analysis has been conducted of the proposed algorithm with the conventional methods. The comparison results can easily reflect that the proposed algorithm can ensure the optimal use of PV generation system and can serve peak shaving service effectively. It can also ensure an economic and environment friendly system where the existing algorithms are limited to serve these. The proposed algorithm can mitigate the available power issues for hybrid PV-BESS connected system and it can also minimize the operating cost by dispatching the generation units optimally.

Suggested Citation

  • Rana, Md Masud & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Uddin, Moslem & Sarkar, Md Rasel, 2021. "A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system," Energy, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:energy:v:234:y:2021:i:c:s0360544221014055
    DOI: 10.1016/j.energy.2021.121157
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    1. Zhang, Yan & Fu, Lijun & Zhu, Wanlu & Bao, Xianqiang & Liu, Cang, 2018. "Robust model predictive control for optimal energy management of island microgrids with uncertainties," Energy, Elsevier, vol. 164(C), pages 1229-1241.
    2. Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír & Mohd Yunus, Mohamad Nur Salam & Syed Mohd Zaki, Syed Amarul Adli, 2018. "Peak-off-peak load shifting for optimal storage sizing in hybrid power systems using Power Pinch Analysis considering energy losses," Energy, Elsevier, vol. 156(C), pages 299-310.
    3. Jouvet, Pierre-André & Solier, Boris, 2013. "An overview of CO2 cost pass-through to electricity prices in Europe," Energy Policy, Elsevier, vol. 61(C), pages 1370-1376.
    4. Jannesar, Mohammad Rasol & Sedighi, Alireza & Savaghebi, Mehdi & Guerrero, Josep M., 2018. "Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration," Applied Energy, Elsevier, vol. 226(C), pages 957-966.
    5. Mahani, Khashayar & Farzan, Farbod & Jafari, Mohsen A., 2017. "Network-aware approach for energy storage planning and control in the network with high penetration of renewables," Applied Energy, Elsevier, vol. 195(C), pages 974-990.
    6. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2015. "Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving," Applied Energy, Elsevier, vol. 147(C), pages 246-257.
    7. repec:dau:papers:123456789/7761 is not listed on IDEAS
    8. Uddin, Moslem & Romlie, M.F. & Abdullah, M.F. & Tan, ChiaKwang & Shafiullah, GM & Bakar, A.H.A., 2020. "A novel peak shaving algorithm for islanded microgrid using battery energy storage system," Energy, Elsevier, vol. 196(C).
    9. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
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