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Simultaneous load leveling and voltage profile improvement in distribution networks by optimal battery storage planning

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  • Mehrjerdi, Hasan

Abstract

Battery Energy Storage Systems can provide various applications in the distribution networks including load leveling, expansion deferral, voltage profile improvement, frequency regulation, fast reserve, and renewable energy time shift. Despite offering various applications, the BESSs are characterized with high investment costs. An optimal investment plan can justify the cots by exploiting multiple simultaneous applications. To this end, this paper proposes a novel planning model for the BESSs in distribution network wherein both load leveling and voltage profile improvement applications are extracted. The load leveling application refers to storing cheap energy at off-peak periods to deliver at peak period with high energy costs. In this way, the load profile tends to be flat and resulting lower energy cost. The voltage profile improvement is achieved by the optimal reactive power control of the inverter located between the BESS and the grid. The idea is that the inverter can allocate rated power capacity to the reactive power exchange at periods with negligible or zero active power conversion. Simulation results demonstrate that the voltage profile can improve in some degrees without increasing planning and/or operation costs. Higher degrees of improvement can be achieved at the expanse of cost increase. Also, the simulations show that the conducted load leveling results to loss reduction, peak shaving, and network expansion deferral subsequently.

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  • Mehrjerdi, Hasan, 2019. "Simultaneous load leveling and voltage profile improvement in distribution networks by optimal battery storage planning," Energy, Elsevier, vol. 181(C), pages 916-926.
    • Handle: RePEc:eee:energy:v:181:y:2019:i:c:p:916-926
    DOI: 10.1016/j.energy.2019.06.021
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    9. Yang, Jun & Su, Changqi, 2021. "Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty," Energy, Elsevier, vol. 223(C).
    10. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Energy and uncertainty management through domestic demand response in the residential building," Energy, Elsevier, vol. 192(C).
    11. shafiei, Mohammad & Ghasemi-Marzbali, Ali, 2023. "Electric vehicle fast charging station design by considering probabilistic model of renewable energy source and demand response," Energy, Elsevier, vol. 267(C).
    12. Masood, Nahid-Al- & Mahmud, Sajjad Uddin & Ansary, Md Nazmuddoha & Deeba, Shohana Rahman, 2022. "Improvement of system strength under high wind penetration: A techno-economic assessment using synchronous condenser and SVC," Energy, Elsevier, vol. 246(C).
    13. Mandhir Kumar Verma & Vivekananda Mukherjee & Vinod Kumar Yadav & Santosh Ghosh, 2020. "Constraints for effective distribution network expansion planning: an ample review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 531-546, June.
    14. He, Shuaijia & Gao, Hongjun & Liu, Junyong & Zhang, Xi & Chen, Zhe, 2022. "Distribution system planning considering peak shaving of energy station," Applied Energy, Elsevier, vol. 312(C).
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