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2000
Volume 18, Issue 8
  • ISSN: 2352-0965
  • E-ISSN: 2352-0973

Abstract

Introduction

When the superior power grid fails and loses power, due to the traditional single power supply radial grid structure of low-voltage substation areas, all loads in the low-voltage substation area will lose power, causing a poor electricity consumption experience for low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in distribution networks, considering island operation, is proposed.

Methods

This method integrates GFM-ESS and flexible interconnections, taking islanding operations into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed. The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly, minimizing the annual comprehensive cost and the annual power outage load are the objective functions. A bilevel programming model for GFM-ESS and flexible interconnection of low-voltage distribution networks, considering island operation, has been established. Moreover, a comprehensive evaluation method based on the analytic hierarchy process for proposed low-voltage distribution network structural schemes is introduced. An evaluation index system is established to assess the rationality of these proposed network structural planning schemes. Finally, the superiority of the proposed collaborative planning method is verified through a comparative analysis of three planning methods.

Results

The proposed collaborative planning method can effectively ensure the continuous power supply of low-voltage distribution networks under the fault scenario of the upper power network.

Conclusion

Moreover, the rationality of the results obtained from the proposed collaborative planning method is verified through a comprehensive evaluation method of grid structure schemes based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine which two areas are optimal for grid planning.

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2024-07-02
2025-11-15
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References

  1. WangY. ChenC. WangJ. BaldickR. Research on resilience of power systems under natural disasters—A review.IEEE Trans. Power Syst.20163121604161310.1109/TPWRS.2015.2429656
    [Google Scholar]
  2. CampbellR J Weather-related power outages and electric system resiliencyCongressional Research ServiceAvailable from: https://sgp.fas.org/crs/misc/R42696.pdf 2012
    [Google Scholar]
  3. SandhyaK. GhoseT. KumarD. ChatterjeeK. PN inference based autonomous sequential restoration of distribution system under natural disaster.IEEE Syst. J.20201445160517110.1109/JSYST.2020.2994585
    [Google Scholar]
  4. HuangG. WangJ. ChenC. QiJ. GuoC. Integration of preventive and emergency responses for power grid resilience enhancement.IEEE Trans. Power Syst.20173264451446310.1109/TPWRS.2017.2685640
    [Google Scholar]
  5. GeriniF. ZuoY. GuptaR. ZecchinoA. YuanZ. VagnoniE. CherkaouiR. PaoloneM. Optimal grid-forming control of battery energy storage systems providing multiple services: Modeling and experimental validation.Electr. Power Syst. Res.202221210856710.1016/j.epsr.2022.108567
    [Google Scholar]
  6. ChenJ. LiuM. MilanoF. Adaptive virtual synchronous generator considering converter and storage capacity limits.CSEE J. Power Energy Syst.202282580590
    [Google Scholar]
  7. UtkarshaP. NaiduN.K.S. SivaprasadB. SinghK.A. A flexible virtual inertia and damping control strategy for virtual synchronous generator for effective utilization of energy storage.IEEE Access20231112406812408010.1109/ACCESS.2023.3330237
    [Google Scholar]
  8. Hossain LipuM.S. AnsariS. MiahM.S. HasanK. MerajS.T. FaisalM. JamalT. AliS.H.M. HussainA. MuttaqiK.M. HannanM.A. A review of controllers and optimizations based scheduling operation for battery energy storage system towards decarbonization in microgrid: Challenges and future directions.J. Clean. Prod.202236013218810.1016/j.jclepro.2022.132188
    [Google Scholar]
  9. YanN. ZhangB. LiW. MaS. Hybrid energy storage capacity allocation method for active distribution network considering demand side response.IEEE Trans. Appl. Supercond.20192921410.1109/TASC.2018.2889860
    [Google Scholar]
  10. HuangW. ZhangX. LiK. ZhangN. StrbacG. KangC. Resilience oriented planning of urban multi-energy systems with generalized energy storage sources.IEEE Trans. Power Syst.20223742906291810.1109/TPWRS.2021.3123074
    [Google Scholar]
  11. LiZ. TangW. LianX. ChenX. ZhangW. QianT. A resilience-oriented two-stage recovery method for power distribution system considering transportation network.Int. J. Electr. Power Energy Syst.202213510749710.1016/j.ijepes.2021.107497
    [Google Scholar]
  12. LiC. YanJ. SunD. Multidimensional economic evaluation of energy storage participation in multiple scenarios in distribution networks.Glob. Energy Interconnect.2022505471479
    [Google Scholar]
  13. HasanK. OthmanM.M. MerajS.T. MekhilefS. AbidinA.F.B. Shunt active power filter based on savitzky-golay filter: Pragmatic modelling and performance validation.IEEE Trans. Power Electron.20233878838885010.1109/TPEL.2023.3258457
    [Google Scholar]
  14. MerajS.T. YahayaN.Z. HasanK. A filter less improved control scheme for active/reactive energy management in fuel cell integrated grid system with harmonic reduction ability.Appl. Ener.2022312118784
    [Google Scholar]
  15. MerajS.T. YuS.S. RahmanM.S. ArefinA.A. LipuM.S.H. TrinhH. A novel extendable multilevel inverter for efficient energy conversion with fewer power components: Configuration and experimental validation.Int J Circ Theor Appl20232023126
    [Google Scholar]
  16. ZhangG. WangY. PengB. LuY. QiuP. XuF. WangC. Multi-objective operation optimization of active distribution network based on three-terminal flexible multi-state switch.J. Renew. Sustain. Energy201911202550110.1063/1.5053614
    [Google Scholar]
  17. WangX. YangW. LiangD. Multi-objective robust optimization of hybrid AC/DC distribution networks considering flexible interconnection devices.IEEE Access2021916604816605710.1109/ACCESS.2021.3135609
    [Google Scholar]
  18. Baghban-NovinS. GolshannavazS. NazarpourD. HamidiA. Flexible feeder interconnections for increased penetration of renewables and improved volt/VAr control in distribution networks.IET Gener. Transm. Distrib.201913214861486910.1049/iet‑gtd.2018.6793
    [Google Scholar]
  19. ZhangL. TongB. WangZ. TangW. ShenC. Optimal configuration of hybrid AC/DC distribution network considering the temporal power flow complementarity on lines.IEEE Trans. Smart Grid20221353857386610.1109/TSG.2021.3102615
    [Google Scholar]
  20. WeidongZ.H.O.N.G. DongshengT.A.N.G. JiwenL.I.U. Design of intelligent flexible interconnected AC/DC hybrid LV distribution network.Mod. Architect. Electric20191011621
    [Google Scholar]
  21. ZhangB. LiJ. ZhangL. TangW. CaiY. Local control method and simulation analysis of hybrid AC/DC low-voltage distribution networks with high-proportion photovoltaics.Energy Rep.20239781982810.1016/j.egyr.2023.04.071
    [Google Scholar]
  22. LuZ.H.A.N.G. BiaoX.U. WeiT.A.N.G. Intra-day correction strategy of dispatching plan for AC/DC hybrid distribution network based on spatio-temporal power coordin ation.Autom. Electr. Power Syst.20214524106114
    [Google Scholar]
  23. LiJ. ZhangL. ZhangB. TangW. Coordinated planning for flexible interconnection and energy storage system in low-voltage distribution networks to improve the accommodation capacity of photovoltaic.Global Energy Interconnection20236670071310.1016/j.gloei.2023.11.004
    [Google Scholar]
  24. EhsanA. YangQ. State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review.Appl. Energy2019239C1509152310.1016/j.apenergy.2019.01.211
    [Google Scholar]
  25. FletcherJ.R.E. FernandoT. IuH.H-C. ReynoldsM. FaniS. Spatial Optimization for the Planning of Sparse Power Distribution Networks.IEEE Trans. Power Syst.20183366686669510.1109/TPWRS.2018.2846407
    [Google Scholar]
  26. BajajM. SinghA.K. AlowaidiM. SharmaN.K. SharmaS.K. MishraS. Power quality assessment of distorted distribution networks incorporating renewable distributed generation systems based on the analytic hierarchy process.IEEE Access2020814571314573710.1109/ACCESS.2020.3014288
    [Google Scholar]
  27. SinghA. DasA. BeraU.K. LeeG.M. Prediction of transportation costs using trapezoidal neutrosophic fuzzy analytic hierarchy process and artificial neural networks.IEEE Access2021910349710351210.1109/ACCESS.2021.3098657
    [Google Scholar]
  28. ZhaoJ. A method of power supply health state estimation based on grey clustering and fuzzy comprehensive evaluation.IEEE Access202311122261223610.1109/ACCESS.2023.3240692
    [Google Scholar]
  29. ZhouK. LiZ. GongW. ZhaoS. WenC. SongY. Influence of magnetic field generated by air core reactors in SVC-based substation and an optimal suppression method based on fuzzy comprehensive evaluation.IEEE Trans. Electromagn. Compat.20206251961197010.1109/TEMC.2019.2942435
    [Google Scholar]
  30. LiY. ZhouJ. TianJ. ZhengX. TangY.Y. Weighted error entropy-based information theoretic learning for robust subspace representation.IEEE Trans. Neural Netw. Learn. Syst.20223394228424210.1109/TNNLS.2021.3056188 33606640
    [Google Scholar]
  31. XinW. RenL. JingZ. Comprehensive evaluation of distribution network planning schemes based on improved AHP and CRITIC methods.Intellig. Comput. Applic.20201038590
    [Google Scholar]
  32. ZhongC. YiX. WuF. Planning and selection of the optimal consumption scheme for distribution networks based on simulation and evaluation of photovoltaic consumption capacity.Power Grid Technol.2023470311791188
    [Google Scholar]
  33. LiuY. YuZ. LiH. ZengR. The LCOE-indicator-based comprehensive economic comparison between AC and DC power distribution networks with high penetration of renewable energy.Energies20191224462110.3390/en12244621
    [Google Scholar]
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