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Optimal control of grid-connected overvoltage of distributed photovoltaic power generation based on cluster division

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China To address the overvoltage problem caused by the reverse flow of current when a high proportion of distributed photovoltaic (PV) is connected to the distribution network, this paper proposes a grid-connected voltage regulation control strategy based on the cluster division of the Distributed Model Predictive Control (DMPC) algorithm. Firstly, the overvoltage responsibility of each node is calculated using the Shapley value method. This is combined with k-means clustering to achieve effective cluster division, enabling dynamic adjustment of the active and reactive power of photovoltaic power generation units to stabilize regional voltage. Secondly, a group grid-connected voltage control strategy is introduced. This strategy controls the active and reactive power outputs by integrating real-time power output and voltage information from PV generating units in the region with the DMPC algorithm, ensuring overall voltage stability of the grid-connected system. Finally, actual overvoltage data from a 10 kV distribution line in the Dingxi power grid, Gansu Province, is used to verify that under the proposed control strategy, PV grid-connected overvoltage nodes are maintained within 1.06 p.u. The control effect is improved by a margin of 0.05 compared to traditional control methods. This demonstrates the effectiveness of the grouped grid-connected voltage regulation control strategy, achieving smoother voltage regulation performance in distributed PV grid-connected systems.
Rocznik
Strony
1047--1067
Opis fizyczny
Bibliogr. 26 poz., rys., tab., wykr., wz.
Twórcy
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China
autor
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China
autor
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China
autor
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China
Bibliografia
  • [1] http://www.xinhuanet.com/politics/19cpcnc/2017-10/27/c_1121867529.htm, accessed April 2024.
  • [2] Chai Yuanyuan, Distributed Voltage Optimization Control for Distribution Networks with High Penetration of Photovoltaics, PhD Thesis, Tianjin, Tianjin University (2021).
  • [3] Kaczorowska D., Rezmer J., Janik P., Sikorski T., Smart control of energy storage system in residential photovoltaic systems for economic and technical efficiency, Archives of Electrical Engineering, vol. 72, no. 1, pp. 81–102 (2023), DOI: 10.24425/aee.2023.143691.
  • [4] Zhang X., Ming L., Zixuan G., A review and outlook on control strategies for new energy grid connected inverters, Journal of Global Energy Interconnection, vol. 4, no. 5, pp. 506–515 (2021), DOI: 10.19705/j.cnki.issn2096-5125.2021.05.010.
  • [5] Jingjing T., Yu Q., Feng Z., Shenglin M., Huaxuan X. et al., Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified Gray Wolf Algorithm, Archives of Electrical Engineering, vol. 73, no. 1, pp. 121–141 (2024), DOI: 10.24425/aee.2024.148861.
  • [6] Ali Elrayyah, Sozer Yilmaz, Malik Elbuluk et al., Microgrid-Connected PV-Based Sources: A novel autonomous control method for maintaining maximum powe, IEEE Industry Applications Magazine, vol. 21, no. 2, pp. 19–29 (2015), DOI: 10.1109/MIAS.2014.2345822.
  • [7] Liu R., Kuihua W., Liang F. et al., Coordinated Optimization and Control of Voltage Partitioning in Active Distribution Networks with High Penetration of Distributed Photovoltaics, Acta Energiae Solaris Sinica, vol. 43, no. 2, pp. 189–197 (2022), DOI: 10.19912/j.0254-0096.tynxb.2020-0239.
  • [8] Fazio A.R.D., Risi C., Russo M., Santis M.D., Coordinated Optimization for Zone-Based Voltage Control in Distribution Grids, IEEE Transactions on Industry Applications, vol. 58, no. 1, pp. 173–18 (2022), DOI: 10.1109/TIA.2021.3129731.
  • [9] Adhi Kusmantoro, Irna Farikhah, Solar power and multi-battery for new configuration DC microgrid using centralized control, Archives of Electrical Engineering, vol. 72, no. 4, pp. 931–950 (2023), DOI: 10.24425/aee.2023.147419.
  • [10] Iweh Chu D. et al., Assessment of the optimum location and hosting capacity of distributed solar PV in the southern interconnected grid (SIG) of Cameroon, International Journal of Sustainable Energy, vol. 43, no. 1 (2024), DOI: 10.1080/14786451.2023.2168002.
  • [11] Moulum P.A., Mandeng J.J., Kom C.H. et al., Optimal PMU placement in the Southern Cameroon Interconnected Grid considering the effect of a group of ZIBs for complete obervability and dynamic stability, Research Square, PREPRINT (Version 1) 2024, DOI: 10.21203/rs.3.rs-3934743/v1.
  • [12] Ibrahem Mohamed A. Mahmoud et al., The impact of smart transformer on different radial distribution systems, Archives of Electrical Engineering, vol. 70, no. 2, pp. 271–283 (2021), DOI: 10.24425/aee.2021.136983.
  • [13] Zhang G., Yi Y., Xian P., Overvoltage Control of Photovoltaic Grid-Connected Based on Predictive Model, Smart Power, vol. 45, no. 9, pp. 20–25 (2017).
  • [14] Yu M., Zhu J., Yang L., Short-term load prediction model combining FEW and IHS algorithm, Archives of Electrical Engineering, vol. 68, no. 4, pp. 907–923 (2019), DOI: 10.24425/aee.2019.130691.
  • [15] Zhao Y., Zhi W., Zhonghao Q. et al., Active Distribution Network Distributed Optimization and Scheduling Considering Source-Load Spatio-Temporal Correlation, Automation of Electric Power Systems, vol. 43, no. 19, pp. 68–76 (2019).
  • [16] Guozheng H., Shujuan T., Zihan Z., Load regulation application of university campus based on solar power generation forecasting, Archives of Electrical Engineering, vol. 72, no. 2, pp. 429–441 (2023), DOI: 10.24425/aee.2023.145418.
  • [17] Chai Yuanyuan, Yixin Liu, Chengshan Wang et al., Voltage Coordination Control for Distributed Photovoltaic Generation Clusters with Incomplete Measurements, Proceedings of the CSEE, vol. 39, no. 8, pp. 2202–2212+3 (2019), DOI: 10.13334/j.0258-8013.pcsee.182485.
  • [18] Biserica M., Foggia G., Chanz E., Passelergue J.C., Network partition for coordinated control in active distribution networks, 2013 IEEE Grenoble Conference, Grenoble, France, pp. 1–5 (2013), DOI: 10.1109/PTC.2013.6652277.
  • [19] Li L., Junxi W., Yi H. et al., Day-Ahead Allocation Planning of Multi-Point PV-DG Based on K-means Clustering Particle Swarm Algorithm, High Voltage Engineering, vol. 43, no. 4, pp. 1263–1270 (2017), DOI: 10.13336/j.1003-6520.hve.20170328025.
  • [20] Song B., Seol H., Park Y., A patent portfolio-based approach for assessing potential R&D partners: An application of the Shapley value, Technological Forecasting and Social Change, vol. 103, no. 165, pp. 156–165 (2016), DOI: 10.1016/j.techfore.2015.10.010.
  • [21] Reddy P.V., Shevkoplyas E., Zaccour G., Time-consistent Shapley value for games played over event trees, Automatica (Journal of IFAC), vol. 49, no. 6, pp. 1521–1527 (2013).
  • [22] Tole Sut., Arsyad Cahya S., Giovanni P., Awang J., Kashif I., Maximum power point tracking techniques for low-cost solar photovoltaic applications – Part II: Mathematical Calculation and Measurement and Comparison, criteria on choices and suitable MPPT techniques, Archives of Electrical Engineering, vol. 72, no. 2, pp. 299–322 (2023), DOI: 10.24425/aee.2023.145410.
  • [23] Ying Chen, Chen Shen, A Jacobian-free Newton-GMRES(m) method with adaptive preconditioner and its application for power flow calculations, IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1096–1103 (2006), DOI: 10.1109/TPWRS.2006.876696.
  • [24] Santosh Kumar Gupta, Jayant Tripathi, Mrinal Ranjan, Ravi Kumar Gupta et al., Maximization of injected power and efficiency based optimal location of DPFC using iterative procedure, Archives of Electrical Engineering, vol. 71, no. 1, pp. 91–108 (2022), DOI: 10.24425/aee.2022.140199.
  • [25] Olfati-Saber R., Fax J.A., Murray R.M., Consensus and Cooperation in Networked Multi-Agent Systems, Proceedings of the IEEE, vol. 95, no. 1, pp. 215–233 (2007), DOI: 10.1109/JPROC.2006.887293.
  • [26] Reshikeshan S.S.M., Matthiesen S.L., Illindala M.S. et al., Autonomous Voltage Regulation by Distributed PV Inverters with Minimal Inter-node Interference, IEEE Transactions on Industry Applications, vol. 57, no. 3, pp. 2058–2066 (2021), DOI: 10.1109/TIA.2021.3064911.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e7ddf2c0-62f9-4f12-8bea-a8dc27e0995b
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