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Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers

Author

Listed:
  • Wang, Qin
  • Yao, Wei
  • Fang, Jiakun
  • Ai, Xiaomeng
  • Wen, Jinyu
  • Yang, Xiaobo
  • Xie, Hailian
  • Huang, Xing

Abstract

The distributed maximum power point tracking (DMPPT) technologies, based on a DC optimizer (DCO) for every single photovoltaic (PV) panel, are increasingly proposed to mitigate the waste of solar energy due to the mismatch problems of PV arrays. However, the stability problem of DMPPT based distributed PV grid-connected systems that involve a large amount of DCOs remains to be further studied. Therefore, modeling, deservedly, is the basis for stability analysis. Usually the model of the PV power plant consists of hundreds or even thousands of DCOs, which results in a heavy computation burden during the simulation. To solve the modeling problem, this paper proposes a matrix variables based modeling method for the distributed PV grid-connected system. The core idea of the modeling method is to convert the complex model that contains plenty of PV-DCO generation units to an average model consisting of only two typical submodules, by constructing the block matrix formed variables. In this way, the model has the advantages of good scalability and high simulation efficiency, and can be realized by the vector simulation feature of Matlab/Simulink. Besides, it is easy to obtain the linearization results directly by using the Linearization Toolbox in Simulink, which avoids the complexity of writing programs for linearization calculation when studying the stability of large-scale systems. Based on the average model and corresponding linearization results, the key impacts on the small signal stability of the system are determined via the eigenvalue analysis method and root locus method. It is shown that the total active power output by PV array, the controller parameters of the grid-connected inverter, and the strength of the AC system are critical factors affecting the small signal stability of distributed PV grid-connected system. Different simulation results verify the effectiveness of the proposed approach.

Suggested Citation

  • Wang, Qin & Yao, Wei & Fang, Jiakun & Ai, Xiaomeng & Wen, Jinyu & Yang, Xiaobo & Xie, Hailian & Huang, Xing, 2020. "Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers," Applied Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318197
    DOI: 10.1016/j.apenergy.2019.114132
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    1. Belhaouas, N. & Cheikh, M.-S. Ait & Agathoklis, P. & Oularbi, M.-R. & Amrouche, B. & Sedraoui, K. & Djilali, N., 2017. "PV array power output maximization under partial shading using new shifted PV array arrangements," Applied Energy, Elsevier, vol. 187(C), pages 326-337.
    2. Vavilapalli, Sridhar & Umashankar, S. & Sanjeevikumar, P. & Ramachandaramurthy, Vigna K. & Mihet-Popa, Lucian & Fedák, Viliam, 2018. "Three-stage control architecture for cascaded H-Bridge inverters in large-scale PV systems – Real time simulation validation," Applied Energy, Elsevier, vol. 229(C), pages 1111-1127.
    3. Zheng, Lingwei & Liu, Zhaokun & Shen, Junnan & Wu, Chenxi, 2018. "Very short-term maximum Lyapunov exponent forecasting tool for distributed photovoltaic output," Applied Energy, Elsevier, vol. 229(C), pages 1128-1139.
    4. Viana, Matheus Sabino & Manassero, Giovanni & Udaeta, Miguel E.M., 2018. "Analysis of demand response and photovoltaic distributed generation as resources for power utility planning," Applied Energy, Elsevier, vol. 217(C), pages 456-466.
    5. Solano, J.C. & Olivieri, L. & Caamaño-Martín, E., 2017. "Assessing the potential of PV hybrid systems to cover HVAC loads in a grid-connected residential building through intelligent control," Applied Energy, Elsevier, vol. 206(C), pages 249-266.
    6. Trujillo, C.L. & Velasco, D. & Figueres, E. & Garcerá, G. & Ortega, R., 2011. "Modeling and control of a push-pull converter for photovoltaic microinverters operating in island mode," Applied Energy, Elsevier, vol. 88(8), pages 2824-2834, August.
    7. Chen, Jian & Yao, Wei & Zhang, Chuan-Ke & Ren, Yaxing & Jiang, Lin, 2019. "Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control," Renewable Energy, Elsevier, vol. 134(C), pages 478-495.
    8. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    9. Wang, Yunyun & Pei, Gang & Zhang, Longcan, 2014. "Effects of frame shadow on the PV character of a photovoltaic/thermal system," Applied Energy, Elsevier, vol. 130(C), pages 326-332.
    10. Cook, Tyson & Shaver, Lee & Arbaje, Paul, 2018. "Modeling constraints to distributed generation solar photovoltaic capacity installation in the US Midwest," Applied Energy, Elsevier, vol. 210(C), pages 1037-1050.
    11. Branker, K. & Pathak, M.J.M. & Pearce, J.M., 2011. "A review of solar photovoltaic levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4470-4482.
    12. Saravanan, S. & Ramesh Babu, N., 2017. "Analysis and implementation of high step-up DC-DC converter for PV based grid application," Applied Energy, Elsevier, vol. 190(C), pages 64-72.
    13. Mahdavyfakhr, Mohammad & Rashidirad, Nasim & Hamzeh, Mohsen & Sheshyekani, Keyhan & Afjei, Ebrahim, 2017. "Stability improvement of DC grids involving a large number of parallel solar power optimizers: An active damping approach," Applied Energy, Elsevier, vol. 203(C), pages 364-372.
    14. Liao, Shiwu & Yao, Wei & Han, Xingning & Wen, Jinyu & Cheng, Shijie, 2017. "Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data," Applied Energy, Elsevier, vol. 203(C), pages 816-828.
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