4.6 Article

A novel adaptive command-filtered backstepping sliding mode control for PV grid-connected system with energy storage

期刊

SOLAR ENERGY
卷 178, 期 -, 页码 222-230

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2018.12.033

关键词

Photovoltaic system; Battery energy storage; Projection adaptive; Command-filtered backstepping; Sliding mode

资金

  1. Postgraduate Research & Practice Innovation Program of Jiangsu Provence [SJCX18_0645]
  2. National Natural Science Foundation of China [61503156]
  3. National Key Research and Development Program [2016YFD0400301]
  4. Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing Institute of Technology [XTCX201806]
  5. State Grid Zhejiang Province Technology Project [SGTYHT/17-JS-201]
  6. National first-class discipline program of Food Science and Technology [JUFSTR20180205]

向作者/读者索取更多资源

In order to solve the problems of power fluctuation in the photovoltaic (PV) grid-connected system and the nonlinearity in the model of inverters, a projection-based adaptive backstepping sliding mode controller with command-filter is designed in the system to adjust the DC-link voltage and the AC side current in the PV grid-connected system. Firstly, the mathematical model of the inverter in PV system is established, then backstepping control method is applied to control it, and the command filter is added to the controller to eliminate the differential expansion of the backstepping controller. Furthermore, the adaptive law based on Lyapunov stability theory is designed to estimate the uncertain parameters in the grid-connected inverter. A projection algorithm is introduced into the adaptive controller due to the demand of guaranteeing the bounded estimated value. Additionally, a sliding mode controller is increased to improve its robustness in this system. Considering the influence of irradiation and temperature changes, a battery energy storage system (BESS) is applied on the DC side to suppress the fluctuation of the output power of the PV system. Finally, the simulation results demonstrate that the presented strategy can control precisely the grid-connected inverter.

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