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An economic model predictive control-based flexible power point tracking strategy for photovoltaic power generation

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  • Liu, Xiangjie
  • Zhu, Zheng
  • Kong, Xiaobing
  • Ma, Lele
  • Lee, Kwang Y.

Abstract

In a high solar-power-penetration power grid, photovoltaic (PV) power generation requires to run in a flexible power point tracking (FPPT) mode. However, traditional hierarchical control-based FPPT strategy ignores the dynamic economic performance of PV power generation. To address this issue, an advanced FPPT strategy based on economic model predictive control (EMPC) is proposed to achieve higher dynamic economic performance. This strategy integrates the PV voltage reference calculation, PV voltage control, and pulse width modulation into one optimal control framework, utilizing the economic indices of the PV power generation system (PVPGS) as the cost function to achieve its economic optimization and power tracking. Due to the strong nonlinearity in the PVPGS, the EMPC optimization problem is non-convex, leading to a local optimum. A mixed integer nonlinear programming algorithm is developed, which utilizes a finite number of converter switching states for obtaining the global optimum. Simulations demonstrate that the EMPC-based FPPT strategy enhances the dynamic economic performance compared to the hierarchical control-based FPPT strategy.

Suggested Citation

  • Liu, Xiangjie & Zhu, Zheng & Kong, Xiaobing & Ma, Lele & Lee, Kwang Y., 2023. "An economic model predictive control-based flexible power point tracking strategy for photovoltaic power generation," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223023873
    DOI: 10.1016/j.energy.2023.128993
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    References listed on IDEAS

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    1. Li, Peidu & Gao, Xiaoqing & Li, Zhenchao & Zhou, Xiyin, 2022. "Effect of the temperature difference between land and lake on photovoltaic power generation," Renewable Energy, Elsevier, vol. 185(C), pages 86-95.
    2. Zheng, Jianqin & Du, Jian & Wang, Bohong & Klemeš, Jiří Jaromír & Liao, Qi & Liang, Yongtu, 2023. "A hybrid framework for forecasting power generation of multiple renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
    3. Gao, Fang & Hu, Rongzhao & Yin, Linfei, 2023. "Variable boundary reinforcement learning for maximum power point tracking of photovoltaic grid-connected systems," Energy, Elsevier, vol. 264(C).
    4. Lin, Chia-Hung & Huang, Cong-Hui & Du, Yi-Chun & Chen, Jian-Liung, 2011. "Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method," Applied Energy, Elsevier, vol. 88(12), pages 4840-4847.
    5. Sheik Mohammed, S. & Devaraj, D. & Imthias Ahamed, T.P., 2016. "A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system," Energy, Elsevier, vol. 112(C), pages 1096-1106.
    6. Pal, Rudra Sankar & Mukherjee, V., 2020. "Metaheuristic based comparative MPPT methods for photovoltaic technology under partial shading condition," Energy, Elsevier, vol. 212(C).
    7. Issaadi, Salim & Issaadi, Wassila & Khireddine, Abdelkrim, 2019. "New intelligent control strategy by robust neural network algorithm for real time detection of an optimized maximum power tracking control in photovoltaic systems," Energy, Elsevier, vol. 187(C).
    8. Hou, Guolian & Ke, Yin & Huang, Congzhi, 2021. "A flexible constant power generation scheme for photovoltaic system by error-based active disturbance rejection control and perturb & observe," Energy, Elsevier, vol. 237(C).
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