A two-stage MPPT controller for PV system based on the improved artificial bee colony and simultaneous heat transfer search algorithm

Linjuan Gong; Guolian Hou; Congzhi Huang

doi:10.1016/j.isatra.2022.06.005

A two-stage MPPT controller for PV system based on the improved artificial bee colony and simultaneous heat transfer search algorithm

ISA Trans. 2023 Jan:132:428-443. doi: 10.1016/j.isatra.2022.06.005. Epub 2022 Jun 14.

Authors

Linjuan Gong¹, Guolian Hou², Congzhi Huang³

Affiliations

¹ School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; Xi'an Thermal Power Research Institute Co., Ltd., Xi'an 710054, China. Electronic address: gljncepu@163.com.
² School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China.
³ School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; Key Laboratory of Power Station Energy Transfer Conversion and System, North China Electric Power University, Beijing 102206, China.

PMID: 35753811
DOI: 10.1016/j.isatra.2022.06.005

Abstract

The maximum power point tracking (MPPT) controller can monitor the voltage and current of photovoltaic (PV) array in real-time to acquire the maximum power output for battery charging in PV system. In order to improve the accuracy and rapidity of tracking process, a bionic two-stage MPPT control strategy composed of fast positioning stage and precise determination stage is proposed in this paper for optimizing the duty cycle d of DC-DC converter. Firstly, an improved artificial bee colony algorithm with simplified probability selection mechanism and novel employed bee phase is presented to balances exploration and exploitation for excellent rapidity in positioning rough search region around global peak. Then, the simultaneous heat transfer search (SHTS) algorithm is adopted for accurately acquiring the global maximum power point in obtained search region. On the one hand, the SHTS can reduce the subjectivity in artificial setting of the parameters to ensure the universality and accuracy of search process. On the other hand, the parallel search in SHTS can decrease the optimization time effectively. Finally, extensive simulation results illustrate that this two-stage MPPT strategy shows excellent performance in precisely identifying the GMPP of PV system with phenomenal rapidity among multiple peaks. Moreover, it outperforms all the counterparts in tracking speed and accuracy under partial shading conditions.

Keywords: Improved artificial bee colony; Maximum power point tracking; Partial shading conditions; Photovoltaic (PV) system; Simultaneous heat transfer search.