Zhang Haiyang, Wang Xiaowei, Zhang Jiasheng, Ge Yingkai, Wang Lihua
College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Sci Rep. 2024 Aug 26;14(1):19745. doi: 10.1038/s41598-024-70811-x.
In practical engineering applications, factors like dust adhesion and environmental changes can cause photovoltaic arrays to exhibit multiple peaks in output power. An optimization algorithm with global optimization capability is needed to track its maximum power. In this regard, this paper proposes an improved marine predator algorithm (IMPA) to extract the maximum power point of photovoltaic system under complex solar irradiation conditions. To overcome the issues in the traditional marine predator algorithm (MPA), the opposition-based learning(OBL) strategy is introduced in IMPA, and the sine cosine algorithm (SCA) is integrated into the iteration stage to enhance the search ability of the algorithm. Furthermore, the low-order converter in the traditional MPPT control system is replaced by the Zeta converter, which increases the operating voltage range. Ultimately, simulation results demonstrate that the MPPT based on IMPA has higher tracking efficiency and shorter response time.The experimental results also indicate the practical feasibility of this method, as well as its high level of stability and robustness.
在实际工程应用中，灰尘附着和环境变化等因素会导致光伏阵列输出功率出现多个峰值。需要一种具有全局优化能力的优化算法来跟踪其最大功率。对此，本文提出一种改进的海洋捕食者算法（IMPA），以在复杂太阳辐照条件下提取光伏系统的最大功率点。为克服传统海洋捕食者算法（MPA）中的问题，IMPA引入了基于反向学习（OBL）策略，并在迭代阶段集成了正弦余弦算法（SCA），以增强算法的搜索能力。此外，传统MPPT控制系统中的低阶变换器被Zeta变换器取代，从而扩大了工作电压范围。最终，仿真结果表明基于IMPA的MPPT具有更高的跟踪效率和更短的响应时间。实验结果也表明了该方法的实际可行性及其高度的稳定性和鲁棒性。
