Mumtaz Sidra, Khan Laiq, Ahmed Saghir, Badar Rabiah
Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad, KPK, Pakistan.
PLoS One. 2017 Sep 6;12(9):e0183750. doi: 10.1371/journal.pone.0183750. eCollection 2017.
This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.
本文聚焦于并网混合动力系统中可再生能源的间接自适应跟踪控制。由于气象条件不可预测，可再生能源系统效率低且具有间歇性。家庭负载和传统充电站的行为具有不确定性。为了高效运行可再生能源以获取最大功率，应在线捕捉瞬时非线性动态特性。针对变速风力涡轮机 - 永磁同步发电机（VSWT - PMSG），提出了一种切比雪夫小波嵌入的神经模糊间接自适应最大功率点跟踪（MPPT）控制范式。开发了一种用于光伏（PV）系统的埃尔米特小波合并神经模糊间接自适应MPPT控制策略以提取最大功率，以及用于固体氧化物燃料电池（SOFC）的间接自适应跟踪控制方案。在Matlab/Simulink中开发了一个用于并网混合动力系统的综合仿真试验台。通过在并网混合动力系统试验台中的仿真结果，与传统和智能控制技术进行比较，评估了所提出的间接自适应控制范式的鲁棒性。仿真结果验证了所提出控制范式的有效性。
