Training data1.

This paper presents the topology and machine learning-based intelligent control of high-power PV inverter for maximum power extraction and optimal energy utilization. Modular converters with reduced components economic and reliable for high power applications. The proposed integrated intelligent machine learning based control delivers power conversion control with maximum power extraction and supervisory control for optimal load demand control. The topology of the inverter, operating modes, power control and supervisory control aspects are presented. Simulation is carried out in MATLAB/SIMULINK to verify the feasibility of the proposed inverter and control algorithm. The experimental study is presented to validate the simulation results. The operational performance of the proposed topology is evaluated in terms of operational parameters such as regulation of output power, and load relay control and is compared to existing topologies. The economic performance is also evaluated in terms of power switch sizing and reliability in power delivery concerning switch or power sources failure.

本文针对用于最大功率提取与最优能源利用的大功率光伏逆变器（PV inverter），提出了其拓扑结构与基于机器学习的智能控制方案。采用更少元件的模块化变流器，在大功率应用场景中兼具经济性与可靠性。本文所提出的集成式机器学习智能控制方案，可实现兼具最大功率提取功能的功率转换控制，以及用于优化负载需求调控的监控控制。本文阐述了该逆变器的拓扑结构、工作模式、功率控制与监控控制等相关内容。通过在MATLAB/SIMULINK中开展仿真实验，验证了所提逆变器与控制算法的可行性。同时通过实验研究对仿真结果进行了验证。本文从输出功率调节、负载继电控制等运行参数维度，对所提拓扑的运行性能进行了评估，并与现有拓扑方案进行了对比。此外还从功率开关器件选型，以及当功率开关器件或电源发生故障时的功率传输可靠性两个维度，评估了其经济性能。