Modular Multilevel Converter Controlled by Daisy-Chain Model Predictive Control for Medium Voltage Shunt Active Filter

Nowadays most of the loads exhibits a non-linear nature leading to sever distortion in the grid current. Mitigation of the adverse effects of such problems has been the focus of numerous researches throughout the past century. However, each genuine concept has its set-backs regarding energy consumption, reliability or protection. A Modular Multi-level converter (MMC) based Shunt Active Power Filter (SAPF) is introduced in this paper. The converter is to be connected to the medium voltage grid to compensate the reactive power required by the non-linear loads, thus eliminating the harmonics. The MMC out performs high-voltage/highpower converters in terms of quality output performance, high modularity, simple scalability, and low voltage and current rating demand for the power switches. A Model Predictive Control (MPC) algorithm is developed to control the converter. Least Mean Square Algorithm (LMS) based Adaptive Linear Neuron (ADALINE) network generates the reference current. The threephase load current is measured and analyzed to estimate the harmonics waveform, which is then fed to the MPC to generate the optimal switching sequence for the MMC. Simulation and results are presented to show the effectiveness of the proposed techniques.