Single-source Switched-capacitor Boost Nine-level Inverter with Reduced Components

Increasing demands for improvement in power quality and power capacity have contributed to development of switched-capacitor multilevel inverters(SCMLIs).Recently developed SCMLIs enable single-stage voltage boosting,as well as inversion resulting in step-up ac output.Towards reduction in number of components,this paper introduces a boost type singlesource nine-level(9-level)SCMLI employing two capacitors and three diodes.Owing to the series-parallel connection process,capacitor voltages are inherently balanced and assist in quadruple voltage boosting from a single-source.Maximum voltage stress across semiconductor devices is limited to twice input voltage only.Using a minimum number of components,the proposed SCMLI can be extended to increase voltage levels without additional dc input.Each extension module adds two additional voltage steps in the output while maintaining maximum voltage stress the same as 9-level circuit.Followed by in-depth analysis of circuit operation and power losses,a thorough comparison of recently developed single-phase 9-level MLIs is carried out,which verifies design superiority.Extensive simulation and experimental results are presented to verify the prominent features of the 9-level SCMLI under dynamic operating conditions.

A Combined Reinforcement Learning and Sliding Mode Control Scheme for Grid Integration of a PV System

The paper presents development of a reinforcement learning(RL)and sliding mode control(SMC)algorithm for a 3-phase PV system integrated to a grid.The PV system is integrated to grid through a voltage source inverter(VSI),in which PVVSI combination supplies active power and compensates reactive power of the local non-linear load connected to the point of common coupling(PCC).For extraction of maximum power from the PV panel,we develop a RL based maximum power point tracking(MPPT)algorithm.The instantaneous power theory(IPT)is adopted for generation reference inverter current(RIC).An SMC algorithm has been developed for injecting current to the local non-linear load at a reference value.The RL-SMC scheme is implemented in both simulation using MATLAB/SIMULINK software and on a prototype PV experimental.The performance of the proposed RL-SMC scheme is compared with that of fuzzy logic-sliding mode control(FL-SMC)and incremental conductance-sliding mode control(IC-SMC)algorithms.From the obtained results,it is observed that the proposed RL-SMC scheme provides better maximum power extraction and active power control than the FL-SMC and IC-SMC schemes.

Forecasting Global Solar Insolation Using the Ensemble Kalman Filter Based Clearness Index Model

This paper describes a novel approach in developing a model for forecasting of global insolation on a horizontal plane.In the proposed forecasting model,constraints,such as latitude and whole precipitable water content in vertical column of that location,are used.These parameters can be easily measurable with a global positioning system(GPS).The earlier model was developed by using the above datasets generated from different locations in India.The model has been verified by calculating theoretical global insolation for different sites covering east,west,north,south and the central region with the measured values from the same locations.The model has also been validated on a region,from which data was not used during the development of the model.In the model,clearness index coefficients(KT)are updated using the ensemble Kalman filter(EnKF)algorithm.The forecasting efficacies using the KT model and EnKF algorithm have also been verified by comparing two popular algorithms,namely the recursive least square(RLS)and Kalman filter(KF)algorithms.The minimum mean absolute percentage error(MAPE),mean square error(MSE)and correlation coefficient(R)value obtained in global solar insolation estimations using EnKF in one of the locations are 2.4%,0.0285 and 0.9866 respectively.