Hardware Implementation and Steady-State Analysis of ZVS-PWM Cuk Converter Based MPPT for Solar PV Module

ENERGYO ◽  
2018 ◽  
Author(s):  
M. Vaigundamoorthi Muthusamy ◽  
Ramesh R. Ramadoss
Author(s):  
M. Vaigundamoorthi Muthusamy ◽  
Ramesh R. Ramadoss

Abstract The main objective of this paper is to design and implement a ZVS-PWM Cuk converter to extract maximum power from solar PV module which uses Adaptive Perturb and Observer (APAO) algorithm. ZVS-PWM cuk converter is the interface between the solar PV panel and load. In order to improve electromagnetic compatibility and to reduce the switching losses across the switches, the soft switching (ZVS) has been implemented for Cuk converter, resulting in high converter conversion efficiency with less EMI at high-frequency operation. The harmonic content that each of the converter circuit produces is examined using FFT analysis. The implemented adaptive PAO algorithm improves the steady state stability and dynamic response when compared to the conventional PAO method. This algorithm is simulated using MATLAB/Simulink and implemented using ATMEGA16 micro controller. Hardware validation is carried out for the converter with the solar PV panel with rating of 37W, and operating at 25 kHz.


Author(s):  
Thomas Y.S. Lee

Models and analytical techniques are developed to evaluate the performance of two variations of single buffers (conventional and buffer relaxation system) multiple queues system. In the conventional system, each queue can have at most one customer at any time and newly arriving customers find the buffer full are lost. In the buffer relaxation system, the queue being served may have two customers, while each of the other queues may have at most one customer. Thomas Y.S. Lee developed a state-dependent non-linear model of uncertainty for analyzing a random polling system with server breakdown/repair, multi-phase service, correlated input processes, and single buffers. The state-dependent non-linear model of uncertainty introduced in this paper allows us to incorporate correlated arrival processes where the customer arrival rate depends on the location of the server and/or the server's mode of operation into the polling model. The author allows the possibility that the server is unreliable. Specifically, when the server visits a queue, Lee assumes that the system is subject to two types of failures: queue-dependent, and general. General failures are observed upon server arrival at a queue. But there are two possibilities that a queue-dependent breakdown (if occurs) can be observed; (i) is observed immediately when it occurs and (ii) is observed only at the end of the current service. In both cases, a repair process is initiated immediately after the queue-dependent breakdown is observed. The author's model allows the possibility of the server breakdowns/repair process to be non-stationary in the number of breakdowns/repairs to reflect that breakdowns/repairs or customer processing may be progressively easier or harder, or that they follow a more general learning curve. Thomas Y.S. Lee will show that his model encompasses a variety of examples. He was able to perform both transient and steady state analysis. The steady state analysis allows us to compute several performance measures including the average customer waiting time, loss probability, throughput and mean cycle time.


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