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Power electronic converters find application in diverse fields due to their high power conversion efficiency. Converters are often characterized by time response specifications, robustness and stability. Conventionally, converters employ the classic PID controller. The state space average linear time invariant model of a boost converter is known to be a non-minimum phase system. This paper demonstrates that the boost converter with a PID controller using the Queen Bee assisted Genetic Algorithm (QBGA) optimization is not robust to plant parameter variations. A fractional order PID controller based on QBGA optimization proposed here is shown to have improved robustness. The controller proposed here is applicable across converters, viz., buck, boost and buck-boost, equally.

The recent growth of battery-powered applications has increased the need for high-efficiency step-up dc-dc converters. The step-up conversion is commonly used in several applications, such as electric vehicle (EV); plug-in hybrid electric vehicles (PHEV); photovoltaic (PV) systems; uninterruptible power supplies (UPS); and fuel cell systems. The input current is shared among inductors by paralleling the converters; resulting in high reliability and efficiency. In this paper; a detailed analysis for reducing power loss and improving efficiency is discussed. In continuous conduction mode; the converters are tested with a constant duty cycle of 50%. The multi phase interleaved boost converter (MPIBC) is controlled by interleaved switching techniques; which have the same switching frequency but phases are shifted. The efficiency of the six phase IBC model is 93.82% and 95.74% for an input voltage of 20 V and 200 V, respectively. The presented six phase MPIBC is validated by comparing it with the existing six phase IBC. The result shows that the presented converter is better than the existing converter. The prototype of the two phase and six phase IBC is fabricated to test the performance. It is found that the output power at the load end is highest for the 5 kHz switching frequency.

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The main aim of this paper is to introduce a framework for the design and modelling of a photovoltaic (PV)-wind hybrid system and its control strategies. The purpose of these control techniques is to regulate continuous changes in the operational requirements of the hybrid system;currently, in power system networks, the distribution of energy plays a major role in maintaining power reliability in distribution systems. In this study, the proposed hybrid system was incorporated with a combined PV and wind energy system. Maximum power point tracking (MPPT) methods have been proposed to achieve maximum efficiency from the designed system. In addition, this study focused on improving the stability of the hybrid system. To improve the power quality and transient stability of the proposed system, we introduce a novel control strategy called the distributed power flow controller (DPFC) implementation with an optimization technique called the lion optimization algorithm(LOA)technique. This LOA control technique was developed for the first time in the application of a DPFC controller in a grid-connected system. The control technique was developed using signals from the system parameters, that is, voltage and current. To tune these parameters, this study used fuzzy logic and lion optimization techniques. The proposed system with controllers was tested in MATLAB/Simulink and the results were compared.