In this paper, an efficient adaptive energy management strategy (EMS) is presented for a hybrid energy storage system (HESS) application to compensate power fluctuation. The HESS consists of a battery and super-capacitor, which are integrated into the DC grid using a modified triple active bridge converter (m-TAB). The conventional EMS uses a low pass filter (LPF) to distribute high and low-frequency components of power. However, the time constant of the LPF is fixed throughout the process, which discharges the battery at the same rate even near the low state of charge (SOC) region. This increases the degradation rate of the battery. The proposed EMS employs an adaptive time constant LPF-based power allocation method to distribute the total power between the energy storage devices. The adaptive feature of the EMS changes the power distribution ratio dynamically to increase the utilization of the super-capacitor and battery operation time, thereby enhancing the life cycle. The proposed EMS is simulated in MATLAB/SIMULINK platform with the m-TAB converter, and the results are compared with the conventional EMS to prove its superiority. The system is also tested on an experimental prototype of 500 W for different test cases, and the outcomes are presented to support the proposed EMS.

Parallel operation of power converters in islanded DC microgrids exhibits significant trade-off in voltage regulation and current sharing with conventional droop control. The converters exhibit inaccuracies in proportionate sharing of current when subject to heavy and transient loading while sharing a common bus. Moreover, the inaccuracies further persist due to unmodeled dynamics, parametric uncertainties, disturbance in the system and communication reliability. Therefore, the resilient parallel operation of power converters in DC microgrids requires a robust and fast control strategy that can mitigate the effect of disturbances and maintain regulated bus voltage with proportional current sharing amongst the power converters. Consequently, this work proposes a novel ANN driven droop control for a DC microgrid to enhance the transient response and mitigate disturbance in finite time. Two controllers based on adaptive droop strategy are proposed; the primary controller is a generalized Hebb's learning law-based PI integrated controller that can adjust the gains in real time for finite-time disturbance compensation in the networks and the secondary control regulates the bus voltage using fractional order sliding mode control. The effectiveness of the proposed method is evaluated by simulation and experiment and compared with the conventional and distributed droop control methods, proving its robust and adaptive performance for resilient DC microgrid applications.

This article proposes an adaptive power Management system for energy storage integration to the DC grid using a modified dual active bridge bi-directional DC-DC converter. The converter can achieve high voltage gain and zero voltage switching for a wide range of loading conditions with distributed voltage stress. An adaptive power Management system (APMS) is designed with a voltage droop control based model reference adaptive control (MRAC). A reduced order harmonic model of the converter is used for the APMS design. The proposed APMS does not require detailed knowledge of the system parameters and is also robust to uncertainty and multiple disturbances. The proposed converter and its control technique are verified in MATLAB/SIMULINK platform. An experimental laboratory prototype is also developed for 500W rating, and the results are presented to validate the system’s efficacy by comparing with conventional PI and sliding mode controllers.

The energy storage integration to grid using a dual active bridge DC – DC converter requires a promising controller for its efficient operation. In this paper a model reference adaptive controller (MRAC) for power flow control of a grid connected bi-directional neutral point clamped (NPC) structure based dual active bridge converter is introduced. The converter modelling is based on harmonic analysis. The controller is simple to implement and matches the power demand by the grid from the energy storage. The system performance is verified in MATLAB/Simulink platform for 5kW DAB converter and the results validates its satisfactory dynamic response for different disturbances in the system.

A Maximum Power Point Tracking (MPPT) Controller using a buck converter has been designed and developed for a standalone Photovoltaic(PV) array. Perturb and Observe (P&O) algorithm has been implemented on a microcontroller to achieve the maximum power output from PV array. The whole developed hardware system has been tested with and without MPPT in a conventional PV array. The results show that the introduction of MPPT controller increases the efficiency of the conventional PV array.

This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural people of a third world country like India. The designed system consists of two major blocks; the first one is required to be carried to the patient home, named 'Portable Telecardiology Kit'. The second one, named 'Automated Cardiac Signal Processor', a PC based system, to be permanently placed at the nearest rural health care center. The 'Portable Telecardiology Kit' contains a portable ECG machine, a dedicated microcontroller-based full duplex communication system, both interfaced, in a single enclosure. This kit will convert the ECG signal along with a tag page (containing different information regarding patient's health and history of illness) to a digitized serial electromagnetic wave. The signal may be transmitted over a distance of about 7-10 km through a cordless phone under full duplex mode. The PC-based system, after receiving the transmitted signal from patient site, extract the ECG signal after proper filtering, and then pass the signal through an in-built knowledge-base. Finally, a rule-based rough set decision system is generated for the development of an inference engine for disease identification from these time-plane features. The system will generate a report indicating the preliminary level abnormalities, and the precautions that can be adopted at an early stage. The entire report is then sent to the Portable kit at the patient bed-site.