An efficient maximum power point tracking (MPPT) method plays an important role to improve the efficiency of a photovoltaic (PV) generation system. This study provides an extensive review of the current status of MPPT methods for PV systems which are classified into eight categories. The categorisation is based on the tracking characteristics of the discussed methods. The novelty of this study is that it focuses on the key characteristics and eleven selection parameters of the methods to make a comprehensive analysis, which is not considered together in any review works so far. Again, the pros and cons, classification and immense comparison among them described in this study can be used as a reference to address the gaps for further research in this field. A comparative review in tabular form is also presented at the end of the discussion of each category to evaluate the performance of these methods, which will help in selecting the appropriate technique for any specific application.

Distributed generation (DG) is one of the key components of the emerging microgrid concept that enables renewable energy integration in a distribution network. In DG unit operation, inverters play a vital role in interfacing energy sources with the grid utility. An effective interfacing can successfully be accomplished by operating inverters with effective control techniques. This paper reviews and categorises different control methods (voltage and primary) for improving microgrid power quality, stability and power sharing approaches. In addition, the specific characteristics of microgrids are summarised to distinguish from distribution network control. Moreover, various control approaches including inner-loop controls and primary controls are compared according to their relative advantages and disadvantages. Finally, future research trends for microgrid control are discussed pointing out the research opportunities. This review paper will be a good basis for researchers working in microgrids and for industry to implement the ongoing research improvement in real systems.

This paper introduces an energy management algorithm for a hybrid solar and biogas-based electric vehicle charging station (EVCS) that considers techno-economic and environmental factors. The proposed algorithm is designed for a 20-kW EVCS and uses a fuzzy inference system in MATLAB SIMULINK to manage power generation, EV power demand, charging periods, and existing charging rates to optimize real-time charging costs and renewable energy utilization. The results show that the proposed algorithm reduces energy costs by 74.67% compared to existing flat rate tariffs and offers lower charging costs for weekdays and weekends. The integration of hybrid renewables also results in a significant reduction in greenhouse gas emissions, with payback periods for charging station owners being relatively short, making the project profitable.

In this paper we propose a special type of colocated feedback controller for smart structures. The controller is a parallel combination of high-Q resonant circuits. Each of the resonant circuits is tuned to a pole (or the resonant frequency) of the smart structure. It is proven that the parallel combination of resonant controllers is stable with an infinite gain margin. Only one set of actuator-sensor can damp multiple resonant modes with the resonant controllers. Experimental results are presented to show the robustness of the proposed controller in damping multimode resonances.