The microgrid is an emerging trend in modern power systems. Microgrids consist of controllable power sources, storage, and loads. An elaborate control infrastructure is established to regulate and synchronize the interaction of these components. The control scheme is divided into a hierarchy of several layers, where each layer is composed of multi-agents performing their dedicated functions and arriving at a consensus of corrective values. Lateral and horizontal interaction of such multi-agents forms a comprehensive hierarchical control structure that regulates the microgrid operation to achieve a compendium of objectives, including power sharing, voltage, and frequency regulation. The success of a multi-agent-based control scheme is dependent on the health of the communication media that is used to relay measurements and control signals. Delays in the transmission of control signals result in an overall deterioration of the control performance and non-convergence. This paper proposes novel multi-agent moving average estimators to mitigate the effect of latent communication links and establishes a hierarchical control scheme incorporating these average estimators to accurately arrive at system values during communication delays. Mathematical models are established for the complete microgrid system to test the stability of the proposed method against conventional consensus-based methods. Case-wise simulation studies and lab-scale experimental verification further establish the efficacy and superiority of the proposed control scheme in comparison with other conventionally used control methods.

Power transformers are a fundamental component of the modern power distribution network. The fault-free operation of step-up and step-down transformers is of prime importance to the continuous supply of electrical energy to the consumers. To ensure such efficient operation, power distribution companies carry out routine maintenance of distribution transformers through preplanned schedules. The efficacy of such maintenance depends on a proper understanding of the transformer and its components and efficient prediction of faults in these components. There are several components whose condition can be studied to predict transformer failures and therefore the overall health of a transformer. These include transformer windings, insulations, transformer oil, core insulations, and ferromagnetic cores. This work develops a new, simplified fuzzy logic–based method to predict the health of a transformer by taking into account the state of several individual components. Case studies are used to demonstrate the efficacy of the developed method.

Energy harvesting from renewable energy sources is trending in the world due to inventions in modern technology. This paper proposes a grid-tied single-phase modified W-type 81-level inverter. Inverter design equations to calculate various parameters, such as the number of voltage levels and the number of DC power sources, along with the feedback controller equations, are developed to integrate the proposed topology with an electric power grid. The modeling of the control system for the proposed topology is carried out in the synchronously rotating reference frame for single-phase systems. The PWM generation part of the proposed inverter system makes use of the binary search nearest level algorithm to efficiently track the grid voltage signal. The proposed system integrates the inverter with the grid without the need for an output filter. The efficiency analysis shows that the proposed system delivers active and reactive power to the grid with an efficiency of around 90% and a THD of 1.04%. The voltage and current waveforms for the dynamic active and reactive power flow reveal that the proposed system exhibits a good transient and steady-state response. The overall system is simulated in MATLAB/Simulink and the results are verified using a hardware implementation of the prototype circuit.