Emerging trends and advances in techniques in power electronics, Unified Power Quality Conditioner (UPQC) has a superior performance compared to other methods. The paper proposes the application of a ANN based UPQC to enhance the power quality of a three-phase Low-voltage network connected to a hybrid distribution generation (DG) system. The proposed work emphases the detailed performance analysis of a distributed generation system that integrates a solar PV and wind energy system by utilizing Unified Power Quality Conditioner (UPQC) with an artificial neural network (ANN) controller with respect to proportional-integral (PI) controller. The core objective of the proposed ANN is to offer good steady and dynamic state performance compared to the PID controller. The system called UPQC-ANN-RE feeds energy generated by a photovoltaic array and a wind turbine into the electrical grid and loads attached to a system of 3-phase 4-wire electrical distribution. In addition to inserting active/real power in the utility grid, the system of UPQC-ANN-RE functions as a UPQC, improving power quality signs e.g., voltage and current harmonics and power factor. A detailed analysis of the active-real power flow by converters is carried out to allow a good understanding of the operation of the UPQC-ANN-RE. The simulation outcomes are presented to assess the dynamic and steady state performance of the system of UPQC-ANN-RE connected to an electrical distribution system and to compare the consequences with the PI controller.

The proliferation of distributed energy resources in distribution systems has given rise to a new concept known as Microgrids (MGs). The effective control of MGs is a crucial aspect that needs to be prioritized before undertaking any implementation procedure. This article provides a comprehensive overview of hierarchical control methods that ensure efficient and robust control for MGs. Specifically, it focuses on the secondary controller approaches (centralized, distributed, and decentralized control) and examines their primary strengths and weaknesses. The techniques are thoroughly discussed, deliberated, and compared to facilitate a better understanding. According to functionality, the hierarchical-based control scheme is allocated into three levels: primary, secondary, and tertiary. For secondary control level, the MG communication structures permit the usage of various control methods that provided the significance of the secondary controller for consistent and reliable MG performance and the deficiency of an inclusive recommendation for scholars. Also, it gives a review of the literature on present important matters related to MG secondary control approaches in relation to the challenges of communication systems. The problem of the secondary level control is deliberated with an emphasis on challenges like delays. Further, at the secondary layer, the distributed control techniques for reducing communication system utilization and then reducing communication system delays are conferred. Furthermore, the benefits and limitations of various control structures, such as centralized, decentralized, and distributed are also discusses in this study. Later a comparative analysis of entire control approaches, the best methods of control according to the author’s perspective are also discussed.

Islanded DC microgrids face challenges in voltage stability and communication overhead due to renewable energy variability. A novel enhanced distributed coordinated control framework, based on adaptive event-triggered mechanisms, is developed for the efficient management of multiple hybrid energy storage systems (HESSs) in islanded DC microgrids (MGs). We propose a hierarchical distributed control framework integrating ANN-based controllers and adaptive event-triggered mechanisms to dynamically regulate power flow and minimise communication. This system utilises a hierarchical coordinated control method (HCCM) with primary virtual resistance droop control integrated with state-of-charge (SoC) management and secondary control for voltage regulation and proportional current distribution through optimised communication networks. The integration of artificial neural network (ANN)-based controllers alongside traditional PI control leads to an improvement in system responsiveness. The control approach dynamically adjusts the trigger parameters to minimise communication overhead with tight voltage regulation. An extensive simulation using MATLAB/Simulink shows how the system can effectively manage variability in renewable energy sources and maintain stable voltage profiles with precise power distribution and minimal bus voltage fluctuations. Simulations confirm enhanced voltage regulation (±0.5% deviation), proportional current sharing (98% accuracy), and 60% communication reduction under load transients (outcomes).

MPC is an optimization control technique and it handles the constraints effectively in comparison to any other classical control technique. However, MPC is famous for slow dynamic SISO systems. In this research work, MPC performance is analyzed for a fast-dynamic MIMO system i-e rotors of quad copter to demonstrate the Roll, Pitch and Yaw movements in the presence of hard constraints. The simulations are done by first developing the system model of DC motor and then simulating it in Simulink. The results are presented for both SISO and MIMO systems at different set-points both in the absence and presence of hard constraints. The results have shown that MPC effectively regulates' the fast-dynamic MIMO system without violating the constraints.

The management of electricity distribution faces numerous challenges, including energy losses arising from technical and non-technical issues such as electricity theft. Energy losses due to theft have a significant global impact, including in South Africa (SA). SA rural areas are suffering from poor voltage, and technical and non-technical losses due to old power system systems. Hence, this research project is a proposal for the upgradation of an old and technically weak network of Nottingham Road, Kwa-Zulu Natal in South Africa. To reduce non-technical losses, this research examines the influence and potential solutions of using smart meters. The paper focuses on modeling real low voltage (LV) distribution systems and the energy meters that measure various parameters of the smart meters. This research also examines the effect of illegal links on the network. However, implementing the smart metering technology for lesser power consumers in developing countries such as South Africa can be challenging because of the greater initial costs. Therefore, this paper investigates the possibility of various technology choices and their return on investment in both urban and rural regions.