Predictive control of standalone DC microgrid with energy storage under load and environmental uncertainty

Distributed generators (DGs) with integration of renewable resources (RRs) such as photovoltaic (PV) and wind turbine have been widely considered to reduce the dependency on conventional power generation systems along with enhancement of the quality and sustainability of the power system. Recently, DC microgrid has gained popularity in many real-world applications such as rural electrification due to its simplicity and low power losses. However, the power variability of renewable resources and continuous change in load demand imposes risks of power mismatch in standalone DC systems that increase the chances of stability and reliability issues. Therefore, complementary generation and/or storage systems are coupled with standalone DC microgrid to mitigate the power fluctuations and maintain a power balance in the system. This dissertation presents a power management strategy (PMS) based on model predictive control (MPC) for a standalone DC microgrid. A control scheme for a standalone DC microgrid system with RRs, storage, and load is desired to have the capability of effective power management that maximizes the extraction of energy from renewable generators, minimizes the transients in the system during disturbances, and protects the storage from over/under charging conditions. As a part of the proposed MPC, an optimization problem is formulated to meet the voltage performance in the system with respect to operating conditions and constraints. The proposed PMS uses the ARIMA prediction method to forecast the load and environmental parameters. The predicted parameters are utilized to estimate the future performance of the system by solving the dynamic model of the system, and a cost function is optimized to generate suitable control sequences. This research also presents detailed mathematical models of the considered systems. This dissertation presents an extensive simulation-based analysis of the proposed approach. With the proposed control, maximum utilization of the renewable generators has been achieved, and the DC bus voltage is regulated at nominal value with minimum transients under various load/environmental disturbances. Moreover, the research investigates the proposed MPC based on ARIMA prediction by comparing the performance of different types of prediction methods. The dissertation also measures the effectiveness of the proposed MPC by comparing its performance with a conventional PI controller

Image-Based Partial Discharge Identification in High Voltage Cables Using Hybrid Deep Network

Deep learning and digital image technologies have combined to create a potentially effective tool for identifying partial discharge (PD) patterns precisely. However, it is necessary to investigate which algorithm guarantees the best performance. The more common tools are restricted by a lack of training data and an advanced model in itself. Therefore, the main goal of this paper is to develop an efficient hybrid network comprising two deep networks, long short-term memory (LSTM), and convolutional neural network (CNN), for identifying the form of PD. A total of $8186\times 25$ (non-PD $\times$ PD) images were applied to assess the proposed methods. The size of the PD type was increased to 3675 images using data augmentation techniques. The results indicated that the integration of CNN and LSTM networks can provide a more robust implementation for PD detection. The integrated CNN-LSTM deep network based on data augmentation outperformed features derived from a single deep network. The recall, F-measure, and classification precision have 99.9% as a validation accuracy with a 99.8% intersection over union and a loss of 0.004

Single-Phase Fault Tolerant Multilevel Inverter Topologies—Comprehensive Review and Novel Comparative Factors

Multilevel inverters (MLIs) are used in a variety of industrial applications in high- and medium-voltage systems. The modularity, high-power output from medium voltages, and low harmonic content are some of the advantages of MLIs. The reliability of MLIs is quite important. The reliability is affected by different kinds of faults occurring in the MLIs. In MLI circuits, switching devices are the most vulnerable components and have a major involvement in all types of faults. As an outcome, it is necessary to take proper corrective action in the event of a fault. This work provides a comprehensive review of different fault tolerant (FT) solutions for MLIs in the event of switch fault. Moreover, various single-phase FT MLI topologies are reviewed, along with their constructional features, merits, and demerits. This work also proposes a comparison approach that integrates novel factors to account for fault tolerance quantitatively. A comparison investigation verifies the effectiveness of the proposed method. The FT operation of an existing five-level FT MLI topology is discussed, simulated, and experimentally verified

Single-Phase Fault Tolerant Multilevel Inverter Topologies—Comprehensive Review and Novel Comparative Factors

Multilevel inverters (MLIs) are used in a variety of industrial applications in high- and medium-voltage systems. The modularity, high-power output from medium voltages, and low harmonic content are some of the advantages of MLIs. The reliability of MLIs is quite important. The reliability is affected by different kinds of faults occurring in the MLIs. In MLI circuits, switching devices are the most vulnerable components and have a major involvement in all types of faults. As an outcome, it is necessary to take proper corrective action in the event of a fault. This work provides a comprehensive review of different fault tolerant (FT) solutions for MLIs in the event of switch fault. Moreover, various single-phase FT MLI topologies are reviewed, along with their constructional features, merits, and demerits. This work also proposes a comparison approach that integrates novel factors to account for fault tolerance quantitatively. A comparison investigation verifies the effectiveness of the proposed method. The FT operation of an existing five-level FT MLI topology is discussed, simulated, and experimentally verified