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Load survey has become a routine project for shipbuilding and shipping companies to investigate electrical load characteristics to enhance the power system planning and operation of marine vessels. In this brief perspective, we will outline a few steps to feeder losses analysis based on the result conducted by the load survey. The power flow and feeder loss analysis are extracted and used to determine the critical parameters that can significantly affect the system feeder losses used in the electrical load analysis in new ships. Exploring this new research direction will provide a more thorough understanding of feeder losses in marine vessel power systems. In this paper, a case study of container ship power loss analysis using the Newton–Raphson method is presented. The analysis results can provide shipbuilding corporations and ship owners with useful information for planning, designing, operating, and controlling shipboard power systems. As an energy-saving measure for ship microgrids, the frequency converters are widely used by shipyards for seawater and freshwater cooling systems and heating, ventilation, and air conditioning (HVAC) systems, so that these systems can adjust the speed of the motor according to the actual demand of the load, so as to avoid full-load operation during the motor operation. With the proposed method, other measures, such as battery energy storage systems and energy-saving lighting equipment based on LEDs, are also utilized for shipboard power demand management. [ABSTRACT FROM AUTHOR]

This article presents the calculation procedure of short circuits adopting the characteristic currents method (CCM). In a previous paper by the author G. Parise, the CCM has been upgraded with the introduction of “characteristic” countercurrents and the generalization of the Kirchhoff laws. For illustrating the calculation procedure, the selected case study deals with a low voltage cold ironing system where multiple ships are allowed to operate simultaneously on one shore power transformer and, so, a comparison has been developed between the IEC approach of the short-circuit calculation and the CCM. [ABSTRACT FROM AUTHOR]

This article presents a robust passivity-based control (PBC) strategy to mitigate the instability effect of the dc–dc boost power converter supplying a constant power load and a constant voltage load in dc microgrid systems. The control robustness of the PBC against both line and load variation is significantly improved by adding the nonlinear disturbance observer (NDO). Using the disturbance estimation technique, this observer works in parallel with the PBC strategy to compensate the disturbances of the system through a feed-forward compensation channel. Based on the dissipation property, the PBC strategy ensures the system stability, whereas the NDO guarantees global trajectory tracking to the reference voltage during disturbances. This control strategy not only ensures large-signal stability of the system, but also provides a fastest recovery performance during disturbances of the system as compared with other PBC strategies. The hardware-in-loop and real-hardware experimental results are provided to verify the control robustness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In recent years, due to the large spread of power electronics converters onboard shipboard power systems (SPSs), harmonic contamination became an inherent problem. Moreover, as the SPSs are mostly operating in an islanded mode with a limited rating of the generators that feed heavy variable loads, voltage stability issues became a challenge as well. To address these issues, implementing PWM-based FACTS devices using IGBTs such as the active power filters may not be very practical for high-power SPSs due to their limited rated powers, high implementation cost, and high losses. The passive power filters (PPFs) and fixed capacitor–thyristor controlled reactors (FC-TCR) can be effective alternatives due to their capability to operate in high-power applications, smaller losses and, lower cost. The aim of this article is to provide more in-depth analytical investigations to evaluate and compare the behavior of the PPFs and the FC-TCR compensator in reducing the harmonics and enhancing the voltage stability concurrently of high-power SPSs. In addition, details of the voltage stability concept are addressed to visualize the potential risk of the voltage collapse. Besides, the modeling of the FC-TCR and design of the closed-loop control algorithm to ensure voltage stability is conducted. Via intensive simulation studies of a practical ship, which are carried out in MATLAB/Simulink environment, it has been demonstrated that the FC-TCR based on the proposed design can enhance the power quality and voltage stability of SPSs better than traditional PPFs filters. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative adaptive nonsingular Second-Order Terminal Sliding Mode (SOTSM) control strategy specifically designed to stabilise disturbed nonlinear Cyber-Physical Systems (CPSs) within a finite timeframe. Unlike the conventional methods, our approach incorporates a novel nonlinear sliding surface that eliminates the need for a reaching step, significantly enhancing the system's robustness. Novel real-time adaptive control laws are developed to cope with external perturbations, time-varying delays, and cyber-attack on actuators without requiring the identification of their upper bounds. The proposed method ensures robust performance for time-varying delayed and disturbed nonlinear CPSs, even in the face of strong cyber-attacks targeting the actuators. Moreover, the proposed method has distinct advantages: it delivers rapid response times, enhanced flexibility, exceptional accuracy, smooth and robust control devoid of transient fluctuations or chattering, and ensures finite-time convergence. Simulation results comprehensively demonstrate the superior efficiency and success of our proposed technique compared to traditional methods such as integral Sliding Mode Control (SMC) and State-Feedback Control (SFC) schemes. [ABSTRACT FROM AUTHOR]

In recent years, renewable energy (RE) has shown promise as a sustainable solution to the rising energy demand worldwide. Photovoltaic (PV) technology has emerged as a highly viable RE alternative. The majority of PV schemes use specific PV models with specified parameters. This study proposes a PV model with generic specifications, a PV array, a DC/DC converter, a DC/AC inverter, maximum power point tracking (MPPT), and grid synchronization using a feedback control system under the MATLAB/Simulink environment. Various MPPT techniques have been adapted to track the PV's maximum power point (MPP); however, there are various uncertainties. To address these challenges, this paper presented a perturb and observe (P&O) strategy to track the MPP of PV systems reliably. The MPP of a PV system varies according to meteorological order, such as solar radiation and cell temperature. The MPPT primarily gathers the maximum current and voltage of the PV array and provides them to the load using a boost converter. The MPPT performance and PV array attributes are analyzed during abrupt weather changes. Finally, a feedback controller is configured to perform synchronization of the inverter with the grid. The validity and reliability of the PV module using P&O methods provide a higher efficacy of MPPT under MATLAB/simulation. Finally, the presented results endorse the strength of the proposed technique. [ABSTRACT FROM AUTHOR]

The transmission lines of an electricity system are susceptible to a wide range of unusual fault conditions. The transmission line, the longest part of the electricity grid, sometimes passes through wooded areas. Storms, cyclones, and poor vegetation management (including tree cutting) increase the risk of cross-country faults (CCFs) and high-impedance fault (HIF) syndrome in these regions. Recognizing and classifying CCFs associated with HIF syndrome is the most challenging part of the project. This study extracted signal characteristics associated with CCF and HIF syndrome using the Tunable Q Wavelet Transform (TQWT). An adaptive tunable Q-factor wavelet transform (TQWT) based feature-extraction approach for CCHIF fault signals with high impact, short response period, and broad resonance frequency bandwidth was presented. In the first part, the time–frequency distribution of the vibration signal is used to determine the distinctive frequency range. Adaptive optimal matching of the impact characteristic components in the vibration signal was achieved by optimizing the number of decomposition layers, quality factor, and redundancy of TQWT based on the characteristic frequency band. In the last, the TQWT inverse transform was utilized to recreate the best sub-band to boost its weak impact characteristics. The effectiveness of the approach is confirmed by simulation and experimental findings in signal processing. The best decomposition level for signature features that can be extracted has been decided by Minimum Description length (MDL). The IEEE 39-bus system is used to test the suggested approach with reactor switching and the Ferranti effect. [ABSTRACT FROM AUTHOR]

Grid faults are found to be one of the major issues in renewable energy systems, particularly in wind energy conversion systems (WECS) connected to the grid via back-to-back (BTB) converters. Under such faulty grid conditions, the system requires an effective regulation of the active (P) and reactive (Q) power to accomplish low voltage ride through (LVRT) operation in accordance with the grid codes. In this paper, an improved finite-control-set model predictive control (FCS-MPC) scheme is proposed for a PMSG based WECS to achieve LVRT ability under symmetrical and asymmetrical grid faults, including mitigation of DC-link voltage fluctuation. With proposed predictive control, optimized switching states for cost function minimization with weighing factor (WF) selection guidelines are established for robust BTB converter control and reduced cross-coupling amid P and Q during transient conditions. Besides, grid voltage support is provided by grid side inverter control to inject reactive power during voltage dips. The effectiveness of the FCS-MPC method is compared with the conventional proportional-integral (PI) controller in case of symmetrical and asymmetrical grid faults. The simulation and experimental results endorse the superiority of the developed FCS-MPC scheme to diminish the fault effect quickly with lower overshoot and better damping performance than the traditional controller. [ABSTRACT FROM AUTHOR]

In recent years, shipborne emissions have become a growing environmental threat. The International Maritime Organization has implemented various rules and regulations to resolve this concern. The Ship Energy Efficiency Management Plan, Energy Efficiency Design Index, and Energy Efficiency Operational Indicator are examples of guidelines that increase energy efficiency and reduce shipborne emissions. The main engine shaft power (MESP) and fuel consumption (FC) are the critical components used in ship energy efficiency calculations. Errors in ship energy efficiency calculation methodologies are also caused by misinterpretation of these values. This study aims to predict the MESP and FC of a container ship with the help of data-driven methodologies utilizing actual voyage data to assist in the calculation process of the ship's energy efficiency indexes appropriately. The algorithms' prediction success was measured using the RMSE, MAE, and R2 error metrics. When the simulation results were analyzed, the Deep Neural Network and Bayes algorithms predicted MESP best with 0.000001 and 0.000002 RMSE, 0.000987 and 0.000991 MAE, and 0.999999 R2, respectively, while the Multiple-Linear Regression and Kernel Ridge algorithms estimated FC best with 0.000208 and 0.000216 RMSE, 0.001375 and 0.001471 MAE, and 0.999999 R2, respectively. [ABSTRACT FROM AUTHOR]

One of the common power quality (PQ) problems in transmission and distribution systems is the voltage sag that affects the sensitive loads. Losses and problems caused by the voltage sag in the power system can be reduced by correctly determining the relative location of the voltage sag. This paper proposes a novel algorithm to classify voltage sag relative location and fault type, which is the main root cause of voltage sag, based on the actual voltage and current data before and during the voltage sag. The performance of the algorithm is investigated by performing a numerical simulation utilizing MATLAB/Simulink. Moreover, the proposed algorithm is integrated into the power quality monitoring system (PQMS) of the real distribution system and tested. The results show that the performance of the proposed method is satisfactory. [ABSTRACT FROM AUTHOR]

Zero-emission transportation is currently a public priority, especially in big cities. For this reason, the use of electric vehicles (EVs) is receiving much attention. To facilitate the adoption of EVs, a proper charging infrastructure together with energy management is essential. This article proposes a design guideline for a direct current (DC) charging station with bipolar properties. A bipolar system can convert a two-wire system into three wires in a microgrid system with a neutral line. The configuration of the bipolar system supports different loads; therefore, the unbalanced operation is inherent to the system. The proposed bipolar DC charging station (CS) has a three-level balancing converter that reduces the step-down effort chargers. Moreover, this paper proposes the continuous-control-set model predictive control (CCS-MPC)-based balancing strategy that allows the handling of different output loads while keeping the neutral-line voltage efficiently regulated with improved dynamic performance compared to a traditional controller. Stability and parameter robustness analyses are also performed for the control parameter selection. To ensure the performance of the proposed method, both simulation and experimental results are presented and compared with those obtained from the traditional methods. [ABSTRACT FROM AUTHOR]

Smart grid plays a vital role in energy management systems. It helps to mitigate the demand side management of electricity by managing the microgrid. In the modern era, the concept of hybrid microgrids emerged which helps the smart grid management of electricity. Additionally, the Internet of Things (IoT) technology is used to integrate the hybrid microgrid. Thus, various policies and topologies are employed to perform the task meticulously. Pakistan being an energy deficient country has recently introduced some new policies such as Energy Wheeling Policy (EWP), Energy Import Policy (EIP), and Net Metering/Distributed Generation Policy (NMP) to manage the electricity demand effectively. In addition, the Energy Efficiency and Conservation Act (EECA) has also been introduced. In this paper, we present the overview and impact of these policies in the context of the local energy market and modern information and communication mechanisms proposed for smart grids. These new policies primarily focus on energy demand–supply for various types of consumers such as the demand for bulk energy for industrial ventures and the distributed production by consumers. The EWP deals with obtaining power from remote areas within the country to ease the energy situation in populated load centers and the EIP highlights energy import guidelines from foreign countries. The NMP deals with the integration of renewable energy resources and EECA is more focused on the measures and standardization for energy efficiency and conservation. The benefits and challenges related to EWP, NMP, and EIP have also been discussed concerning the present energy crisis in Pakistan. The generalized lessons learned and comparison of a few aspects of these policies with some other countries are also presented. [ABSTRACT FROM AUTHOR]

In recent years, the usage potential of alternative energy sources has been gaining importance to increase the efficiency of ships within the scope of the obligations brought by international maritime regulations. The possibility of using alternative energy sources such as solar energy, wind energy, fuel cells, and waste heat recovery technologies on ships has been evaluated in the literature. Today, ships also have waste heat recovery systems as standard equipment for this purpose, and this method is suitable for thermoelectric generators that generate electricity from temperature differences on shipboards. This article aims to review the thermal technologies for the power generation of shipboards. By conducting a case study, an energy efficiency increase was obtained when functional areas were selected on a practical ship, and the effect of this efficiency increase on emissions was examined. As a result of the research, it was discovered that thermoelectric generators increased onboard energy efficiency and have significant potential for sustainability in the maritime sector. [ABSTRACT FROM AUTHOR]

In light of the reliable operation of renewable shipboard microgrids, this paper implements a fractional-order theory for flexible modeling for an accurate study of shipboard microgrids. Then, it introduces a novel variable structure control strategy based on a fractional-order reduced chatter nonlinear sliding mode. This strategy incorporates a time delay estimation and an optimization routine for parameter adjustments, aiming to achieve nearly time-optimal control performance and faster frequency accommodation. The proposed method exploits the benefits of fractional order modeling, reduced chatter sliding mode, and variable structure approaches. While the adapted reduced chatter strategy may decrease convergence speed, the variable structure strategy compensates for this by accelerating settling speed. These features, along with continuous, soft, and limited control signals, make the proposed method suitable for the challenging conditions of low inertia, high dynamics, uncertainty, and a noisy environment in nonlinear renewable shipboard microgrids. The Lyapunov stability proof and simulation results demonstrate the proposed method's fast, high accuracy, and reliable performance. Furthermore, the validation process, which involves comparisons with conventional sliding-mode strategies, fractional-order proportional-integral-derivative controllers, and experimental test results using the Speedgoat real-time target machine in conjunction with Simulink real-time, serves to further establish the superiority of the proposed approach. • Introduces a novel approach using fractional-order theory for a unique variable structure control strategy tailored for shipboard microgrids. • Presents a cutting-edge control strategy based on fractional-order chatter-free nonlinear sliding mode for nearly time-optimal control performance. • Exploits the advantages of fractional order modeling, chatter-free sliding mode, and variable structure approaches to tackle challenges faced by renewable shipboard microgrids. • Mitigates the convergence speed reduction caused by chatter free solution using continuous, soft variable structure, and limited control signals. [ABSTRACT FROM AUTHOR]

- In recent years, the aviation industry has witnessed a substantial integration of power electronics technology within Aircraft Microgrids (AMs). Consequently, the extension of electrical wiring networks has expanded, resulting in heightened intricacies within these systems. Therefore, the identification and location of faults in wiring networks have become an important topic in AMs to guarantee the safety of the electrical power systems. Time Domain Reflectometry (TDR) is widely used to locate and recognize electric wire faults. However, soft fault location on complex electrical networks using TDR is perplexing due to its weak effect on the reflected signal. Moreover, the existence of noise in the environment can worsen the TDR's performance. In this paper, a new approach based on TDR, along with the Subtractive Correlation Method (SCM) and Neural Network (NN), is proposed. The TDR response of the complex wiring network is determined using a newly proposed model based on the Finite Difference Time Domain (FDTD) method. The validity of the proposed model is established through experimentation including two distinct cable types also the introduced model notably enhances computational efficiency, a fact substantiated by our experimental findings and an extensive benchmarking against recent publications. These evaluations collectively underscore a significant reduction in computational time. Then, the reflected signal undergoes processing through SCM, a technique employed to amplify the subtle influence of the soft fault in two scenarios: one accompanied by noise and the other noise-free. Furthermore, NN is used to handle the inverse problem of localizing and characterizing the soft faults by their exact resistance values. Even within noisy environments, the proposed methodology excels in accurately locating and characterizing soft faults with a high degree of precision, all in real-time diagnostic scenarios. • Novel FDTD-based model for determining the TDR response of intricate wiring networks. • Empirically validated model enhancing computational efficiency and reducing time. • SCM approach amplifies subtle soft fault impacts, even in noisy environments. • Neural Networks excel in precisely localizing and characterizing soft faults by resistance values. • Real-time diagnostic capability for pinpointing and characterizing soft faults with exceptional precision. [ABSTRACT FROM AUTHOR]

The energy consumption of major equipment in residential and industrial facilities can be minimized through a variety of cost-effective energy-saving measures. Most saving strategies are economically viable where several algorithms can be employed to reduce energy consumption to reduce costs to a considerable extent. Machine learning (ML) is one of these techniques. A review of recent research efforts concerning the application of ML strategies to energy conservation and management problems is presented in this study. In addition, ML approaches and strategies for energy-saving problems, management, technologies, and control methods have been discussed. A comprehensive review of all available publications is also used to make observations about past considerations. As a result, it has been concluded that ML is capable of solving a wide range of decision and management problems within a short period of time with minimal energy consumption. In addition, ML perspectives have been viewed from the perspective of emerging communication technologies, instruments, and cyber-physical systems (CPSs), along with the advancement of ultra-durable and energy-efficient Internet-of-Things (IoT) based communication sensors technology. Moreover, a comprehensive review of recent developments in ML algorithms is also included, including safe reinforcement learning (RL), Deep RL, path integral control for RL, and others not previously. Lastly, critical ML considerations such as emergency and remedial measures, integrity protection, fusion with existing robust controls, and combining preventive and emergent measures have been discussed. The implementation of recently applied ML, RL, and IoT strategies for energy management, conservation, and resilient operation is clarified in this paper. The proposed review highlights the advantages and drawbacks of the recent energy conservation strategies. Finally, the perspective solutions have been clarified to cope with the world direction for zero energy buildings. • A comprehensive review of AI techniques in energy applications has been presented. • Empirical analysis of the energy management and conservation methods. • Describes the ML's and IoT's role in energy control and how to implement it. • Explains the challenges of demand-side data pre-processing of machine learning. • Offers possible directions for future research in the resilient operation of smart grids. [ABSTRACT FROM AUTHOR]

• Investigating and revealing potential risks of poor energy quality for shipboard microgrids. • Providing a clear view of the importance of selecting the accurate algorithms for analyzing the quality of energy and delivering a comparative study. • Proposing a developed algorithm, which is an offline-based energy quality analyzing technique developed for the short-term protective action stage to assess the energy quality of shipboard microgrids. • Proposing an enhanced algorithm, which is an online-based energy quality assessing technique, Which is very suitable for the long-term preventive action stage. Retrofitting of shipboard microgrids is receiving much attention nowadays due to the flexibility it offers to adapt existing ships with rapid market variations to move towards all-electric ships (A-ESs). This modernity mainly relies on incorporating the power electronics converters that unfortunately draw a large number of harmonics, which affect the energy quality and threaten the system stability and crew/passengers safety. The contribution of this paper lies in proposing two developed open-loop algorithms to assess the harmonics distortion of A-ESs without relying on signal periodicity. The first algorithm is an offline-based analyzing technique developed for the short-term protective action stage, which incorporates the eigenvalue solution inside the short-time fast Fourier transform (ST-FFT) to adapt its window size. Consequently, this algorithm can provide a comprehensive harmonics analysis with a fast transient response even under large system frequency drifts. The second algorithm is an online-based assessing technique, which is very suitable for the long-term preventive action stage to provide accurate harmonics distortion assessment with the fast transient response and efficient computation burden. This approach relies on cascading three moving average filters (MAFs) with particular window sizes to filter and estimate the mean value inside the discrete Fourier transform and the true RMS blocks without the need of frequency information. Hence, it results in enhancing the harmonics rejection capability of the algorithm even under the existence of non-characteristic harmonics and frequency drifts. Simulation and experimental results are provided to validate the efficacy of the proposed algorithms and the results are compared with traditional methods. [ABSTRACT FROM AUTHOR]