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Due to their significant performance, Phase-Shifted Full-Bridge Converters (PSFBCs) have gained widespread adoption in medium- and high-power applications. The performance of a PSFBC is greatly influenced by its magnetic components, namely the transformer and resonance inductor. To address these challenges, this paper proposes a parameter optimization of magnetic components for PSFBCs, specifically the transformer turns ratio and resonance inductor value, to enhance conversion efficiency and minimize operational loss. A digital twin of PSFBCs enabling a more accurate loss estimation is proposed to achieve this objective. The proposed loss estimation method precisely calculates the effective and circulation intervals and the corresponding current points of the primary-side transformer current, resulting in improved accuracy. By leveraging the digital twin, the effects of transformer turns ratio and resonant inductor value on the conversion efficiency of a PSFBC can be efficiently simulated. This facilitates the parameter optimization of magnetic components, thereby minimizing operational losses across different application scenarios. This paper also designs and implements a PSFBC prototype with a rated input voltage of 380 V, output voltage of 24 V, and output current of 20 A. The experimental results show the influences of transformer turns ratio and resonant inductor value on the PSFBC and validate the proposed digital twin. The proposed parameter optimization of magnetic components is further evaluated across two application scenarios with varying utilization rates. The simulation results indicate a reduction of approximately 14% in operational loss per hour after applying the parameter optimization of magnetic components for the PSFBC used as a battery charger. The results demonstrate the effectiveness and practicality of the proposed digital twin in designing PSFBCs. [ABSTRACT FROM AUTHOR]

There will be an increasing number of retired batteries in the foreseeable future. Retired batteries can reduce pollution and be used to construct a battery cycle ecosystem. To use retired batteries more efficiently, it is critical to be able to determine their State of Health (SOH) precisely and speedily. SOH can be estimated accurately through a comprehensive and inefficient charge-and-discharge procedure. However, the comprehensive charge and discharge is a time-consuming process and will make the SOH assessment for many retired batteries unrealistic. This paper proposes an accurate and efficient SOH Estimation (SOH-E) method using the actual data of retired batteries. A battery data acquisition system is designed to acquire retired batteries' comprehensive discharge and charge data. The acquired discharge data are separated into various time interval-segregated sub-data. Then, the specially designed features for SOH-E are extracted from the sub-data. Neural Networks (NNs) are trained using these sub-data. The retired batteries' SOH levels are then estimated after the NNs' training. The experiments described herein use retired lead–acid batteries. The batteries' rated voltage and capacity are 12 V and 90 Ah, respectively. Different feature value extractions and time intervals that might affect the SOH-E accuracy and are tested. The Backpropagation NN (BPNN) and Long-Short-Term-Memory NN (LSTMNN) are designed to estimate SOH in this paper. The experimental results indicate that SOH can be calculated in 30 min. The Root-Mean-Square Errors (RMSEs) are less than 3%. The proposed SOH-E can help decrease pollution, extend the life cycle of a retired battery, and establish a battery cycle ecosystem. [ABSTRACT FROM AUTHOR]

This article proposes a three-stage dead-time adjustment scheme for the leading-leg and lagging-leg switches of phase-shift full-bridge converter (PSFBC) according to the load conditions to enhance the conversion efficiencies at light loads. This article also investigates an iterative rigorous loss calculation for light loads under dead-time adjustment. The proposed iterative calculation can be used to modify the duty ratio of the transition region and estimate the operating currents more accurately; therefore, the losses of a PSFBC at light loads and under the dead-time adjustments can be effectively estimated. A PSFBC prototype with an input voltage of 380 V, an output voltage of 48 V, and a rated output power of 480 W is designed and implemented in this article. Experimental results show that comparing with the PSFBC without the dead-time adjustment and with the conventional dead-time adjustment, the conversion efficiency enhancements of 12.13% and 5.97% can be achieved by the proposed three-stage dead-time adjustment scheme at about 5% load condition, respectively. For a small-scale data center with 100 designed PSFBCs, simulated results indicate that about 3.21 MWh of electricity and 1.03 tons of carbon dioxide emission can be saved and reduced per year, respectively, by the proposed dead-time adjustment scheme. [ABSTRACT FROM AUTHOR]

This work studies the power quality impacts of electric transportation charging including electric buses (EBs) and electric vehicles (EVs) on distribution systems. The stochastic harmonic models for EBs and EVs and the stochastic models for their usage scenarios are built utilising the measured charging data. Based on these models, a power quality analysis method considering the charging uncertainties of EBs and EVs is proposed in this study and then their impacts on distribution systems are investigated. The Monte Carlo simulation is integrated into the proposed method to study the under voltage, overcurrent, voltage unbalance, transformer overload, harmonic current, voltage etc. caused by the stochastic charging of EBs and EVs. An actual distribution system acquired from Taiwan Power Company is taken as an example to validate the practicability of the proposed method. The test results of the proposed stochastic model are compared with those of the conservative model. [ABSTRACT FROM AUTHOR]

A fully decentralized controlled (FDC) electric vehicle (EV) charger, where its design is intended to mitigate the charging impact on power grids, is proposed in this paper. The proposed FDC EV charger uses the parameters measured from the power grid, EV charger and EV battery pack to adjust the charging current. Fuzzy logic control is used in this paper to integrate these measured parameters into the proposed FDC EV charger. As the proposed charger can be realized without a centralized control center and information exchanges between EV chargers, an FDC scheme for EV charger can therefore be effectively achieved. A prototype of the proposed FDC EV charger with a rated power of 500 W is implemented. Experimental results verify that the proposed charger can automatically adjust the charging current according to variations in the power grid and EV. Simulations analyze the impact of 100 EVs with a rated power of 7 kW charged simultaneously. Simulation results show that the EV charging impact on power grids can be effectively mitigated by the proposed FDC EV chargers. [ABSTRACT FROM PUBLISHER]

The limited capacity of a single inverter has encouraged the usage of parallel inverters for the interconnection of renewable energy generation system. The current-sharing control is one of the commonly used operating strategies for parallel inverters; however, the conversion efficiency using conventional current sharing is low at light loads. Therefore, a smart control strategy for conversion efficiency enhancement of parallel inverters is proposed in this paper. The proposed control strategy is based on the conversion efficiency curve of a single inverter, where a particle swarm optimization based algorithm is utilized to find the optimal conversion efficiency of parallel inverters. Integration of the proposed control strategy into a photovoltaic generation system (PVGS) with a rated output power of 20 kW interconnected by ten inverters with rated output powers of 2 kW is simulated in this paper. Simulation results demonstrate that the proposed smart control strategy can effectively enhance the conversion efficiency of parallel inverters at light loads and increase the electrical energy output of PVGSs. A fully digitally controlled single-phase inverter with a rated output voltage of 220 V and a rated output power of 2 kW is also implemented in this paper. Two implemented inverters are used to validate the performance of the proposed smart control strategy for parallel inverters. Experimental results show that the proposed control strategy can enhance the conversion efficiency of parallel inverters at light loads. [ABSTRACT FROM AUTHOR]

The output power of photovoltaic generation (PVG) varies with solar irradiance and temperature nonlinearly. Therefore, the maximum power point tracking (MPPT) is very important to operate PVG to harvest the maximum solar energy in real time. The perturbation and observation (P&O) method is one of the most commonly used MPPT methods. However, P&O MPPT suffers a tradeoff in selecting the perturbation step sizes of the control variables. This paper proposes a parameter-estimation-based MPPT for PVG. Based on the measured voltages and currents and the characteristic output function of PVG, the proposed MPPT uses parameter estimation to calculate the solar irradiance and temperature directly. The operating voltage of maximum power point can then be found out immediately. The proposed MPPT can effectively reduce the maximum power tracking time of conventional MPPT methods and increase the harvested energy during MPPT. Simulation and experimental results comparing the proposed MPPT to a P&O MPPT demonstrate the performance achieved by the proposed MPPT. [ABSTRACT FROM PUBLISHER]

This study measures the long‐term electric energy data of an electric vehicle (EV) charging station, and uses these field measurements to analyse and construct the load behaviour model of an EV charging station. According to the statistics of field measurements, the state of charge of EV battery pack at the start of charging and the number of EVs starting charging in each time interval can be modelled using Poisson distribution, Roulette wheel selection and uniform distribution. The load behaviour of an EV charging station can be modelled and analysed accordingly. To validate the accuracy of the proposed load behaviour model, a portion of field measurements is reserved for load behaviour model verification. The proposed load behaviour model can also be used to analyse the impacts of EV charging stations on distribution systems. Test results show that the load behaviour model proposed in this study has higher accuracy and the impacts of EV charging stations on distribution systems can be analysed more effectively and precisely. [ABSTRACT FROM AUTHOR]

Fault Management System (FMS) is one of the main functions in Distribution Automation System (DAS); however, the conventional FMS cannot be used in distribution systems with Distributed Generators (DGs) due to the lack of directional function. The directional fault detection device is expensive due to the expensive directional module used. In a wide-ranging distribution system, the investment cost will be very high if the fault detecting devices are expensive. Therefore, the design and implementation of a cost-effective FMS for distribution system with DGs is necessary. A Multi-Level Fault-Current Indicator (MLFCI) having a plurality of reed switches used to detect different current levels is proposed in this paper. The hardware prototype is designed and implemented. An algorithm used to locate fault based on the different fault current levels is derived. A MLFCI-based FMS for distribution systems with DGs is then realized. Experimental results demonstrate the feasibility of the proposed MLFCI. Simulation results are then used to demonstrate the validity of the proposed MLFCI-based FMS for distribution systems with DGs. [ABSTRACT FROM AUTHOR]

Fault indicating devices such as fault indicators (FIs) have been widely used in distribution systems to improve reliability and reduce outage duration. Recently, FIs with communication interfaces are integrated into distribution automation (DA) to further reduce fault-finding time by reporting FIs' statuses back to control center. When faults occur, a lot of alarms and fault information are received from Outage Management System (OMS), Trouble Call System (TCS) and Customer Information System (CIS) and are shown to system operators. As a result, the identification of faulted line sections in a wide-ranging distribution system from FIs' statuses is not an easy task, especially when multiple faults occur simultaneously and/or distributed generators (DGs) are connected. An automatic and fast faulted line-section location method for distribution systems based on FIs is proposed in this paper. The line sections between adjacent FIs can be treated as a possible fault location (PFL) and the fault current detected by the FI can be considered as line current (LC) flowing between the adjacent PFLs. A relationship matrix between PFLs and LCs is then derived and used to design the proposed automatic and fast faulted line-section location method. The faulted line sections can then be located effectively and efficiently by the proposed method. Test results for an actual distribution system demonstrate the validity of the proposed faulted line-section location method. [ABSTRACT FROM PUBLISHER]

Vulnerability mitigation is one of the most important issues for power system planning and operation. Recent research reveals that energy storage systems (ESSs) have a great potential to be used to mitigate power system vulnerability. However, their benefits greatly depend on the locations and capacities of ESSs installed. Therefore this study aims to find the optimal locations and capacities of ESSs for power system vulnerability mitigation. A vulnerability assessment is proposed in this study to calculate the impact factors for power systems based on generator and line outages. A bus impact severity (BIS) analysis is then designed and used to find the vulnerable buses in the power system. Formulations of optimal locations and capacities for ESS placement are derived and solved by a genetic algorithm‐based method. Since better locations for ESS placement can be found, the search space for ESS placement can be reduced effectively. Accordingly, the computational time for finding the optimal solution can be saved and the possibility to obtain a global optimum solution can be improved. Test results show that the proposed method can be used to find the optimal locations and capacities for ESS placement and mitigate system vulnerability effectively. [ABSTRACT FROM AUTHOR]

Utilizing battery storage systems (BSSs) can reduce the intermittent output of PV generation systems (PVGSs) and make them dispatchable. The aim of this paper is to design an optimal charging/discharging scheduling for BSSs such that the line loss of distribution systems interconnected with sizeable PVGSs can be minimized. A mathematical model for BSSs which can be used to simulate the charging procedures such as the commonly-used constant current to constant voltage (CC-CV) charging method, the discharging procedures and the state of charge (SOC) is proposed first. The minimum line loss problem considering the intermittent output of PVGSs and the scheduling of BSSs is then formulated based on the BSS mathematical model. The optimal charging/discharging scheduling of BSSs can then be obtained by a genetic algorithm (GA) based method. Test results demonstrate the validity of the proposed mathematical model and optimal charging/discharging scheduling for BSSs. [ABSTRACT FROM PUBLISHER]

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]

Abstract: This paper tries to use USB and personal digital assistant to develop a novel power quality (PQ) monitoring platform and then integrates GPRS technique into the proposed PQ platform to realize a wide-area PQ monitoring and report-back system. The works of this paper can be divided into three parts. First, a small-scale PQ monitoring platform with appropriately designed I/O interfaces and peripherals is designed and implemented. Next, a GPRS module which can be integrated into the designed PQ monitoring platform is developed. Finally, a web server with well-designed database and web human–machine interfaces used to record abnormal PQ data and display PQ data are designed. The proposed GPRS-based wide-area PQ monitoring and report-back system can be used for PQ monitoring with minimum cost and maximum efficiency. All the functions implemented in this paper can realize the novel, real-time and wide-area PQ monitoring. Experimental results demonstrate the validity of the proposed system. [Copyright &y& Elsevier]

Abstract: Distributed generator (DG) resources are small, self-contained electric generating plants that can provide power to homes, businesses or industrial facilities in distribution feeders. They can be used to reduce power loss and improve service reliability. However, the values of DGs are largely dependent on their types, sizes and locations as they were installed in distribution feeders. A value-based method is proposed in this paper to enhance the reliability and obtain the benefits for DG placement. The benefits of DG placement described in this paper include power cost saving, power loss reduction, and reliability enhancement. The costs of DG placement include the investment, maintenance and operating costs. The proposed value-based method tries to find the best tradeoff between the costs and benefits of DG placement and then find the optimal types of DG and their corresponding locations and sizes in distribution feeders. The derived formulations are solved by a genetic algorithm based method. Test results show that with proper types, sizes and installation site selection, DG placement can be used to improve system reliability, reduce customer interruption costs and save power cost; as well as enabling electric utilities to obtain the maximal economical benefits. [Copyright &y& Elsevier]

Abstract: In a competitive electric energy market, service quality and reliability are two of the essential issues of the business. Distribution automation has been chosen by many utilities around the world as one of the most reliable measures for reducing outage time in their distribution networks. Considering network reliability data and the customer interruption costs, a value-based planning method is proposed in this paper to find the optimal numbers and locations of switches in feeder automation systems. The proposed method takes reliability costs, maintenance and investment costs into account to obtain a feeder automation plan that has a maximum benefit and a proper system reliability requirement. Three stages are involved in the search for optimal solution. Using minimum feeder data and assume equally distributed feeder loads, stage 1 gives initial estimates of reliability indices and costs, and benefit/cost ratios of different feeder automation options. To gain the maximum benefits from feeder automation with reasonable costs, results of stage 1 are used to select feeders with highest priorities for automations. Stage 2 determines the optimum locations of switches that minimize feeder outage costs, and in stage 3, the best locations for tie switches in the automated network are determined. Numerical processing procedure is described and the solution efficiency and results are compared with those obtained from a genetic algorithm. [Copyright &y& Elsevier]

Abstract: This paper proposes a systematic method to allocate the power flow and loss for deregulated transmission systems. The proposed method is developed based on the basic circuit theories, equivalent current injection and equivalent impedance. Four steps are used to trace the voltages, currents, power flows, and losses contributed by each generator sequentially. Using this method, the real and reactive power on each transmission lines and their sources and destinations can be calculated. The loss allocation of each line, which is produced by each generator, can also be obtained. Test results show that the proposed method can satisfy the power flow equation, the power balance equation and the basic circuit theories. Comparisons with previous methods are also provided to demonstrate the contributions of the proposed method. [Copyright &y& Elsevier]

A direct approach for unbalanced three-phase distribution load flow solutions is proposed in this paper. The special topological characteristics of distribution networks have been fully utilized to make the direct solution possible. Two developed matrices—the bus-injection to branch-current matrix and the branch-current to bus-voltage matrix— and a simple matrix multiplication are used to obtain load flow solutions. Due to the distinctive solution techniques of the proposed method, the time-consuming LU decomposition and forward/backward substitution of the Jacobian matrix or Y admittance matrix required in the traditional load flow methods are no longer necessary. Therefore, the proposed method is robust and time-efficient. Test results demonstrate the validity of the proposed method. The proposed method shows great potential to be used in distribution automation applications. [ABSTRACT FROM AUTHOR]

Demand Response (DR) provides an opportunity for customers to reduce their loads during times of high prices and therefore to shave the peak loads. The power outputs of large-scale generator units can be predicted and controlled easily; therefore, the pricing and reliability of conventional power utilities can be assessed straightforwardly. However, the customer loads are very variable and difficult to predict and control; therefore, the integration of DR might cause uncertainty issues on pricing and reliability and is essential to be further investigated. A novel uncertainty model for load reduction is proposed in this paper. The probability intensities of load reduction are first estimated from the measured load reduction variations. A multi-state probability model is then proposed for load reduction and the Markov process is used to calculate the state probabilities. A stochastic analysis scheme using Monte Carlo simulation for pricing and reliability taking the DR uncertainty into account is then investigated. Several cases are designed to compare the effects of DR uncertainty. Simulation results show that the proposed uncertainty model can be integrated into conventional economic dispatch to precisely evaluate the DR uncertainty on system operation and reliability. [ABSTRACT FROM AUTHOR]

This paper studies the system unbalance caused by rooftop Photovoltaic Generation Systems (PVGSs) in distribution networks and proposes an improved method. The voltage and current unbalance studies for three extreme cases considering all rooftop PVGSs being connected to one single phase and then the stochastic analyses for the integration cases of rooftop PVGSs are considered. These three extreme cases lead to severe system unbalance problems. An improving method that combines the On Load Tap Changer (OLTC) and the optimal phase arrangement of distribution transformers is proposed in this paper to mitigate the system unbalance. The OLTC-based improving method is applied first. If the system unbalance is still out of range, the optimal phase arrangement of distribution transformers is further used to mitigate the system unbalance problem. The objective function of optimal phase arrangement is to minimize the system unbalance with the constraints of voltage limits, line flow limit, etc. Test results show that the proposed method can improve the system unbalance significantly even under very extreme cases. [ABSTRACT FROM AUTHOR]

Fault Current Indicators (FCIs) with communication interfaces have been widely used in distribution systems to reduce fault-finding time. The effectiveness of a Fault Management System (FMS) composed of FCIs greatly depends on the performance of the communication network deployed by the FCIs and the failure rates of distribution systems. The conventional techniques only focus on the issues of optimal number and location of FCIs or communication network deployment individually; therefore, the effectiveness of an FMS cannot be assessed realistically. A systematic effectiveness assessment methodology for FMS considering the performance of the communication network deployed by the FCIs and the failure rates of distribution systems is vital and is investigated in this paper. A communication evaluation platform is designed in this paper and used to acquire the field measurements of communication parameters. The communication parameters, especially the Packet Success Rate (PSR), between two adjacent FCIs are measured, and the Probability Density Function (PDF) of the PSR can be built accordingly. The effectiveness of the FMS is then assessed by stochastic analysis considering the failure rates of the distribution system and PSR PDFs between two adjacent FCIs. Due to the characteristics of easy installation, maintenance, longer battery life, lower cost, and so on of ZigBee, the ZigBee-based FCI is mainly discussed in this paper. In order to efficiently find the communication route when a fault occurs, a fast communication route tracking method is also proposed in this paper and its feasibility is demonstrated in an actual distribution system. Experimental and simulation results demonstrate the validity of the proposed systematic effectiveness assessment methodology for an FMS composed of FCIs. The proposed assessment methodology can more realistically react to the actual conditions of the FMS and therefore save on installation time and costs. [ABSTRACT FROM AUTHOR]

Electric load analysis is an important task in early new stage for design of shipboard power systems (SPSs). The installation generation capacity onboard depends on the accurate result of the analysis, which significantly affects the system economic and secure operations. In the traditional electrical load analysis, the demand factor is often obtained from engineering experiences which may lead to inaccurate analysis results. In order to obtain better results, a methodology for electrical load analysis in SPSs is proposed in this article. The load analysis spreadsheet is adopted to find the power consumption of key electric loads in SPSs. The actual power consumptions of selected loads are collected by intelligent meters. The statistical analysis is then performed to find the critical parameter of each selected load in the load analysis under different operating conditions based on the power measurement of field test and load analysis is performed for estimating system power demand accordingly. The large practical maritime vessel power systems are selected for numerical analysis to ensure the performance of the proposed method. The proposed method has been adopted by local ship builders in Taiwan to better understand the load characteristics in shipboard power systems to support various functions of system planning and operation in a more effective manner. [ABSTRACT FROM AUTHOR]

In order to solve the problems caused by the pulsating current ripple of switching-mode power converters, a passive pulsating ripple canceling circuit (PPRCC) is proposed in this paper. The features of the proposed PPRCC include simple, modular structure, and high degree of design flexibility. By integrating the proposed PPRCC, an input current ripple-free flyback-type converter is adopted and analyzed as an example because of its comprehensive utilization in small power rating commercial products. In addition, the switch voltage spike of flyback converter can be suppressed by integrating the proposed PPRCC without using snubbers, it turns out that the efficiency can be further improved. The corresponding operating principle, steady-state analysis, and zero ripple design criteria of the proposed PPRCC are provided. Finally, a 100 W laboratory prototype is constructed to verify the effectiveness of the proposed principle. Experimental results show that the resulting peak-to-peak input current ripple is reduced by 96% and nearly 0.5% and 1.7% improvement in efficiency can be achieved by the proposed PPRCC, at 80 W and 100 W load conditions, respectively. [ABSTRACT FROM PUBLISHER]

This paper considers the use of phasor angle measurements provided by phasor measurement units to identify multiple power line outages. The problem of power line outage identification has traditionally been formulated as a combinatorial optimization problem, the optimal solution of which can be found through an exhaustive search. However, the size of the search space grows exponentially with the number of outages and may thus pose a potential problem for the practical implementation of an exhaustive search, especially when multiple power line outages are considered in a power system. To reduce the complexity while improving outage detection performance, we propose a novel global stochastic optimization technique based on cross-entropy optimization, which has been proven to be a powerful tool for many combinatorial optimization problems, to identify multiple line outages. To validate the effectiveness of the proposed approach, the algorithm is tested using IEEE 118- and 300-bus systems, as well as a Polish 2736-bus system. Simulation results demonstrate that the percentage of correctly identified line outages achieved by the proposed method outperforms those obtained by existing sparse signal recovery algorithms. [ABSTRACT FROM PUBLISHER]