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In a low-voltage electric distribution network, arc fault presents a high energy density electricity-discharging phenomenon between conductors, which is often caused by aging of electric facilities, loose contacts and terminals, or insulation failure due to internal and external destructions. A large amount of heat may be created during this discharging, which will further cause the risk of fire hazards to mitigate in the residential environment. Currently, many utility grid operators and electricity users are still devoted to seeking effective detection technology for arc fault protection. This paper proposes a hybrid approach that combines discrete wavelet transform (DWT), empirical mode decomposition (EMD), and dynamic time warping (DTW) methods for low-voltage AC series arc fault detection. In DWT, it uses time–frequency domain characteristics of the arc current signal to extract the occurrence of arc fault. In EMD, it decomposes the complex arc fault current signal into a finite intrinsic mode (IMF) signal; then, instantaneous amplitude of IMF signal is obtained by Hilbert–Huang transform (HHT) as a feature for arc fault identification. Firstly, the results of arc fault detections depend on the results from DWT and EMD. When both two methods detect different results, DTW method will be activated, using the similarity measurements between normal and arc fault current waveforms as an assistant measure to determine the occurrence of arc fault. The performance of the proposed approach is tested and validated using various electric appliances, and the results show that the proposed approach can effectively detect low-voltage AC series arc fault. [ABSTRACT FROM AUTHOR]

In this study, a three-phase four-wire distribution static compensator (DSTATCOM) is proposed to improve power quality, including the compensation of the three-phase unbalanced grid currents, the total harmonic distortion (THD) reduction of the grid current, and the power factor (PF) correction. Moreover, when different types of loads vary in the power system, the instantaneous power follows into or out of the DC-link capacitor in the DSTATCOM and results in poor transient responses of the grid current and DC-link voltage and performance deterioration. Hence, the DC-link voltage control plays a significant part in the DSTATCOM under load variation. For the purpose of mending the transient responses of the grid currents and DC-link voltage control and the performance of the DSTATCOM, the conventional proportional-integral (PI) controller is substituted with a novel online trained wavelet Takagi-Sugeno-Kang fuzzy neural network (WTSKFNN) controller in this study. Furthermore, the network structure and the online learning method of the proposed WTSKFNN controller are described in detail. Finally, the experimental results are given to certify the feasibility and effectiveness of the DSTATCOM using the proposed WTSKFNN controller for the power quality enhancement and the DC-link control improvement under load variation. [ABSTRACT FROM AUTHOR]

Microgrid operation is challenging because the amount of electricity that is produced from renewables is uncertain and the inertia of distributed generation resources is very small. Energy storage systems can regulate energy, improve the reliability of the power systemand enhance the transient stability. This paper determines the optimal capacities of energy storage systems in an islanded microgrid that is composed of wind-turbine generators, photovoltaic arrays, and micro-turbine generators. The energy storage system can enhance the reliability of the microgrid and eliminate the unnecessary load shedding when a severe transient (such as a generator outage) occurs in the islanded microgrid. The studied problem is expressed as a multi-objective programming formulation, which is solved using an immunity-based algorithm. Four objective functions are optimized: minimum of energy storage capacity, minimum of load shedding, maximum of the lowest swing frequency, and minimum of the Customer Average Interruption Duration Index (CAIDI). These four objective functions are subject to both steady-state constraints and the transient-state equality constraint. The steady-state constraints include the total shed load limit, the feasible range of energy storage capacities while the transient-state equality constraint is expressed by the dynamic equation. The Pareto optimums are explored and optimality of the problem is investigated. The simulation results based on an islanded 15-bus microgrid show the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

The expression and calculation of transmission loss (TL) play key roles for solving the power system economic dispatch (ED) problem. ED including TL must compute the total TL and incremental transmission loss (ITL) by executing power flow equations. However, solving the power flow equations is time-consuming and may result in divergence by the iteration procedure. This approach is unsuitable for real-time ED in practical power systems. To avoid solving nonlinear power flow equations, most power companies continue to adopt the TL formula in ED. Traditional loss formulas are composed of network parameters and in terms of the generator's real power outputs. These formulas are derived by several assumptions, but these basic assumptions sacrifice accuracy. In this study, a new expression for the loss formula is proposed to improve the shortcomings of traditional loss formulas. The coefficients in the new loss formula can be obtained by recording the power losses according to varying real and reactive power outputs without any assumptions. The simultaneous equations of the second-order expansion of the Taylor series are then established. Finally, the corresponding coefficients can be calculated by solving the simultaneous equations. These new coefficients can be used in optimal real and reactive power dispatch problems. The proposed approach is tested by IEEE 14-bus and 30-bus systems, and the results are compared with those obtained from the traditional B coefficient method and the load flow method. The numerical results show that the proposed new loss formula for ED can hold high accuracy for different loading conditions and is very suitable for real-time applications. [ABSTRACT FROM AUTHOR]

This study aimed to propose individual phase voltage regulation strategies using the sparrow search algorithm (SSA) in the IEEE 8500-node large-scale unbalanced distribution network with high photovoltaic (PV) penetration. The proposed approach is capable of individual phase regulation, which coordinates the on-load tap changer (OLTC), voltage regulator (VR), switched capacitor bank (SCB), and volt–var setting controlled by a smart inverter to improve voltage variation and unbalance. Consequently, the change time of VRs, the switched times of SCBs, and the individual phase voltage magnitude and unbalance ratio are considered in the fitness function for the SSA. The simulation scenarios fully consider the unbalanced load conditions and PV power output patterns, and the numerical results demonstrate that the voltage variation and unbalance are clearly improved, by 15% and 26%, respectively. The fitness values, operation times of OLTC, VR, and SCB, and the settings of the volt–var controlled smart inverter are also optimized by the SSA. The outcomes of this study are helpful for distribution system operators in formulating voltage control strategies corresponding to different system conditions. [ABSTRACT FROM AUTHOR]

PV hosting capacity (PVHC) analysis on a distribution system is an attractive technique that emerged in recent years for dealing with the planning tasks on high-penetration PV integration. PVHC uses various system performance indices as judgements to find an available amount of PV installation capacity that can be accommodated on existing distribution system infrastructure without causing any violation. Generally, approaches for PVHC assessments are implemented by iterative power flow calculations with stochastic PV deployments so as to observe the operation impacts for PV installation on distribution systems. Determination of the stochastic PV deployments in most of traditional PVHC analysis methods is automatically carried out by the program that is using random selection. However, a repetitive problem that exists in these traditional methods on the selection of the same PV deployment for a calculation was not previously investigated or discussed; further, underestimation of PVHC results may occur. To assess PVHC more effectively, this paper proposes an improved stochastic analysis method that introduces an innovative idea of using repetitiveness check mechanism to overcome the shortcomings of the traditional methods. The proposed mechanism firstly obtains all PV deployment combinations for the determination of all possible PV installation locations. A quick-sorting algorithm is then used to remove repetitive PV deployments that are randomly selected during the solution procedure. Finally, MATLAB and OpenDSS co-simulations implemented on a small distribution feeder are used to validate the performance of the proposed method; in addition, PVHC enhancement by PV inverter control is investigated and simulated in this paper as well. Results show that the proposed method is more effective than traditional methods in PVHC assessments. [ABSTRACT FROM AUTHOR]

An increase in the neutral current results in a malfunction of the low energy over current (LCO) protective relay and raises the neutral-to-ground voltage in three-phase, four-wire radial distribution feeders. Thus, the key point for mitigating its effect is to keep the current under a specific level. The most common approach for reducing the neutral current caused by the inherent imbalance of distribution feeders is to rearrange the phase connection between the distribution transformers and the load tapped-off points by using the metaheuristics algorithms. However, the primary task is to obtain the effective load data for phase rearrangement; otherwise, the outcomes would not be worthy of practical application. In this paper, the effective load data can be received from the feeder terminal unit (FTU) installed along the feeder of Taipower. The net load data consisting of customers' power consumption and the power generation of distributed energy resources (DERs) were measured and transmitted to the feeder dispatch control center (FDCC). This paper proposes a method of establishing the equivalent full-scale net load model based on FTU data format, and the long short-term memory (LSTM) was adopted for monthly load forecasting. Furthermore, the full-scale net load model was built by the monthly per hour load data. Next, the particle swarm optimization (PSO) algorithm was applied to rearrange the phase connection of the distribution transformers with the aim of minimizing the neutral current. The outcomes of this paper are helpful for the optimal setting of the limit current of the LCO relay and to avoid its malfunction. Furthermore, the proposed method can also improve the three-phase imbalance of distribution feeders, thus reducing extra power loss and increasing the operating efficiency of three-phase induction motors. [ABSTRACT FROM AUTHOR]