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.

With widespread non-linear loads and the increasing penetration of distributed generations in the power system, harmonic pollution has become a great concern. The causes of harmonic pollution not only include the integer harmonics, but also interharmonics, which exacerbate the complexity of harmonic analysis. In addition, the output variability of highly non-linear loads and renewables such as electric arc furnaces and photovoltaic solar or wind generation may lead to weakly time-varying harmonics and interharmonics in both frequency and magnitude. These features present challenges for accurate assessment of associated power-quality (PQ) disturbances. To tackle such increasing time-varying PQ problems, a hybrid detection method using synchrosqueezing wavelet transform (SSWT) is proposed. The proposed method first obtains the proper parameter values for the mother wavelet according to numerical computations. The wavelet transform-based synchrosqueezing and a clustering method are applied to determine each frequency component of the waveform under assessment. The time-domain waveform and the associated magnitude of each frequency component is then reconstructed by the inverse SSWT operation. The novelty of the proposed method is that it can decompose the measured waveform containing both harmonics and interharmonics into intrinsic mode functions without the need for fundamental frequency detection. Compared to other time–frequency analysis methods, SSWT has better anti-noise and higher resolution of time–frequency curves; even the measured signal has close frequency components. Simulation results and actual measurement validations show that the proposed method is effective and relatively accurate in time-varying harmonic and interharmonic detection and is suitable for applications in power networks and microgrids that have high penetration of renewables or non-linear loads causing time-varying voltage or current waveforms.

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.

Wind energy is among the fastest-growing electric energy resources worldwide. As the electric power generated by wind turbines (WTs) varies, the WT-connected bus voltage fluctuates. This paper presents a study on implementing a swarm-based proportional and integral (PI) controller for GTO-STATCOM voltage regulator to mitigate the voltage fluctuation caused by the output variations of an offshore wind farm. The proposed swarm-based algorithm for the PI controller is Harris Hawks Optimization (HHO). Simulation results obtained by the HHO algorithm are compared with three other swarm-based algorithms and show that STATCOM with HHO-based PI controller can effectively regulate the WT-connected bus voltage under different wind power output conditions. It shows that the STATCOM compensation performance of the proposed algorithm is superior to that of the compared solutions in maintaining the stable WT-connected bus voltage.

There is an increasing number of microgrid applications for power system networks at different voltage levels. Community microgrid systems are also being encouraged in order to increase energy efficiency, reduce electricity bills, and alleviate the reliability problem with respect to power delivery for local residential users. Understanding electricity information can help in effective management and control of various energy sources operated in community microgrid systems. This paper thus aims to develop a simulation-based electricity analysis scheme for a real community microgrid configuration using a proposed modelling methodology, simulation mechanisms, and a power balancing control strategy under the MATLAB environment. Simulation results considering different weather conditions report the observed performance of electricity analysis. In addition, calculations of electricity bills depending on two electricity rates are discussed, representing the benefits of electricity bill reduction when electricity users accepted the power supply from community microgrid systems.

Microgrid has been used to improve the reliability and resilience of existing electric grid, to manage the integration of various renewable energy sources, and to provide the electricity saving benefit by demand side management. It is now emerging from test benches and demonstration sites into commercial applications, which is driven by technological growth. In this paper, a DC-coupled hybrid microgrid is studied and the end-users electricity analysis is discussed. A simulation-based analysis platform is implemented using MATLAB/Simulink and OPAL-RT real-time simulation technology. The investigations involve modelling, and simulation mechanism. The used control strategies are presented, and two different electricity price rates are introduced to calculate the electricity bill for the studied microgrid system operating in different scenarios. Findings demonstrate the benefit of electricity saving provided by the operation of the microgrid system.