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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.

This paper proposes an adaptive Kalman filter (AKF) control algorithm for capacitive touch panels under the radiation effect of a commercial fluorescent lamp. The predicted covariance matrix of the proposed algorithm is timely updated by two-dimensional gesture compensation. It adaptively adjusts the filter correction manner between fast tracking and smoothing modes. The trajectory area and velocity concept builds up the compensation method and proves in real-time practice by a microprocessor unit. The electromagnetic radiation effect is investigated to obtain the lamp emission noise level. A comprehensive system structure provides the flexibility and efficiency in competing with different algorithms for comparison. A microprocessor unit completed the AKF method calculation in 8.23 ms under fluorescent lamp lightening condition in real time. All Python environments are implemented in the merit of hardware peripheral support, rich programming environments, and open source modules.

The classification of sound signals can be applied to the fault diagnosis of mechanical systems, such as vehicles. The traditional sound classification technology mainly uses the time-frequency domain characteristics of signals as the basis for identification. This study proposes a technique for visualizing sound signals, and uses artificial neural networks as the basis for signal classification. This feature extraction method mainly uses a principle to convert a time domain signal into a coordinate symmetrized dot pattern, and presents it in the form of snowflakes through signal conversion. To verify the feasibility of this method to classify different noise characteristic signals, the experimental work is divided into two parts, which are the identification of traditional engine vehicle noise and electric motor noise. In sound measurement, we first use the microphone and data acquisition system to measure the noise of different vehicles under the same operating conditions or the operating noise of different electric motors. We then convert the signal in the time domain into a symmetrized dot pattern and establish an acoustic symmetrized dot pattern database, and use a convolutional neural network to identify vehicle types. To achieve a better identification effect, in the process of data analysis, the effect of the time delay coefficient and weighting coefficient on the image identification effect is discussed. The experimental results show that the method can be effectively applied to the identification of traditional engine and electric vehicle classification, and can effectively achieve the purpose of sound signal classification.

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.

The calculation of the magnitudes and phase angles of the bus voltage is a challenging task in real-time applications for power systems. Voltage profile, which denotes the present conditions of a power system, is determined by executing the traditional AC power flow program or by searching the supervisory control and data acquisition system. The AC power flow program is not suitable for several real-time applications, such as contingency analysis and security control calculations, because of its complexity and convergence problems. Fast computation is the major concern in such applications. In this paper, a new method based on sensitivity factors, referred to as Jacobian-based distribution factors (JBDFs), is proposed for calculating the magnitudes and phase angles of bus voltages. This method requires setting up JBDFs and deriving optimal solution paths of bus voltage for non-swing buses through dynamic programming under base-case loading conditions. Under real-time conditions, the proposed method initially calculates real and reactive power line flows via JBDFs, and then computes the voltage magnitudes and phase angles of non-swing buses through the derived optimal solution paths. The excellence of the proposed hybrid calculation method is verified by IEEE test systems. Simulation results demonstrate that the proposed method exhibits fast computation and high accuracy. Thus, the method is suitable for real-time applications. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

This paper proposes a simple and efficient approach for the optimal dispatch in a medium-voltage microgrid (MG) with various types of distributed generation (DG). The fuel costs generated by these DGs are determined using quadratic and linear functions dependent on the types of DGs. Instead of using the traditional Lagrange multiplier method for power system economic dispatch, the proposed direct search method (DSM) approach is able to handle several inequality constraints without introducing any multipliers and furthermore it can solve the non-derivative problems or the fuel cost functions being much more complicated. Accordingly, the DSM is proposed for determining the optimal dispatch of MGs with various types of DG to minimize generation costs under grid-tied and autonomous operations. Results demonstrate that the proposed DSM is a highly suitable and simple approach to determining the optimal dispatch in medium-voltage MGs with various types of DG.

The inclusion of microgrids (MGs) in power systems, especially distribution-substation-level MGs, significantly affects power systems because of the large volumes of import and export power flows. Consequently, power dispatch has become complicated, and finding an optimal solution is difficult. In this study, a three-stage optimal power dispatch model is proposed to solve such dispatch problems. In the proposed model, the entire power system is divided into two parts, namely, the main power grid and MGs. The optimal power dispatch problem is resolved on the basis of multi-area concepts. In stage I, the main power system economic dispatch (ED) problem is solved by sensitive factors. In stage II, the optimal power dispatches of the local MGs are addressed via an improved direct search method. In stage III, the incremental linear models for the entire power system can be established on the basis of the solutions of the previous two stages and can be subjected to linear programming to determine the optimal reschedules from the original dispatch solutions. The proposed method is coded using Matlab and tested by utilizing an IEEE 14-bus test system to verify its feasibility and accuracy. Results demonstrated that the proposed approach can be used for the ED of power systems with MGs as virtual power plants.

This study proposes a novel network sensitivity-based approach to solving complex power flow calculation problems in real time. A new sensitivity factor, named Jacobian-based distribution factor (JBDF), is used for the calculation of active and reactive power flow in transmission systems. It is derived from the Jacobian matrix of the base case Newton-Raphson power flow solution, and kept constant during real-time line flow calculation. Unlike well-known distribution factors, such as generation shift distribution factor (GSDF), generalised generation shift distribution factor (GGDF) and Z-bus distribution factor (ZBD), this approach reflects changes in complex injection power. Changes in load conditions from base case loads, with either conforming or non-conforming changes in complex power in each bus, can be used to rapidly compute active and reactive power flow without iterations. The proposed approach was tested on IEEE 14-Bus and 30-Bus systems. Numerical results demonstrate that the proposed approach is not only superior to previous distribution factors, but also compares favourably with the Newton-Raphson power flow method. It is well suited to real-time applications in steady-state security control and optimal dispatch.