Real-time power system dynamic security assessment based on advanced feature selection for decision tree classifiers

This paper proposed a novel algorithm based on advanced feature selection technique for decision tree (DT) classifier to assess the dynamic security in power system. The proposed methodology utilized symmetrical uncertainty (SU) to reduce the data redundancy in a dataset for DT classifier based dynamic security assessment (DSA) tools. The results show that SU reduces the dimension of the dataset used for DSA significantly. Subsequently, the approach improves the performance of DT classifier. The effectiveness of the proposed technique is demonstrated on modified IEEE 30-bus test system model. The results show that the DT classifier with SU outperform the DT classifier without SU. The performance of the proposed algorithm indicates that the DT classifier with SU is able to assess the dynamic security of the system in near real-time. Therefore, it is able to provide vital information for protection and control application in power system operation

Power quality improvement using dynamic voltage restorer in electrical distribution system: an overview

This paper represents a review of the dynamic voltage restorer for power quality improvement in the electrical distribution system. Over the past 50 years, issues concerning power quality have steadily increased, to prevent the effect of the voltage disturbances, some of the devices are put as a solution to these problems such as distribution static compensator (D-STATCOM), solid-state transformer (SST), and uninterruptible power supply (UPS), dynamic voltage restorer (DVR). The DVR is one of the economic solutions to overcome the voltage disturbances like voltage sag/swell and harmonics. It is widely used to mitigate the voltage disturbances in the power distribution system, especially in the medium and low distribution networks. This paper aims to review the implementation of the DVR in the system integrated with renewable energy resources. This is important because the future of electricity business is moving towards renewable energy and also provides a thorough discussion of the typical components, controllers, compensation methods, and the application of DVR. The extensive review of the technology aims to ease and speed up the development and the advancement of the DVR in the near future

Harmonic Reduction of a Single-Phase Multilevel Inverter Using Genetic Algorithm and Particle Swarm Optimization

Power inverter play an important role in power system especially with its capability on reducing system size and increase efficiently. The recent research trends of power electronic system are focusing on multilevel inverter topics in optimization on voltage output, reducing the total harmonics distortion, modulation technique, and switching configuration. The research emphasizes the optimization with a fundamental switching frequency method that is the optimized harmonic stepped waveform (OHSW) modulation method. The selective harmonic elimination (SHE) calculation has adapted with genetic algorithm (GA) and particle swarm optimization (PSO) in order to speed up the calculation. Both bioinspired algorithms are compared in terms of total harmonic distortion (THD) and selective harmonic elimination for both equal and unequal sources. The overall result showed that both algorithms have high accuracy in solving the nonlinear equation. However, the genetic algorithm showed better output quality in terms of selective harmonic elimination which overall no exceeding 0.4%. Particle swarm optimization shows strength in finding the best total harmonic distortion where in seven-level cascaded H-bridge multilevel inverter (m=0.8) shows 6.8% only as compared to genetic algorithm. Simulation for three-level, five-level, and seven-level for each multilevel inverter at different circumferences had been done in this research. The result draws out a conclusion where the possibility of having a filterless high-efficient inverter can be achieved

The impact of fault current limiter in power system performance

Continues growth of electrical energy demand is resulting in a corresponding increase in the short circuit in power system. Several solutions have been implemented, including the use of Fault Current Limiter (FCL), in order to reduce circuit breakers rated capacity and to limit the electromagnetics stress in associated equipment. This project presents a comprehensive study of the impact of fault current limiter in power system performance. The FCL use for this study is solid-state type because it has advantages in term of flexibility and control over superconducting type. In order to evaluate the impact of fault current limiter in power system performance, simulation model of power system performance with solid-state FCL are used. For simulation model development, MATLAB Simulation Tools: SIMULINK software is used. A distribution system fed from single source is used to assess the impact of FCL to power system performance. The FCL is evaluated in term of its performance in limiting fault current from about 50 kA to a lower value of 1.7 kA. Results show that the solid-state FCL is effective for reducing short circuit currents up to 98% and also can be used to protect busbars from voltage sag when the system is subjected to various types of faults

Estimating dynamic model parameters for adaptive protection and control in power system

This paper presents a new approach in estimating important parameters of power system transient stability model such as inertia constant H and direct axis transient reactance in real time. It uses a variation of unscented Kalman filter (UKF) on the phasor measurement unit (PMU) data. The accurate estimation of these parameters is very important for assessing the stability and tuning the adaptive protection system on power swing relays. The effectiveness of the method is demonstrated in a simulated data from 16-machine 68-bus system model. The paper also presents the performance comparison between the UKF and EKF method in estimating the parameters. The robustness of method is further validated in the presence of noise that is likely to be in the PMU data in reality