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Distribution network protection is a complicated problem and mal-operation of the protective relays due to false settings make the operation of the network unreliable. Besides, obtaining proper settings could be very complicated. This paper aims to discuss an innovative evolutionary Lightning Flash Algorithm (LFA) which is developed for solving the relay coordination problems in distribution networks. The proposed method is inspired from the movements of cloud to ground lightning strikes in a thunderstorm phenomenon. LFA is applied on three case study systems including ring, interconnected and radial distribution networks. The power flow analysis is performed in Digsilent Power Factory software; then the collected data are sent to MATLAB software for optimization process. The proposed algorithm provides optimum time multiplier setting and plug setting of all digital overcurrent relays in each system. The results are compared with other methods such as particle swarm optimization and genetic algorithm. The result comparisons demonstrate that the proposed LFA can successfully obtain proper relay settings in distribution networks with faster speed of convergence and lower total operation time of relays. Also, it shows the superiority and effectiveness of this method against other algorithms.

A novel LFA is designed based on the movements of cloud to ground lightning strikes in a thunderstorm. This method is used to optimally adjust the time multiplier setting and plug setting of the relays in distribution system to provide a proper coordination scheme.

The proposed algorithm was tested on three case study systems, and the results were compared with other methods. The results confirmed that the proposed method could optimally adjust the relay settings in the electric distribution system to provide a proper protection scheme.

The practical implications can be conducted on distribution networks. The studies provided in this paper approve the practical application of the proposed method in providing proper relay protection in real power system.

This paper proposes a new evolutionary method derived from the movements of cloud to ground lightning strikes in thunderstorm. The proposed method can be used as an optimization toolbox to solve complex optimization problems in practical engineering systems.

Directional Overcurrent Relay (DOCR) coordination computation allowing for desired and high level accuracy in interconnected power systems is very difficult and is a highly constraint oriented optimization problem. This paper aims to study the effectiveness of a newly reported optimization technique, Teaching Learning Based Optimization (TLBO), in protective relay coordination comparing with a widely used optimization technique, Particle Swarm Optimization (PSO).

DOCR coordination in electric power systems is considered as an optimization problem by formulating objective function and specifying problem constraints. Optimum values of the DOCR adjustment parameters (Time Dial Setting and Plug Setting) in terms of reliable coordination margin and operating times of relays are computed by both the algorithms, TLBO and PSO. Optimal coordination is verified in three test bus systems: IEEE 6-bus, WSCC 9-bus and IEEE 14-bus systems.

A comparison between the numerical results of using both the algorithms indicates that the TLBO gives better results in terms of the total operating times of relays and Coordination Time Interval (CTI).

This paper represents the performance of a newly reported optimization technique, TLBO which is till now unpopular to protection engineers to be applied in protective relay coordination applications. The technique provides better performance in comparison to the widely applied technique, PSO. It is expected that TLBO would facilitate protection engineers to decide the optimum and appropriate settings of the relays for leading exact relays coordination.

This paper aims to focus on the implementation of the International Electrotechnical Commission (IEC) 61850–9-2 standard based process bus with merging units (MUs) and sampled values (SV) to improve the protection and control systems. The digital process interface is important to be included on the process bus level.

The IEC 61850–9-2 process bus standard is not extensively used in regard to SV when the IEC 61850 standard is implemented by power utilities. Many protection and control intelligent electronic devices (IEDs) are connected to a substation communication network, routers and switches using fibre-optic linked Ethernet. However, inductive current transformers (CTs) and voltage transformers (VTs) secondary circuits are still hardwired to the IEDs. The paper highlight issues with the copper wires for currents signals and how these issues can be eliminated by using the MUs and the SV protocol. The voltage regulator control IED of each transformer is required to regulate the voltage level of the secondary side bus bar it is connected to. All the regulating IEDs of parallel-connected transformers are required to communicate with each other to share information. They collectively control the bus bar voltage depending on the switching configuration of the parallel transformers.

It is shown that process bus information such as the high voltage switchgear status information of primary plant in the yard, can be used to improve the substation protection and control systems. The power transformer protection and voltage regulator control are focused on.

The deliverables of the research work can be applied in: The Centre for Substation Automation and Energy Management systems of the Department of Electrical Engineering, power utilities and other establishments using power systems and digital substations in the electrical supply industry. The research work on the thesis led to the development of a laboratory test-bench where students can learn and understand the basics of the IEC 61850–9-2 SVs principles. The test-bench components such as the IEDs, real-time digital simulator, standalone MUs and Ethernet equipment can be used for future research applications. The test-bench can be used to demonstrate during course work for students at the University, the basics of digital substations using a process bus network with IEDs, MUs and Ethernet equipment.

The research work showed where lab equipment is getting outdated and future equipment will be required for research work in IEC 61850–9-2 process bus.

Power utilities can benefit from implementing the IEC 61850 part 9–2 of the standard and by using MUs and other process interface information in substations. A cost reduction in high voltage equipment, substation installation and commissioning costs and better performance of protection and control system can be achieved.

This research paper aims to investigate the change detection filter technique with a decision tree-based event (fault type) classifier for recognizing and categorizing power system disturbances on the high-voltage DC (HVDC) transmission link.

A change detection filter is used to the average and differential current components, which detects the point of fault initiation and records a change detection point (CDP). The half-cycle differential and average currents on both sides of the CDP are sent through the signal processing unit, which produces the respective target. The extracted target indices are sent through a decision tree-based fault classifier mechanism for fault classification.

In comparison with conventional differential current protection systems, the developed framework is faster in fault detection and classification and provides great accuracy. The new technology allows for prompt identification of the fault category, allowing electrical grids to be restored as quickly as possible to minimize economic losses. This novel technology enhances efficiency in terms of reducing computing complexity.

Setting a threshold value for identification is one of the limitations. To bring the designed system into stability condition before creating faults on it is another limitation. Reducing the computational burden is one of the limitations.

Creating a practical system in laboratory is difficult as it is a HVDC transmission line. Apart from that, installing rectifier and converter section for HVDC transmission line is difficult in a laboratory setting.

The suggested scheme’s importance and accuracy have been rigorously validated for the standard HVDC transmission system, subjected to various types of DC fault, and the results show the proposed algorithm would be a feasible alternative to real-time applications.

Optimum utilization of investments has always been considered one of the most crucial aspects of capital markets. Investment into various securities is the subject of portfolio optimization intent to maximize return at minimum risk. In this series, a population-based evolutionary approach, stochastic fractal search (SFS), is derived from the natural growth phenomenon. This study aims to develop portfolio selection model using SFS approach to construct an efficient portfolio by optimizing the Sharpe ratio with risk budgeting constraints.

This paper proposes a constrained portfolio optimization model using the SFS approach with risk-budgeting constraints. SFS is an evolutionary method inspired by the natural growth process which has been modeled using the fractal theory. Experimental analysis has been conducted to determine the effectiveness of the proposed model by making comparisons with state-of-the-art from domain such as genetic algorithm, particle swarm optimization, simulated annealing and differential evolution. The real datasets of the Indian stock exchanges and datasets of global stock exchanges such as Nikkei 225, DAX 100, FTSE 100, Hang Seng31 and S&P 100 have been taken in the study.

The study confirms the better performance of the SFS model among its peers. Also, statistical analysis has been done using SPSS 20 to confirm the hypothesis developed in the experimental analysis.

In the recent past, researchers have already proposed a significant number of models to solve portfolio selection problems using the meta-heuristic approach. However, this is the first attempt to apply the SFS optimization approach to the problem.

The purpose of this paper is to estimate that the start-up current parameters are stochastic or not. Electronic equipment in luminaries significantly improves their luminous efficiency, thereby increasing the energy efficiency of lighting installations. However, the use of electronics [e.g. electronic ballasts for discharge lamps or power supply units for light-emitting diode (LED) luminaries] may also cause some negative effects in lighting installations. One of such effects is large inrush current, which can greatly exceed the admissible line load and trigger the overcurrent protective devices.

The paper presents results of laboratory tests together with their statistical analysis of the inrush currents of lighting luminaires. Three road luminaires build in different technologies of similar power have been selected for the study. The theoretical distributions described by the analytical formulas matched the empirical distributions by using the MATLAB’ Statistical Toolbox.

As parameters that characterize short-time overcurrent at start-up are the maximum value of overcurrent amplitude in start-up moment (I_PIC), the duration of overcurrent in start-up moment (t_PIC) and melting integral MI. The aim of this statistical analysis of the selected parameter is to provide an overcurrent mathematical description allowing to estimate the probability of occurrence of values. For lighting luminaire fitted with magnetic ballasts, the parameters analyzed will randomly vary with the moment of power on. For electronic ballasts, the occurrence of this phenomenon depends on the adopted construction solution.

This will allow, for example, to estimate the probability of activation of protection device by comparing the value of the inrush current Joule’s integral MI with its value for the analyzed protection device. The proposed method may be useful for checking the selectivity of the protection devices in the lighting system.

The study enables application of a probabilistic model for analysis of inrush currents of lighting luminaire and predicting the possible consequences of their occurrence.

An annual substation equipment failure report says 3/7 capacitive voltage transformer (CVT) got damaged because of ferroresonance overvoltage. The conventional mitigation circuit fails to protect the transformer as the overvoltage may fall in the range between 2 and 4 per unit. It is necessary to develop a device to suppress the overvoltage as well as overcurrent of the CVT. This study aims to propose the suitability of memristor emulator as a mitigation circuit for ferroresonance.

The literature implies that a nonlinear circuit can protect the transformer against ferroresonance. An attempt is made with a memristor emulator using Operational Amplifier (OPAMP) for the mitigation of ferroresonance in a prototype transformer. The circuit is simulated using PSpice and validated for its ideal characteristics using hardware implementation. The nonlinear memductance is designed which is required to mitigate the ferroresonance. The mitigation performance has been compared with conventional method along with fast Fourier transform (FFT) analysis.

While the linear resistor recovers the secondary voltage by 74.1%, the memristor emulator does it by 82.05% during ferroresonance. Also, the total harmonic distortion (THD) of ferroresonance signal found to be 22.06% got improved as 2.56% using memristor emulator.

The suitability of memristor emulator as a mitigation circuit for ferroresonance is proposed in this paper. As ferroresonance occurs in instrument transformers which have extra high voltage (EHV) rated primary windings and (110 V/[110 V/1.732]) rated secondary windings, the mitigation device is proposed to be connected as a nonlinear load across the secondary windings of the transformer. This paper discusses the preliminary work of ferroresonance mitigation in a prototype transformer. The mitigation circuit may have memristor or meminductor for ferroresonance mitigation when they are commercially available in future.

The electronic component-based memristor emulator may not work at 110 V practically as they may be rated at low power. Hence, chemical component-based memristor emulator was developed to do the same. The authors like to clarify that the memristor will be a solution for ferroresonance in future not the memristor emulator circuit.

With the real form of memristor, the transistor world will be replaced by it and may have a revolution in the field of electronics, VLSI, etc. This contribution attempts to project the use of memristor in a smaller scale in high-voltage engineering.

The electronic component-based memristor emulator is proposed as a mitigation circuit for ferroresonance. The hypothesis has been verified successfully in a prototype transformer. Testing circuit of memristor emulator involves transformer, practically. The mitigation performance has been compared with conventional method technically and justified with FFT analysis.

The paper aims to present an application of teaching learning-based optimization (TLBO) algorithm and static Var compensator (SVC) to improve the steady state and dynamic performance of self-excited induction generators (SEIG).

The TLBO algorithm is applied to generate the optimal capacitance to maintain rated voltage with different types of prime mover. For a constant speed prime mover, the TLBO algorithm attains the optimal capacitance to have rated load voltage at different loading conditions. In the case of variable speed prime mover, the TLBO methodology is used to obtain the optimal capacitance and prime mover speed to have rated load voltage and frequency. The SVC of fixed capacitor and controlled reactor is used to have a fine tune in capacitance value and control the reactive power. The parameters of SVC are obtained using the TLBO algorithm.

The whole system of three-phase induction generator and SVC are established under MatLab/Simulink environment. The performance of the SEIG is demonstrated on two different ratings (i.e. 7.5 kW and 1.5 kW) using the TLBO algorithm and SVC. An experimental setup is built-up using a 1.5 kW three-phase induction machine to confirm the theoretical analysis. The TLBO results are matched with other meta heuristic optimization techniques.

The paper presents an application of the meta-heuristic algorithms and SVC to analysis the steady state and dynamic performance of SEIG with optimal performance.

Line–cell conversion and rotation of operators between cells are common in lean production systems. Thus, the purpose of this study is to provide an integrated look at these two practices through integrating job rotation scheduling and line-cell conversion problems, as well as investigating the effect of rotation frequency on flow time of a Seru system.

First, a nonlinear integer programming model of job rotation scheduling problem and line–cell conversion problem (Seru-JRSP) was presented. Then, because Seru-JRSP is NP-hard, an efficient and effective invasive weed optimization (IWO) algorithm was developed. Exploration process of IWO was enhanced by enforcing two shake mechanisms.

Computations of various sample problems showed shorter flow time and less number of assigned operators in a Seru system scheduled through job rotation. Also, nonlinear behavior of flow time versus number of rotation periods was shown. It was demonstrated that, setting number of rotation frequency to one in line with the literature leads to inferior flow time. In addition, ability of developed algorithm to generate clusters of equivalent solutions in terms of flow time was shown.

In this research, integration of job rotation scheduling and line–cell conversion problems was introduced, considering lack of an integrated look at these two practices in the literature. In addition, a new improved IWO equipped with shake enforcement was introduced.

THE A‐C ELECTRIC POWER GENERATION SYSTEM components for the VFW‐614 aircraft are supplied by the Aerospace Electrical Division of Westinghouse Electric Corporation located in Lima, Ohio. The a‐c electric power system consists of 2 main engine/constant speed drive driven channels and 1 auxiliary power unit (gas turbine) driven channel. Each channel consists of a generator, a generator control unit (GCU), a differential protection current transformer assembly and a control CT assembly that are supplied by Westinghouse AED. All system components are shown in fig 1.