https://cyberleninka.org/article/n/468779.pdf

A review of metaheuristic scheduling techniques in cloud computing

A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution

This article presents a bibliographic survey over the last 40 years on the research and development and on the procedures for evaluating faults by dissolved gas analysis of power transformers.

Dissolved gas analysis technique for incipient fault diagnosis in power transformers: A bibliographic survey

This paper presents an integrated model based upon the fuzzy approach and evidential reasoning decision-making approach to condition assessment of power transformers. An assessing index system, including the DGA data, electrical testing, and oil testing, is established to facilitate the assessing model. The model is composed of two levels, that is, the fuzzy model and evidential reasoning model. The fuzzy model is proposed for generating the original basic probability assignments for the second-level model. Afterwards, an evidential reasoning decision-making model is utilized to combine all of the evidence and give an overall evaluation conclusion. Based upon this integrated model, a decision-making procedure is put forward to serve as an effective tool for transformer condition assessments. The results show that the assessing model is capable of offering an overall evaluation of the observed transformer condition.

An Integrated Decision-Making Model for Condition Assessment of Power Transformers Using Fuzzy Approach and Evidential Reasoning

ower transformers are one of the most expensive elements in a power system, and their failure is a very costly event. Power transformers are mainly involved in energy transmission and distribution. Unplanned power transformer outages have considerable economic impact on the operation of electric power networks. To have reliable operation of transformers, it is necessary to identify problems at an early stage before a catastrophic failure occurs. In spite of corrective and predictive maintenance, preventive maintenance is gaining due importance in the modern era, and it must be taken into account to obtain the highest reliability of power apparatus such as power transformers. The well-known preventive maintenance techniques such as dissolved gas analysis (DGA), thermal monitoring, partial discharge measurement, capacitance and tan delta measurements, frequency response analysis, etc. are performed on transformers for a specific type of problem. DGA is a very efficient and reliable tool for the earliest detection of inception faults in transformer and other electrical equipment using insulating oil. Condition monitoring of electrical equipment, such as transformers, helps users in many ways such as planning of maintenance schedule, obtaining knowledge of the health of equipment, estimating the remaining service life of equipment, finding areas of further improvement, refining product specification, etc. Kraft paper (cellulose) immersed in mineral oil is used as the insulation system for the copper windings in large power transformers. As the system ages under load, the paper and oil can degrade, potentially leading to catastrophic failure. Partial discharge (PD) is an important tool for improving the reliability of HV insulation systems. It is a very sensitive and nondestructive method of evaluation of the health of the insulation of any HV equipment. PD always is associated with the degradation of insulation systems in HV equipment. Therefore, PDs need to be detected, measured, located, and reduced to a safe value so that the quality of the insulation system is not affected.

Condition Monitoring of Power Transformers - Bibliography Survey

A two areas network connected by a transmission line of 500 Kv 200km is simulated in MATLAB to generate the faulted voltage and current signals. And the network was modeled as a distributed parameters. Then Discrete Wavelet transform based algorithm is developed by using "C" programming to identify and determine the fault location in transmission line.

Fault detection, classification and location on transmission lines using wavelet transform

The paper investigates specific methodologies for the effective use of neural networks. For this purpose 220/132/11 kV 100 MVA transformer is considered. A transformer model can be viewed as a functional approximator constructing an input-output mapping between specific variables and the terminal behaviors of the transformer. A neural network system is proposed to implement the entire approximating task by taking the advantage of its self learning and highly non-linear mapping capability. Two kinds of neural networks, back propagation feed forward network (BPFN) and radial basis function network (RBFN) were investigated to model the faults in power transformers. A voltage impulse of 1 kV is applied at the HV terminal and different types of fault conditions are simulated using PSPICE (Simulation Program with Integrated Circuit Emphasis) and thus the data generated is used for training and testing the neural network.

Modeling transformer internal short circuit faults using neural network techniques

Conventional space vector pulse width modulation based asymmetrical dual inverter configuration produces high common mode voltage (CMV) variations. This CMV causes the flow of common mode current, which adversely affects the motor bearings and electromagnetic interference of nearby electronic systems. In this study, a simple and generalized carrier based pulse width modulation (PWM) technique is proposed for dual inverter configuration. This simple approach generates various continuous and discontinuous modulating signals based PWM algorithms. With the application of the discontinuous modulating signal based PWM algorithm to the asymmetrical dual inverter configuration, the CMV can be reduced with a slightly improved quality of output voltage. The performance of the continuous and discontinuous modulating signals based PWM algorithms is explored through both theoretical and experimental studies. Results show that the discontinuous modulating signal based PWM algorithm efficiently reduces the CMV and switching losses.

/pdf/reduction-of-common-mode-voltage-in-asymmetrical-dual-3b513pylii.pdf

Reduction of Common Mode Voltage in Asymmetrical Dual Inverter Configuration Using Discontinuous Modulating Signal Based PWM Technique

This paper proposes Dolphin echolocation Algorithm (DEA) for solving the multi-objective reactive power dispatch problem. Echolocation is the genetic sonar used by dolphins and more than a few kinds of other animals for direction-finding and hunting in different environments. This aptitude of dolphins is mimicked in this paper to develop a new process for solving optimal reactive power dispatch problem. A detailed study has shown that meta-heuristic algorithms have certain overriding rules. These rules will facilitate to get enhanced results. Dolphin echolocation algorithm takes reward of these rules and outperforms many active optimization methods. The new approach DEA leads to outstanding results with little computational efforts. In order to evaluate the efficiency of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other specified algorithms. Simulation results show that DEA is superior to other algorithms in tumbling the real power loss and enhancing the voltage stability.

https://ijcjournal.org/index.php/InternationalJournalOfComputer/article/download/244/243

Dolphin Echolocation Algorithm for Solving Optimal Reactive Power Dispatch Problem

This paper proposes a new heuristic algorithm that is enthused by the black hole phenomenon called as Black Hole Algorithm (BHA) used for solving the multi-objective reactive power dispatch problem. The Black Hole Algorithm (BHA) starts with a preliminary population of contestant solutions to an optimization problem. For all iteration of the black hole algorithm, the most excellent candidate is preferred to be the black hole, which followed by pulling further candidates around it, called stars. If a star move very close to the black hole, it will be swallowed by the black hole and is disappeared everlastingly. In such a case, a fresh star - candidate solution is arbitrarily generated and positioned in the search space and starts a fresh search.In order to evaluate the efficiency of the proposed algorithm; it has been tested on standard IEEE 30 bus system and compared to other specified algorithms. Simulation results show that BHA is superior to other algorithms in reducing the real power loss and improving the voltage stability.

Black Hole Algorithm for Solving Optimal Reactive Power Dispatch Problem

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