Development Of Knowledge-Based Power System Protection Design Courseware

Power system protection is a relatively specialized topic that encompasses a large variety of areas from generator protection at the source side to as far as motor protection at the load end. However, the sources for a complete collection of information on power system protections comprising the generator protection, station bus protection, line protection, transformer protection and motor protection are obviously scattered. Having been in the engineering consultancy business for years, it is realized that finding even a fundamental knowledge of a particular protection scheme in the line protection area in a convenient way is somewhat cumbersome. There isn't any interactive multimedia application software that can offer a complete compilation of topics on various power system protections comprising not only theories but also some pertinent industry application recommendations. It is therefore the objective of the project to develop, using an expert system approach, an interactive multimedia courseware to serve as a computer-based training tool in power system protections by integrating technical theories, industrial application recommendations and some specific simulations by which the user has a wide range of choices for obtaining technical information on power system protection. The method involved in designing the courseware revolves around the approach of using an authoring expert system shell Macromedia Director. It provides the facility of blending the power system protection knowledge domain and interactivity knowledge

Artificial neural network application in coordination of directional overcurrent protective relays in electrical mesh distribution network

Directional Overcurrent relays (DOCR) applications in meshed distribution network (MDN) eliminate short circuit fault current flow due to the system topological structure. Effective and reliable coordination between primary and secondary relay pairs eliminated miscoordination in MDN system. Otherwise, the risk of safety of lives and installations may be compromised alongside with system instability. This paper proposes an Artificial Neural Network (ANN) approach to improve the optimized DOCR response time to short circuit fault within the MDN in order to address miscoordination problem due to wrong response time among adjacent DOCRs to the same fault location. A test model series of several DOCRs in simulated IEEE 8-bus test system, designed in DigSilent Power Factory. Extracted data from three phase short circuit fault analysis, applied in numerical optimization of time setting multiplier (TSM), plug setting multiplier (PSM) and operation time of DOCRs. These data adapted in function fitting training of ANN to determine an improved optimal operation time of DOCRs in general network

Novel Rule Base Development from IED-Resident Big Data for Protective Relay Analysis Expert System

Many Expert Systems for intelligent electronic device (IED) performance analyses such as those for protective relays have been developed to ascertain operations, maximize availability, and subsequently minimize misoperation risks. However, manual handling of overwhelming volume of relay resident big data and heavy dependence on the protection experts’ contrasting knowledge and inundating relay manuals have hindered the maintenance of the Expert Systems. Thus, the objective of this chapter is to study the design of an Expert System called Protective Relay Analysis System (PRAY), which is imbedded with a rule base construction module. This module is to provide the facility of intelligently maintaining the knowledge base of PRAY through the prior discovery of relay operations (association) rules from a novel integrated data mining approach of Rough-Set-Genetic-Algorithm-based rule discovery and Rule Quality Measure. The developed PRAY runs its relay analysis by, first, validating whether a protective relay under test operates correctly as expected by way of comparison between hypothesized and actual relay behavior. In the case of relay maloperations or misoperations, it diagnoses presented symptoms by identifying their causes. This study illustrates how, with the prior hybrid-data-mining-based knowledge base maintenance of an Expert System, regular and rigorous analyses of protective relay performances carried out by power utility entities can be conveniently achieved

Two-phase optimal PMU placement considering complete topological observability level for single line contingency

In order to monitor constantly power systems states, the accurate monitoring technique by Phasor Measurement Unit (PMU) has drawn attention. The use of the PMU as a meter in state estimation for constant understanding the power system state will improve the estimation accuracy and the computational burden. However, the number and the location of installed PMUs that realize topological observability for state estimation have to be optimized because of the economic perspective. Furthermore, the PMU measurement network redundancy for a single line contingency in a power system needs to be taken into account. Hence, this research proposes an optimal PMU placement by a two-phase optimization method. The first phase strategy minimizes the number of placed PMUs and the second phase strategy maximizes a PMU measurement redundancy index called Complete Topological Observability Level (CTOL) for a single line contingency. Improving the CTOL means that the PMU placement has higher possibility to carry out state estimation by complete topological observability. Because of the problem characteristics, Mutation and Reposition Binary Particle Swarm Optimization (MRBPSO) for the first phase, and Simulated Annealing (SA) for the second phase are applied to solve the problem. As a result of optimization, the suboptimal solution in the second phase is improved compared to the first one in each parametric constraint in example power systems of IEEE 57-bus and RTS-96

Reliably optimal PMU placement using disparity evolution-based genetic algorithm

Phasor Measurement Units (PMUs) are an important component in Wide Area Protection (WAP)- based operations in power systems. It is needed that a certain placement scheme of PMUs is suggested if power system scale gets larger. The optimal placement of PMU in power systems has been considered and formulated in order to reduce the number of installed PMUs while accomplishing a desired level of reliability of observation. Optimal PMU Placement (OPP) problem as the combinatorial optimization problem has been formulated to determine the minimum PMU location in the power system. In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. Genetic Algorithm (GA) is employed for the purpose of comparison with DEGA. The optimization model is solved for IEEE 118 standard bus system. DEGA can find better placement suggestion compared with GA because of the nature of evolution that models the double spiral structure of DNA to hold the diversity of population

Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report

Protective relay performance analysis is only feasible by first formulating the hypothesis of expected relay operations beforehand. Traditionally, the process involved in discovering the relay operation characteristics is bogged down by the issues of differing knowledge of protection experts, meticulous manual understanding of complex relay event report and the need to have supplementary data from diverse intelligent electronic devices. This paper investigates the implementation of a novel data mining approach of integrated-Rough-Set-and-Genetic-Algorithm based rule discovery and Rule Quality Measure to hypothesize expected relay behavior in the form of an association rule from digital protective relay’s resident event report. Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. Subsequently, the Rule Quality Measure, combined with rule interestingness and importance judgment, deduces the relay CD-decision algorithm to the desired relay CD-association rule. The relay CD-association rule in its singularity form essentially describes the logical pattern of the correlating descriptions of conditions (i.e., attribute set C for various multifunctional protection elements) and the decision class (i.e., attribute D for trip assertion status). Using the area under the ROC curve measurements, the CD-decision algorithm has been verified to be able to predict as well as discriminate future unknown-trip-state relay events in unsupervised learning. This evaluation is necessary to allow the eventual deduction of the single relay CD-association rule to take place. The discovered CD-association rule, and thus the desired hypothesis, has been proven to be an exact manifestation of the relay operation characteristics hidden in the event report

Reliability-based phasor measurement unit with outage of transmission lines

This paper discussed on the Monte-Carlo simulation technique to determine the optimal placement of Phasor Measurement Unit (PMU) in power system whilst ensuring the observability of the system. In addition, the information on Force Outage Rate (FOR) of the system can be calculated using Markov Chain technique. The FOR represents the level of risk security for the transmission line that happened because of unscheduled and unexpected failure or repair in the system. Subsequently, the reliability model of the transmission line can be developed. Using IEEE 57-bus system, the results obtained from Monte-Carlo simulation technique demonstrate the optimal PMU placement, the desired reliability of the Wide Area Monitoring System (WAMS) as well as the number and location of covered contingencies of the system

Influence of measurement uncertainty propagation in current-channel-selectable multi objective optimal phasor measurement unit placement problem

This paper proposes current-channel-selectable multi objective optimal Phasor Measurement Unit (PMU) placement problem with measurement uncertainty propagation. In proposed Multi Objective Optimal PMU Placement (MOOPP) problem, allocation of the current phasor channel of the PMU can be selected for reducing the total PMU placement cost. However, in practice, uncertainty of measurement makes the estimation error bigger because of use of pseudo measurement by the current channel selection. This paper proposes the optimal PMU placement method considering minimizing both the total PMU placement cost and the state estimation error with uncertainty propagation. The result of the numerical experiment demonstrates the advantage of considering the measurement uncertainty propagation, compared to the conventional method which ignores it, in IEEE New England 39-bus test system. As a result, the proposed method obtained a better Pareto solution compared to the conventional methods because of consideration of measurement uncertainty in the pseudo measurements

Optimal location and size of distributed generation to reduce power losses based on differential evolution technique

An electric power system generate electricity to meet demands. Distributed Generation (DG) allows electricity to be generated in a small capacity where the customer is located. In this paper, multi-objective functions based on the indices of system performance are formulated and used to determine the best location. The Differential Evolution technique (DE) has been employed to calculate optimal sizing for each location. Unity power factor DG model have been studied in this work and the problems solved with one DG unit. IEEE 14 bus has been used as a test system