{"title":"Application of wavelet theory to power distribution systems for fault detection","authors":"J. Momoh, T. Rizy","doi":"10.1109/ISAP.1996.501096","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501096","url":null,"abstract":"In this paper, an investigation of the wavelet transform as a means of creating a feature extractor for artificial neural network (ANN) training is presented for application to distribution network fault location. The study includes a terrestrial-based three-phase delta-delta power distribution system. Faults were injected into the system and data was obtained from experimentation. Graphical representations of the feature extractors obtained in the time domain, the frequency domain and the wavelet domain are presented to ascertain the superiority of the wavelet transform feature extractor.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126271061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A genetic algorithm for reliable distribution system design","authors":"R.E. Brown, S. Gupta, R. Christie, S. Venkata","doi":"10.1109/ISAP.1996.501040","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501040","url":null,"abstract":"The steps needed in distribution system design for reliability (DFR) are defining, assessing, and optimizing a criterion. Until recently, distribution design has been largely left to engineering judgment without the help of analytical tools. This paper proposes an economic reliability criterion, an analytical assessment method, and then applies genetic algorithms to help place switches and protective devices to minimize the total cost of reliability. The distribution system DFR is then applied to an existing utility distribution feeder and the results are discussed.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114543554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sang-Hee Kang, Kwang-Ho Kim, Kyung-Rae Cho, Jong-keun Park
{"title":"High speed offset free distance relaying algorithm using multilayer feedforward neural networks","authors":"Sang-Hee Kang, Kwang-Ho Kim, Kyung-Rae Cho, Jong-keun Park","doi":"10.1109/ISAP.1996.501070","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501070","url":null,"abstract":"A new high-speed digital distance relaying algorithm using artificial neural networks is presented. The proposed artificial neural network models are trained with the input patterns of distorted voltage and current signals passed a lowpass filter and with the target patterns of real and imaginary components of DC-offset free current and voltage signals conditioned by a DC-offset removing algorithm. The artificial neural networks play the roles of a DC-offset removing filter and a Fourier filter. In accordance with a series of tests, the relay operating time is less than 9 ms after faults in a 80 km, 154 kV, 60 Hz overhead transmission line system.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128489482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An expert system based aid for clearing overloads on power system plant","authors":"M. Negnevitsky, T. Le","doi":"10.1109/ISAP.1996.501076","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501076","url":null,"abstract":"This paper describes an expert system application for clearing emergency overloads on power systems. A method employing the network sensitivity factors is used to determine appropriate control actions and amount of corrections required to clear overloads. The expert system was developed on the basis of the commercial package VP EXPERT. VP EXPERT provides interactions with a power flow analysis package, PSSE, to calculate network sensitivity factors and line flows, and other external programs and a database. The governing rules for clearing overloads are introduced and the proposed approach is implemented on the IEEE 30-bus system.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127980260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Decision support for hydropower plant upgrading: integrating multi attribute decision making and knowledge based systems","authors":"G. Tangen, P. Stoa","doi":"10.1109/ISAP.1996.501059","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501059","url":null,"abstract":"There is a need to improve the procedures for ranking reconditioning projects in hydropower plants to optimize the allocation of resources, and a concept for decision support based on value focused thinking and multi attribute decision making is developed. This paper suggests an integration of multi attribute decision making and knowledge based support to realize the concept. The two disciplines have different qualities and they can contribute at different stages of the decision process.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An artificial neural network application to distance protection [of power systems]","authors":"W. Qi, G. Swift, P. McLaren, A. Castro","doi":"10.1109/ISAP.1996.501073","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501073","url":null,"abstract":"An application of artificial neural networks (ANNs) to power system distance protection is presented in this paper. A neural network was trained by data from simulation of a simple power system under load and fault conditions, tested by data with different system conditions, and finally run for faults along the whole power line. The research was concentrated on creating more selective arcing fault detection, especially for radial distribution lines where arc resistance can be a significant part of the zero sequence impedance. A nonlinear arcing resistance model was used to provide data and a new operating characteristic was devised. The prospective ANN distance relay showed very good performance in detecting a single-line-to-ground fault with nonlinear arcing resistance along the whole transmission line.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"38 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114036349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intelligent approach to coordination identification in distance relaying","authors":"S. J. Lee, Chen-Ching Liu","doi":"10.1109/ISAP.1996.501045","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501045","url":null,"abstract":"Proper coordination of the protective relays is one of the important conditions for power system security. Settings of distance relays usually determined by heuristic rules may not satisfy the coordination requirements. In this paper, the coordination behaviour of the setting rules of the distance relays is investigated. Coordination conditions and properties are derived and the coordination region is introduced. Efficient algorithms to identify the coordination status are presented together with its test results.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134139110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Methods of approximate reasoning for power system equipment condition and reliability analysis","authors":"Kevin Tomsovic, B. Baer","doi":"10.1109/ISAP.1996.501090","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501090","url":null,"abstract":"Traditional power system maintenance and equipment condition monitoring schedules have been based on manufacturer recommended fixed time intervals. Under greater economic pressures, electric utilities have begun: to shift towards reliability centered maintenance or other maintenance programs with longer maintenance intervals; and to load equipment significantly beyond manufacturer ratings. This work focuses on developing an information theoretic framework for systematically assessing equipment condition and incorporating this into maintenance, diagnostic and operational practices. A numerical example highlights the approach.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134552828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Elders, G. Burt, J. McDonald, J. Spiller, D. Brooks, R. Samwell
{"title":"The application of an intelligent system to power network operation and control","authors":"I. Elders, G. Burt, J. McDonald, J. Spiller, D. Brooks, R. Samwell","doi":"10.1109/ISAP.1996.501063","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501063","url":null,"abstract":"Recent major increases in the extent and power of the monitoring and control systems applied to power systems have led to a significant interest in the provision of online support to power network control engineers. Expectations of improved network performance which have resulted from these developments can only be met if the increased volume of data acquired is matched by increased capacity to interpret it. This paper describes the progressive development and implementation of a modular decision support system (DSS) for South Western Electricity (SWEB), UK. The authors describe the modules of the DSS, with particular emphasis on the restoration advisory function and its model of the power network, and a case study is discussed. The benefits of the step-by-step implementation process adopted are outlined.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133528495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparative study of feature extraction techniques for neural network classifier [power system simulation]","authors":"M.B. Zayan, M. A. El-Sharkawi, N. Prasad","doi":"10.1109/ISAP.1996.501106","DOIUrl":"https://doi.org/10.1109/ISAP.1996.501106","url":null,"abstract":"This paper compares two feature extraction techniques for neural network classifiers. The techniques evaluated are used for the dynamic security assessment of power systems. The feature extraction methods are used to map the observation vectors from the measurement space into a lower dimension feature space. The patterns in the feature space can then be utilized to train a neural network (NN) classifier. The NN classifier is used to classify a given power system into either a \"secure\" or \"insecure\" class. The feature vectors not only represent a reduction in dimensionality, but also lead to an improvement in class dispersion, and hence to a better classification. Two feature extraction algorithms, the minimum entropy method and the Karhunen-Loe've expansion, have been studied to examine their intraset clustering and interset class dispersion. A NN pattern classifier system is developed to illustrate the feasibility of classifying any given operating condition into either secure, or insecure class. Security assessment data from two utility power systems are used to test the proposed techniques.","PeriodicalId":153198,"journal":{"name":"Proceedings of International Conference on Intelligent System Application to Power Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134466558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}