Pub Date : 2007-12-01DOI: 10.1049/IET-SMT:20070064
D. Thrimawithana, U. Madawala
A semi-analytical technique to study the propagation characteristics of high voltage (HV) transient pulses along multi wire electric fences is presented in this paper. The technique models the multi-line fence as a frequency domain function, composed of matrices and vectors, to facilitate an analytical solution for propagation of HV pulses along the fence. The modal transformation is used to decouple the frequency domain function, which is then solved and transformed into time domain through a numerical Laplace inversion algorithm to determine the propagation characteristics of the fence at a given location and time. For various line conditions, the propagation of HV pulses is investigated, and the results are presented with comparisons to simulations by power systems computer aided design (PSCAD) to show the validity of theoretical analysis. The technique provides an accurate insight into the propagation characteristics of HV pulses along multi wire fence lines and thus is an invaluable tool at the design phase of electric fence energizers.
{"title":"Pulse propagation along multi wire electric fences","authors":"D. Thrimawithana, U. Madawala","doi":"10.1049/IET-SMT:20070064","DOIUrl":"https://doi.org/10.1049/IET-SMT:20070064","url":null,"abstract":"A semi-analytical technique to study the propagation characteristics of high voltage (HV) transient pulses along multi wire electric fences is presented in this paper. The technique models the multi-line fence as a frequency domain function, composed of matrices and vectors, to facilitate an analytical solution for propagation of HV pulses along the fence. The modal transformation is used to decouple the frequency domain function, which is then solved and transformed into time domain through a numerical Laplace inversion algorithm to determine the propagation characteristics of the fence at a given location and time. For various line conditions, the propagation of HV pulses is investigated, and the results are presented with comparisons to simulations by power systems computer aided design (PSCAD) to show the validity of theoretical analysis. The technique provides an accurate insight into the propagation characteristics of HV pulses along multi wire fence lines and thus is an invaluable tool at the design phase of electric fence energizers.","PeriodicalId":206953,"journal":{"name":"2007 International Power Engineering Conference (IPEC 2007)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128458437","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}
R. Bharathi, M.J. Kumar, D. Sunitha, S. Premalatha
This paper presents an evolutionary computation (EC) method called genetic algorithm (GA) and a metaheuristic algorithm called ant colony search algorithm (ACSA) to solve the combined economic and emission dispatch (EED) problem with transmission losses. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. A real coded GA has been implemented to minimize both the dispatch cost as well as emission while satisfying all the equality and inequality constraints. ACSA is also developed to provide a means of comparison and it is a new cooperative agents approach, which is inspired by the observation of the behaviors of real ant colonies on the topic of ant trail formation and foraging methods. In the ACSA, a set of cooperating agents called "ants" cooperates to find a good solution for economic dispatch problem. The merits of ACSA are parallel search and optimization capabilities. The feasibility of the proposed method is tested on a power system network and the experimental results of both GA and ACSA are compared with the solutions of conventional Lamda iteration method.
{"title":"Optimization of combined economic and emission dispatch problem — A comparative study","authors":"R. Bharathi, M.J. Kumar, D. Sunitha, S. Premalatha","doi":"10.9790/1676-0263743","DOIUrl":"https://doi.org/10.9790/1676-0263743","url":null,"abstract":"This paper presents an evolutionary computation (EC) method called genetic algorithm (GA) and a metaheuristic algorithm called ant colony search algorithm (ACSA) to solve the combined economic and emission dispatch (EED) problem with transmission losses. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. A real coded GA has been implemented to minimize both the dispatch cost as well as emission while satisfying all the equality and inequality constraints. ACSA is also developed to provide a means of comparison and it is a new cooperative agents approach, which is inspired by the observation of the behaviors of real ant colonies on the topic of ant trail formation and foraging methods. In the ACSA, a set of cooperating agents called \"ants\" cooperates to find a good solution for economic dispatch problem. The merits of ACSA are parallel search and optimization capabilities. The feasibility of the proposed method is tested on a power system network and the experimental results of both GA and ACSA are compared with the solutions of conventional Lamda iteration method.","PeriodicalId":206953,"journal":{"name":"2007 International Power Engineering Conference (IPEC 2007)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131723301","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}
A. Seifi, M. Hesamzadeh, N. Hosseinzadeh, P. Wolfs
This work presents a new algorithm based on a combination of fuzzy (FUZ), dynamic programming (DP), and genetic algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.
{"title":"Application of a new hybrid optimization method for optimum distribution capacitor planning","authors":"A. Seifi, M. Hesamzadeh, N. Hosseinzadeh, P. Wolfs","doi":"10.5539/MAS.V3N4P196","DOIUrl":"https://doi.org/10.5539/MAS.V3N4P196","url":null,"abstract":"This work presents a new algorithm based on a combination of fuzzy (FUZ), dynamic programming (DP), and genetic algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.","PeriodicalId":206953,"journal":{"name":"2007 International Power Engineering Conference (IPEC 2007)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122106359","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}
Pub Date : 2007-09-19DOI: 10.1080/15325000701426096
R. Bansal, T. Bhatti, V. Kumar
This paper presents an artificial neural network (ANN) based approach to tune the parameters of the SVC reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based reactive power controller are optimised for typical values of the load voltage characteristics by conventional techniques. Using the generated data, the method of multilayer feed-forward ANN with the error back-propagation training is employed. An ANN tuned static var compensator (SVC) controller has been applied to control the reactive power of variable slip/speed model of isolated wind-diesel hybrid power system. Transient responses of sample hybrid power system have also been presented.
{"title":"Reactive power control of autonomous wind-diesel hybrid power systems using ANN","authors":"R. Bansal, T. Bhatti, V. Kumar","doi":"10.1080/15325000701426096","DOIUrl":"https://doi.org/10.1080/15325000701426096","url":null,"abstract":"This paper presents an artificial neural network (ANN) based approach to tune the parameters of the SVC reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based reactive power controller are optimised for typical values of the load voltage characteristics by conventional techniques. Using the generated data, the method of multilayer feed-forward ANN with the error back-propagation training is employed. An ANN tuned static var compensator (SVC) controller has been applied to control the reactive power of variable slip/speed model of isolated wind-diesel hybrid power system. Transient responses of sample hybrid power system have also been presented.","PeriodicalId":206953,"journal":{"name":"2007 International Power Engineering Conference (IPEC 2007)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130124702","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}
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