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Embedding Evolutionary Programming (EP) technique in Particle Swarm Optimization (PSO) algorithm improves the global searching capability of PSO and also prevents the premature convergence in local minima. A number of functional operating constraints, such as branch flow limits and load bus voltage magnitude limits are included as penalties in the fitness function. Numerical results on three test systems namely modified IEEE 14 Bus, IEEE 30 Bus and IEEE 118 Bus systems are presented and the results are compared with PSO and EP approaches in order to demonstrate its performance.<\/p>","DOI":"10.4018\/jsir.2010070104","type":"journal-article","created":{"date-parts":[[2011,2,15]],"date-time":"2011-02-15T20:12:08Z","timestamp":1297800728000},"page":"51-66","source":"Crossref","is-referenced-by-count":5,"title":["Congestion Management Using Hybrid Particle Swarm Optimization Technique"],"prefix":"10.4018","volume":"1","author":[{"given":"Sujatha","family":"Balaraman","sequence":"first","affiliation":[{"name":"Government College of Engineering, India"}]},{"given":"N.","family":"Kamaraj","sequence":"additional","affiliation":[{"name":"Thiagarajar College of Engineering, India"}]}],"member":"2432","reference":[{"key":"jsir.2010070104-0","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2005.846049"},{"key":"jsir.2010070104-1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2002.1007911"},{"key":"jsir.2010070104-2","doi-asserted-by":"publisher","DOI":"10.1109\/5.823997"},{"key":"jsir.2010070104-3","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2005.860910"},{"key":"jsir.2010070104-4","unstructured":"Cuello-Reyna, & Jose, R. 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