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dc.contributor.authorSalkuti, Surender Reddy
dc.date.accessioned2018-09-04T07:00:36Z
dc.date.available2018-09-04T07:00:36Z
dc.date.issued2017
dc.identifier.citationAdvances in electrical and electronic engineering. 2017, vol. 15, no. 5, p. 713-723 : ill.cs
dc.identifier.issn1336-1376
dc.identifier.issn1804-3119
dc.identifier.urihttp://hdl.handle.net/10084/131471
dc.description.abstractThis paper presents the Congestion Management (CM) methodologies and how they get modified in the new competitive framework of electricity power markets. When the load on the system is increased or when some contingency occurs in the system, some of the lines may become overloaded. Thus, the loadability of the system should be increased by generating and dispatching the power optimally for the secure operation of power system. In this paper, the CM problem is solved by using the optimal rescheduling of generating units and load demands, and the Swarm intelligent techniques are used to handle this problem. Here, the CM problem is solved by using the Particle Swarm Optimization (PSO), Fitness Distance Ratio PSO (FDRPSO) and Fuzzy Adaptive-PSO (FA-PSO). First, the generating units are selected based on sensitivity to the over-loaded transmission line, and then these generators are rescheduled to remove the congestion in the transmission line. This paper also utilizes the demand response offers to solve the CM problem. The effectiveness of the proposed CM methodology is examined on the IEEE 30 bus and Indian 75 bus test systems.cs
dc.format.extent1320210 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherVysoká škola báňská - Technická univerzita Ostravacs
dc.relation.ispartofseriesAdvances in electrical and electronic engineeringcs
dc.relation.urihttp://dx.doi.org/ 10.15598/aeee.v15i5.2258cs
dc.rights© Vysoká škola báňská - Technická univerzita Ostrava
dc.rightsAttribution-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectcongestion managementcs
dc.subjectdemand response offerscs
dc.subjectGeneration reschedulingcs
dc.subjectmeta-heuristic algorithmscs
dc.subjectSwarm intelligent algorithmscs
dc.titleCongestion Management Based on Optimal Rescheduling of Generators and Load Demands Using Swarm Intelligent Techniquescs
dc.typearticlecs
dc.identifier.doi10.15598/aeee.v15i5.2258
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs


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