Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/17033
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKaur S.-
dc.contributor.authorKaur M.-
dc.contributor.authorKumbhar, Ganesh Balu-
dc.contributor.authorKhanna R.-
dc.date.accessioned2020-12-02T14:28:50Z-
dc.date.available2020-12-02T14:28:50Z-
dc.date.issued2017-
dc.identifier.citationProceedings of 2017 IEEE International Conference on Smart Grid and Smart Cities, ICSGSC 2017, (2017), 89- 93-
dc.identifier.isbn9.78154E+12-
dc.identifier.urihttps://doi.org/10.1109/ICSGSC.2017.8038555-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/17033-
dc.description.abstractThe greatest challenge for power utilities is to meet exponentially increasing energy demand subjected to the constraints of sustainable development with clean energy apart from economic viability. Renewable DGs, in spite of high investment cost and intermittent generation, are compulsive choice for environment friendly planning and sustainable growth. Clean energy DG technologies can provide solution to ever increasing power demand in sustainable and cost effective manner by adopting appropriate incentive mechanism. Clean energy technologies can also be encouraged by penalizing the conventional resources for harmful emissions. The proposed method minimizes the annual cost by maximizing the emission reduction and carbon credit revenue. The proposed formulation yields solution in terms of type, optimal size and location while fulfilling the criterion in terms of economic, technical or techno-economic. The objective function comprises of energy purchase, losses, capital, operational and GHG emission costs. Importance of each objective is mapped with optimal weight allocation, thereby maintaining the consistency among all objectives. A hybrid optimization technique based on Harmony Search integrated with Teaching-Learning is used to enhance the search process. The merit of the proposed algorithm is dynamic tuning of control parameters which enhances the convergence property of the solution algorithm. Results indicate that renewable DG technologies can become financially viable with appropriate price mechanism depending on planner's objective. © 2017 IEEE.-
dc.language.isoen_US-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.ispartofProceedings of 2017 IEEE International Conference on Smart Grid and Smart Cities, ICSGSC 2017-
dc.subjectClean energy planning-
dc.subjectDistributed generation-
dc.subjectHarmony search Teaching-learning Optimization-
dc.titleA hybrid approach for promoting low carbon technologies in distributed generation planning-
dc.typeConference Paper-
dc.scopusid55371065000-
dc.scopusid57213886624-
dc.scopusid13204991600-
dc.scopusid7202996700-
dc.affiliationKaur, S., Electrical Engineering Department, PEC University of Technology, Chandigarh, India-
dc.affiliationKaur, M., Electronics and Comm. Department, Delhi Technological University, Delhi, India-
dc.affiliationKumbhar, G., Electrical Engineering Department, Indian Institute of Technology, Roorkee, India-
dc.affiliationKhanna, R., Electrical Engineering Department, PEC University of Technology, Chandigarh, India-
dc.identifier.conferencedetails2017 IEEE International Conference on Smart Grid and Smart Cities, ICSGSC 2017, 23-26 July 2017-
Appears in Collections:Conference Publications [EE]

Files in This Item:
There are no files associated with this item.
Show simple item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.