DocumentCode
2626022
Title
Application of ANN and DSM techniques for peak load management a case study
Author
Ravi Babu, P. ; Divya, V. P Sree ; Venkatesh, K. ; Kodad, S.F. ; Ram, B. V Sankar
Author_Institution
EEE Dept., CVR Coll. of Eng., Hyderabad
fYear
2008
fDate
21-25 July 2008
Firstpage
169
Lastpage
174
Abstract
The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. To overcome this problem recently, a concept of demand side management (DSM) has emerged in power system planning and management. The main idea of DSM is to discuss the mutual benefits between supplier and consumer for maximum benefits and minimum inconvenience. The work presented in this paper gives the results of application of neural network and DSM techniques applied to an industrial consumer. The study indicates the improvement in energy efficiency of the system in terms of load factor, in addition the consumer also gets saving or reduction in the energy bill due to lowering of maximum demand (MD).
Keywords
demand side management; neural nets; power engineering computing; power system management; power system planning; demand side management; electrical energy; energy efficiency improvement; energy resources; maximum demand; neural network; peak load management; power system management; power system planning; Elasticity; Electricity supply industry; Energy management; IEEE members; Load management; Load modeling; Power engineering and energy; Power system management; Power system modeling; Shape; DSM: Demand Side Management; DT: Differential Tariff; EUEC: End Use Equipment Control; LPT: Load Priority Technique; MD: Maximum Demand;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Technologies in Electrical and Electronics Engineering, 2008. SIBIRCON 2008. IEEE Region 8 International Conference on
Conference_Location
Novosibirsk
Print_ISBN
978-1-4244-2133-6
Electronic_ISBN
978-1-4244-2134-3
Type
conf
DOI
10.1109/SIBIRCON.2008.4602568
Filename
4602568
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