Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/306616
Title: Electricity demand modeling using hybrid optimization of genetic algorithm and particle swarm optimization in artificial neural network
Researcher: Atul Anand
Guide(s): Suganthi L
Keywords: Engineering and Technology
Engineering
Engineering Electrical and Electronic
Electric Power Systems
Socio Economic
Artificial Neural Network
University: Anna University
Completed Date: 2019
Abstract: Demand forecasting plays a dominant part in the economic optimization and secure operation of electric power systems long term load forecasting represents the first step in developing future generation transmission and distribution facilities any substantial deviation in the forecast particularly under the new market structure will result in either overbuilding of supply facilities or curtailment of customer demand the confidence levels associated with classical forecasting techniques when applied to forecasting problem in mature and stable utilities are unlikely to be similar to those of dynamic and fast growing utilities this is attributed to the differences in the nature of growth socio economic conditions occurrence of special events extreme climatic conditions and the competition in generation due to the deregulation of the electricity sector with possible changes in tariff structures under such conditions these forecasting techniques are insufficient to establish demand forecast for long term power system planning consequently this case requires separate consideration either by pursuing the search for more improvement in the existing forecasting techniques or establishing another approach to address the forecasting problem of such systems newline
Pagination: xiv, p154
URI: http://hdl.handle.net/10603/306616
Appears in Departments:Faculty of Electrical Engineering

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02_certificates.pdf52.04 kBAdobe PDFView/Open
03_abstracts.pdf57.23 kBAdobe PDFView/Open
04_acknowledgements.pdf42.86 kBAdobe PDFView/Open
05_contents.pdf42.97 kBAdobe PDFView/Open
06_list_of_tables .pdf50.27 kBAdobe PDFView/Open
07_list_of_figures.pdf37.13 kBAdobe PDFView/Open
08_list_of_abbreviations.pdf63.32 kBAdobe PDFView/Open
09_chapter1.pdf117.19 kBAdobe PDFView/Open
10_chapter2.pdf231.87 kBAdobe PDFView/Open
11_chapter3.pdf388.83 kBAdobe PDFView/Open
12_chapter4.pdf154.13 kBAdobe PDFView/Open
13_chapter5.pdf1.43 MBAdobe PDFView/Open
14_chpater6.pdf376.05 kBAdobe PDFView/Open
15_chapter7.pdf123.93 kBAdobe PDFView/Open
16_conclusion.pdf52.25 kBAdobe PDFView/Open
17_references.pdf105.84 kBAdobe PDFView/Open
18_list_of_publications.pdf43.01 kBAdobe PDFView/Open
80_recommendation.pdf80.09 kBAdobe PDFView/Open


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