Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/10316
Title: Available transfer capability estimation and enhancement in deregulated power systems using intelligent systems
Researcher: Vaithilingam C
Guide(s): Kumudini Devi, R.P.
Keywords: Power systems, intelligent systems, Transaction index, Independent System Operator, Available Transfer Capability, generalized regression neural network, back propagation algorithm, fuzzy logic
Upload Date: 5-Aug-2013
University: Anna University
Completed Date: 2010
Abstract: In recent years the vertically integrated power system around the world is experiencing restructuring process. Horizontally distributed deregulated power system emerging successfully where, the generation and distribution of power are being carried out by many entities enabling healthy competition. The competition might result in quality power and different service standards to the customers. All the details about the proposed transactions are conveyed to Independent System Operator (ISO). After considering the system operating conditions the ISO will estimate the feasibility of the proposed transactions. The Gencos can accept transaction only if ISO finds it as feasible after various analysis. The Available Transfer Capability (ATC) is defined as the additional power that can be transmitted through a specified interface over and above the already committed transactions. The Generalized Regression Neural Network (GRNN), SVM, Back Propagation Algorithm (BPA) and Fuzzy logic are used to develop ATC estimators. The effectiveness of the GRNN, SVM, BPA and Fuzzy logic ATC estimators are tested on IEEE 24 bus RTS and IEEE 118 bus systems and the estimated results are compared with that of RPF results. This thesis analyses the technical feasibility of ATC estimation using Existing Transmission Commitments (ETC). This thesis aims at choosing an operator friendly index which reflects the effect of outage conditions on ATC. Therefore, in this thesis transaction index is used to reflect the impact of outage on ATC. The feasibility of the proposed AI model is tested on IEEE 24 RTS and IEEE 118 systems. The proposed method is applied on IEEE 24 bus RTS and IEEE 118 bus systems and results are discussed. The limitation due to the bus voltage limits can be solved by reactive power injections at the weak buses. A method is proposed based on SVM to estimate the degree of series and shunt compensation needed to obtain the desired ATC value of a given operating condition. The results are presented for IEEE 24 bus RTS system.
Pagination: xx, 169
URI: http://hdl.handle.net/10603/10316
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File49.51 kBAdobe PDFView/Open
02_certficates.pdf986.47 kBAdobe PDFView/Open
03_abstract.pdf18.59 kBAdobe PDFView/Open
04_acknowledgement.pdf14.45 kBAdobe PDFView/Open
05_contents.pdf46.85 kBAdobe PDFView/Open
06_chapter 1.pdf73.93 kBAdobe PDFView/Open
07_chapter 2.pdf146.83 kBAdobe PDFView/Open
08_chapter 3.pdf118.79 kBAdobe PDFView/Open
09_chapter 4.pdf71.97 kBAdobe PDFView/Open
10_chapter 5.pdf62.12 kBAdobe PDFView/Open
11_chapter 6.pdf85.19 kBAdobe PDFView/Open
12_chapter 7.pdf96.17 kBAdobe PDFView/Open
13_chapter 8.pdf28.4 kBAdobe PDFView/Open
14_appendices 1 to 4.pdf217.73 kBAdobe PDFView/Open
15_references.pdf32.58 kBAdobe PDFView/Open
16_publications.pdf16.6 kBAdobe PDFView/Open
17_vitae.pdf10.81 kBAdobe PDFView/Open
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