Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
Deregulation and restructuring of electric power industry is occurring in many parts of the world. It is aimed at introducing competition in the supply and retail side of the industry, while maintaining control over the transmission lines. Tracing methodology hence had been introduced to overcome p...
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| Format: | Citation Index Journal |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/4715/1/3._American_Journal_SIR-1-3-463-471.pdf http://eprints.utp.edu.my/4715/ |
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| Institution: | Universiti Teknologi Petronas |
| Summary: | Deregulation and restructuring of electric power industry is occurring in many parts of the world. It is aimed at introducing competition in the supply and retail side of the industry, while maintaining control over the transmission lines. Tracing methodology hence had been introduced to overcome problems related to the Marginal pricing of transmission costs. This paper first analyses of the proportional method which leads to a redefined power tracing method, and then further refines the proposed prediction method by establishing trends of the learning coefficients, using them to examine the relationship between accuracy and number of samples taken. Response of individual generators to change in demand and the corresponding associated losses are also presented. MATLAB with matpower4.0b extension was used to present the study on the IEEE 24bus RTS. |
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