Book ChapterDOI
Prediction of Market Power Using SVM as Regressor Under Deregulated Electricity Market
K. Shafeeque Ahmed,Fini Fathima,Ramesh Ananthavijayan,Prabhakar Karthikeyan Shanmugam,Sarat Kumar Sahoo,Rani Chinnappa Naidu +5 more
- pp 605-617
TLDR
In this paper, the effectiveness of SVM technique in predicting market power is formulated and linear and nonlinear kernels are compared.Abstract:
This paper proposes a methodology to utilize support vector machines (SVM) as a regressor tool for predicting market power. Both the companies, i.e., Generation (Gencos) and the Distribution (Discos), can utilize this tool to forecast market power on their perspective. Attributes and criterion are to be chosen properly to classify market power. In this paper, the effectiveness of SVM technique in predicting market power is formulated. Independent system operator (ISO) can also use this tool as regressor and it is discussed elaborately. Both linear and nonlinear kernels are compared. Nodal must run share (NMRS) is used as an index for predicting market power. A sample of three-bus system consisting of two generators and one load/two loads is used to illustrate the study.read more
References
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Book
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
TL;DR: This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory, and will guide practitioners to updated literature, new applications, and on-line software.
Journal ArticleDOI
An effective Power Quality classifier using Wavelet Transform and Support Vector Machines
TL;DR: A novel method based on a combination of binary classifiers which are optimized for those special cases where the real signals contain a multitude of events within the analyzed temporal window, and can be implemented with low computational cost.
Journal ArticleDOI
A review on market power in deregulated electricity market
TL;DR: A comprehensive review on market power with various indices which were used in market power analysis and the evolution of research and development in the field of market power is presented in this paper, where the literature work presented in this paper has been divided into various sections to facilitate the upcoming researchers who carry out their research in the area of Market power under various environments.
Journal ArticleDOI
Genetic algorithm based support vector machine for on-line voltage stability monitoring
TL;DR: In this article, a GA-SVM approach for online monitoring of long-term voltage instability has been proposed, which uses the voltage magnitude and phase angle obtained from Phasor Measurement Units (PMUs) as the input vectors to SVM and the output vector is the voltage Stability Margin Index (VSMI).
Journal ArticleDOI
Nodal market power assessment in electricity markets
Peng Wang,Yu Xiao,Yi Ding +2 more
TL;DR: In this paper, the impact of load variation, the size of a power supplier and random failures on market power has been investigated, and the geographic difference of market power caused by network constraints has been considered.
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