Metaphor-less Rao-3 and artificial neural network with parallel computing-based wheeling pricing in competitive power market

Abstract

Fast and accurate wheeling pricing has emerged as an important issue in the recent competitive power market. Embedded cost-based wheeling pricing is well accepted by power market, because it is based on actual flow of power wheeled by them. It also recovers fully the fixed cost of wheeling facility installation and operation. In this article, metaphor-less Rao-3-based ACOPF, MVA-mile method and Bialek tracing has been employed to compute wheeling prices across various generators and loads. In actual power market due to continuously varying load conditions, the computation of wheeling prices is quite a time taking process. Because for computing wheeling prices, the optimal power flow (OPF) program has to be run each time for every loading condition. In this scenario, the artificial neural network (ANN) approach has been found to be very useful, to estimate wheeling prices instantly and accurately for any unseen loading scenario. Here, a number of ANNs have been developed under parallel computing environment. This article presents a metaphor-less Rao-3-based approach to project wheeling prices in the competitive power market by developing a new radial basis function neural network (RBFNN). The present work of wheeling pricing has been demonstrated and examined on IEEE 30-bus system.

Keywords:

• Bialek tracing
• radial basis function neural network (RBFNN)
• MVA-mile method
• parallel computing
• wheeling pricing
• metaphor-Less rao-3 algorithm

Reviewing Editor:

• Qingsong Ai, Senior Editor, Wuhan University of Technology, CHINA

Subjects:

• Technology
• Engineering & Technology
• Electrical & Electronic Engineering
• Engineering Economics
• Industrial Engineering & Manufacturing

Acknowledgment

The authors sincerely acknowledge the Director, MITS, Gwalior, India, Deputy Director (Legal Metrology), Regional Reference Standard Laboratory, Ahmedabad (RRSL), Director, M/s GSL Technology and Services, Kiran Garden, Uttam Nagar, New Delhi, Principal, BRA Polytechnic College, Gwalior and Management ITM University, Gwalior, for providing facilities to carry out research work.

Disclosure statement

The authors declare that they have no competing interests.

Availability of data and material

The datasets generated and/or analyzed during the current study are not publicly available due [confidential] but are available from the corresponding author on reasonable request.

Additional information

Notes on contributors

Abhishek Saxena

Abhishek Saxena received the B.E. degree in electrical engineering from Maharana Pratap College of Technology, Gwalior and the M.E. degree in industrial system and drives from Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India, in 2006 and 2009, respectively.

Seema N. Pandey

Dr. Seema N. Pandey received the B.E. degree in electrical engineering and the M.E. degree in power systems from the Madhav Institute of Tech- nology and Science, Gwalior, India, in 1998 and 2003, respectively, and the Ph.D. degree from ABVIIITM, Gwalior, in 2010.

Shishir Dixit

Dr. Shishir Dixit, Associate Professor, teaches at the Madhav Institute of Technology & Science in Gwalior. As of July 2003, he was a Lecturer at MITS. He received his Master's in Design and Production of H.E.E. from MANIT, Bhopal in 2003, his Ph.D. in Electrical Engineering Stream from Maulana Azad National Institute of Technology, Bhopal in 2014.