A Prediction Based Bidding Strategy for Social Welfare Improvement in Uniform Pricing Mechanism

Authors

  • G. V. Rajasekhar Department of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India
  • P. Surekha Department of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India

DOI:

https://doi.org/10.13052/dgaej2156-3306.3753

Abstract

In the new competitive electricity market, bidding plays a significant role in the area of power trading. The participants are partaking in the trading procedure for a fixed amount of power. The price at which a single buyer bids a block of power influences both the net volume of power cleared and the market-clearing price of electricity traded in the entire network. In this paper, different bidding strategies are defined and simulated. The defined strategies show the dependency on the bid price for clearing a bid. The net earnings of the buyers and sellers depend on the bid price. The selection of bid price for each block of power is studied such that the total volume of power cleared is equal to the participating buyers’ total power demand. The study focuses on determining the optimal bid to result in maximum societal benefit. In addition to the bid price effect on the volume of power cleared, the bid price prediction is also performed in this work using linear regression. The predicted Locational Marginal Price (LMP) of the buyers for different volumes of power cleared is estimated. The results are further compared with LMP obtained using an ordinary load flow problem through which a margin change in the net earnings is observed. An IEEE-30 bus system is simulated with different bidding strategies using MATLAB, and the predicted LMP shows a significant increase in net earnings.

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Author Biographies

G. V. Rajasekhar, Department of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India

G. V. Rajasekhar currently serves as Assistant professor at RGUKT-Ongole campus in EEE department. He received B.Tech from JNT university Hyderabad and M.tech from JNT university Kakinada. He is now pursuing Ph.D at School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru. His research area includes power system trading and optimization.

P. Surekha, Department of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India

P. Surekha currently serves as an Assistant Professor (Sr. Gr.) in the department of Electrical and Electronics Engineering, School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru. She has received her B. E. Degree in Electrical and Electronics Engineering from Bharathiar University, Coimbatore in 2001, Master Degree in Control Systems from PSG College of Technology, Coimbatore in 2006, and Ph. D. in Bio-Inspired algorithms for Optimization from Anna University in 2014. Her research areas include Virtual Instrumentation, Image Processing, Robotics, Machine Learning, and Computational Intelligence.

References

Sawai, Kazunori, and Tetsuo Sasaki. “Simulation on Bidding Strategy at Day-Ahead Market.” Journal of Industrial Engineering 2014 (2014).

Malik, Payal. Design of power markets: Different market structures and options for India. No. 95.

Central Electricity Regulatory Commission. “Formulating Pricing Methodology for Inter-State Transmission in India.” [Online]. (http://www.cercind.gov.in) (2009).

Indian Electricity Exchange [Online]: Available: http://iexindia.com

Vijaya kumar J., Shaik Jameer Pasha, kumar DM vinod. “Congestion influence on optimal bidding in a competitive electricity market using particle swarm optimization.” (2011): 34–39.

Kumar, J. Vijaya, and DM Vinod Kumar. “Optimal bidding strategy in an open electricity market using a genetic algorithm.” Int. J. Adv. Soft Comput. Appl 3, no. 1 (2011): 54–67.

G.V. Rajasekhar and Surekha P, “A study on congestion effect on the locational market price for-profit market strategies,” Second International Conference on Advances in Electrical and Computer Technologies. ICAECT 2020, Lecture Notes in Electrical Engineering, Springer series, volume 711, 2020.

Arya, Shri Shubham. “Central electricity regulatory commission New Delhi.” (2019).

Ajay Talegaonkar and Ravinder, “Tariff-based bidding process for transmission: The first Indian experience,” Fifteenth National Power Systems Conference (NPSC), IIT Bombay, December 2008, pp. 266–270.

V. S., Dr. Bhagavathi Sivakumar P., and Anantha Narayanan V., “Efficient Real-Time Decision Making Using Streaming Data Analytics in IoT Environment,” International Conference on Advanced Computing Networking and Informatics. Advances in Intelligent Systems and Computing, vol. 870. Singapore, pp. 165–173, 2019.

R. Subramani and Vijayalakshmi, C., “Implementation of Optimal Scheduling Model for Power Flow System,” International Journal of Computer-Aided Engineering and Technology, vol. 11, no. 2, pp. 151–162, 2019.

P. Kiran, Dr. Vijaya Chandrakala K. R. M., and Nambiar, T. N. P., “Day-ahead market operation with agent-based modeling” 2017 International Conference on Technological Advancements in Power and Energy (TAP Energy), 2017.

K. Kiranvishnu, Dr. J. Ramprabhakar, and K. Sireesha, “Comparative study of wind speed forecasting techniques,” in 2016 – Biennial International Conference on Power and Energy Systems: Towards Sustainable Energy, PESTSE-2016, 2016.

S. Jayachandran and. P, S., “Precise Frequency Estimation in Power System Network”, International Conference on Advances in Engineering Technology and Management. Madurai, pp. 131–134, 2014.

V. V. Chithra, Menon, R., Sridharan, A., Thomas, J. Mariam, Gutjahr, G., and Prof. Prema Nedungadi, “Regression analysis of character values for life-long learning”, AIP Conference Proceedings, vol. 2336, p. 040006, 2021.

Mohammad Ebrahim Hajiabadi, Mahdi Samadi, “Locational marginal price share: a new structural market power index”. J. Mod. Power Syst. Clean Energy (2019).

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Published

2022-05-25

How to Cite

Rajasekhar, G. V. ., & Surekha, P. . (2022). A Prediction Based Bidding Strategy for Social Welfare Improvement in Uniform Pricing Mechanism. Distributed Generation &Amp; Alternative Energy Journal, 37(05), 1349–1370. https://doi.org/10.13052/dgaej2156-3306.3753

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