NDLI: Optimal bidding strategy with the inclusion of wind power supplier in an emerging power market

Content Provider	IET Digital Library
Author	Singh, Satyendra Fozdar, Manoj
Abstract	In polistic electricity market structure, each power producers can maximise its profit through bidding strategy. Also, with the advent of renewable generation mostly wind has shaped a new prospect in the bidding process. Although, the wind power output uncertainty, wind power suppliers facing an inevitable uncertainty problem in an emerging power market. To alleviate the adverse impact of this uncertainty on wind power bidding, Weibull distribution is used to model wind power scenarios and the forward-reduction algorithm is utilised to reduce scenarios. Furthermore, an overestimation and underestimation cost function is modelled to measure the deviation of wind power output. The bidding strategy with the inclusion of wind power is proposed in this study to maximise profit. However, the uncertainty of rival's behaviour affects the bidding process, which minimised by utilising the normal probability distribution function. The proposed problem is tested on the IEEE standard 30-bus and 57-bus systems and solved by the gravitational search algorithm (GSA). The results are obtained without and with wind power and shows that the effects of wind power on market clearing price and bidding strategy. Moreover, GSA gives higher market clearing price and net profit as compared with particle swarm optimisation and genetic algorithm.
Starting Page	1914
Ending Page	1922
Page Count	9
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 10, May (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2019.0118
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-03-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bidding Process Emerging Power Market Genetic Algorithm IEEE Standards Inevitable Uncertainty Problem Optimal Bidding Strategy Optimisation Optimisation Technique Particle Swarm Optimisation Polistic Electricity Market Structure Power Generation Economics Power Market Power Producers Power System Economics Power System Managemen Power System Operation Pricing Probability Search Problem Statistics Weibull Distribution Wind Power Bidding Wind Power Output Uncertainty Wind Power Plant Wind Power Scenario Wind Power Supplier
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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