Coordinated Bidding Strategy of a Supplier in Day-Ahead and Balancing Energy Market

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Published Oct 1, 2011
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Volume 7, Issue 2, September 2011

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A. K. Jain
Department of Electrical Engineering, Indian Institute of Technology, Kanpur–208016
S. C. Srivastava
Department of Electrical Engineering, Indian Institute of Technology, Kanpur–208016
S. N. Singh
Department of Electrical Engineering, Indian Institute of Technology, Kanpur–208016
L. Srivastava
Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior–474005

Abstract

This paper presents a methodology to develop an optimal coordinated bidding strategy of a supplier in Day-Ahead Energy Market (DAEM) and Balancing Energy Market (BEM). It is assumed that each supplier bids hourly price-volume bid in DAEM and BEM (for up regulation and down regulation) for 24 hours. In this work, a bi-level optimization problem has been proposed to obtain the optimally coordinated bidding strategy of a supplier, considering rivals’ bidding behavior, inter temporal constraints, and multi period auction. Lower level problem represents the market clearing process of System Operator (SO), in which DAEM and BEM are cleared separately and sequentially for all the 24 hours. Upper level problem represents the supplier’s profi t maximization function, which is non linear. Therefore, Artifi cial Bee Colony (ABC) algorithm, a modern heuristic approach, has been used to obtain the best solution of the proposed bi-level optimization problem. The effectiveness of proposed method has been tested on modifi ed IEEE-30 bus system. Results obtained using the ABC algorithm has been compared with those obtained using a Genetic Algorithm (GA) based approach. To illustrate the effect of coordinated bidding strategy on supplier’s profi t, results of the coordinated bidding strategy have been compared with those obtained by uncoordinated bidding strategy.

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How to Cite
Jain, A. K., Srivastava, S. C., Singh, S. N., & Srivastava, L. (2011). Coordinated Bidding Strategy of a Supplier in Day-Ahead and Balancing Energy Market. Power Research - A Journal of CPRI, 223–234. Retrieved from https://node6473.myfcloud.com/~geosocin/CPRI/index.php/pr/article/view/944

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