4.6 Article

Bacteria Foraging Optimization Based Bidding Strategy Under Transmission Congestion

Journal

IEEE SYSTEMS JOURNAL
Volume 9, Issue 1, Pages 141-151

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2013.2258229

Keywords

Bacteria foraging optimization (BFO) algorithm; bi-level optimization problem; congestion management; Monte Carlo simulation (MCS); optimal bidding strategy

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This paper presents a methodology for an optimal bidding strategy of a supplier considering congestion influence and rivals' bidding behavior. Market splitting methodology, which is being used in Nord Pool as well as in the Indian electricity market, has been utilized to manage the congestion. Monte Carlo simulation (MCS) has been used to predict the bidding behavior of the rivals. In this paper, a bi-level optimization problem has been proposed to obtain the optimal bidding strategy of a supplier considering double-sided bidding. Lower level problem represents the market clearing process of the system operator (SO) and the upper level optimization problem represents the supplier's profit maximization function, which is a non-linear function. Bacteria foraging optimization (BFO) algorithm, a modern heuristic approach, has been used to obtain the global solution of the proposed bi-level optimization problem. The effectiveness of the proposed in method has been tested on a five-bus system and modified IEEE-30 bus system. Results obtained using the BFO algorithm have been compared with those obtained using a genetic algorithm (GA) based approach.

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