A new moderate-random-search strategy (MRPSO) is used for an optimal bidding strategy of a supplier, considering linear bidding curve model with a precise model and emission as constraints, and who delivered electricity to end users in oligopolistic dynamic electricity is studied. Bidding strategy of a supplier is solved by MRPSO, where mean best position ( ) boosts the diversity and the exploration ability of particle. The MRPSO adopts an attractor as the main moving direction of particles, which replaces the velocity update procedure in the particle swarm optimization. The effectiveness of the proposed approach is tested with linear bidding model and the results are compared with the solutions obtained using classical PSO. In this paper, a comparative study has been done by a competitive bidding model tested on IEEE 14- and IEEE 39-bus systems and results motivate the suppliers towards opting green technologies. 1. Introduction In this competitive world, the market is to be said perfect only when the seller and buyer both have competition and are participating equally in the competitive bidding process. In energy market, the generation as well as load side has competition in this competitive electricity market. Recently the electricity markets are in transition phase from single buyer and single seller pattern to multibuyer and multiseller pattern. This type of auction system makes an environment for demanding side entities to compete with their opponents through bidding process; moreover the benefits of retailers depend on their participation in the bidding process so developing the optimal bidding strategies of demanding side is of keen interest in recent researches. In this emerging electricity market, each power supplier can increase its own profit through strategic bidding. The imperfect knowledge of rival suppliers extensively affects the profit of each supplier [1]. In the day-ahead electricity market bids have been submitted to the market operator, who matches generation level of each participant for hourly aggregate supply and decides market clearing prices (MCP). The framing of best optimal bids for supplier with their own costs, technical constraints, and behavior of rival’s and market is known as strategic bidding problem. Lots of work has been done on strategic bidding in competitive electricity market. There are some approaches to frame the strategic bidding problem (SBP) on the basis of their MCP and rival’s bidding behavior [2]. A basic model of optimal bidding has been framed firstly, solved by using dynamic programming based
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