Optimal Bidding Strategies in A Restructured Competitive Electric Power Market Adopting LUS-FFA Method
Ramachandra Agrawal1, Sabita Tripathy2, Smita Nayak3, Vipin Gupta4, Manoj Kumar Debnath5
1Ramachandra Agrawal, Department of Electrical Engineering, Siksha ”O” Anusandhan Deemed to be University, Bhubaneswar (Odisha), India.
2Sabita Tripathy, Department of Electrical Engineering, Siksha ”O” Anusandhan Deemed to be University, Bhubaneswar (Odisha), India.
3Smita Nayak, Department of Electrical Engineering, Siksha ”O” Anusandhan Deemed to be University, Bhubaneswar (Odisha), India.
4Vipin Gupta, Department of Electrical Engineering, Siksha ”O” Anusandhan Deemed to be University, Bhubaneswar (Odisha), India.
5Manoj Kumar Debnath, Department of Electrical Engineering, Siksha ”O” Anusandhan Deemed to be University, Bhubaneswar (Odisha), India.
Manuscript received on 26 May 2019 | Revised Manuscript received on 13 June 2019 | Manuscript Published on 26 June 2019 | PP: 272-280 | Volume-8 Issue-1S5 June 2019 | Retrieval Number: A00480681S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: At present, the generating firms throughout the world experience the critical problem of maximizing their own benefit under the constraint of social surplus issues. Strategic bidding can be adopted while trading power to the market controller. The electricity market has become extra competitive after deregulation having an advance market flexibility to be recognized and implemented by the participators for individual gains that is the strategy to bid. An optimization method Local Unimodal Sampling Fire-Fly algorithm (LUS-FFA) is considered to bid within the strategic limits in competitive electric power market by the power supplying and consuming participators ruling the MCP while rest of the power customers are in the aggregate load form. To win its share during the trading hour in the auction process of the market each participator bids against the opponents competing. For profit maximization, winning the auction in the hourly competitive power market to retail partially or entirely the total power demanded of a specific hour is of vital importance. The proposed optimization techniques is adopted to find the bidding strategies in modern dynamic electric power market along with the power producing firms and bulk power consuming customers. Each rival will estimate the bid parameters out of the previous market data. The consequence of the implementation of LUS_FFA technique evidenced higher gross profit over other earlier used ways when tested on IEEE-30 bus power network incorporating 6 Power producing firms and 2 bulk power consumers. A new participant’s entry effect on the present market bidding behavior has also been discussed in this work. A dynamic trading day ahead market with the criteria of ramp extreme for each participator is presented thereby depicting a practical market. Additionally, the Market Clearing Price (MCP) variations are also in the pre-specified limits at every instant of the day along trading duration. Superiority was noticed throughout with the application of the LUS_FFA method irrespective of a static or dynamic market.
Keywords: IPP; CEPM; MCP; DPM; PSO; FFA; LUS; LUS-FFA.
Scope of the Article: Low-power design