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|Title:||Generation scheduling for a price taker genco in competitive power markets||Authors:||Qiao, Song Bo||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries||Issue Date:||2008||Abstract:||The electric power industry in the last decades has evolved from a centralized operational approach to a deregulated one. Many participants and service providers have ma de up the new structure of the power market where the competition is increasing. As the new deregulating framework is imperfect, it is quite important for the market participants to develop optimal bidding strategies which are vital to their benefits in maximizing profits and minimizing the cost. The purpose of this project is to investigate the price behavior of Singapore power market and utilize the historical price data to devise appropriate bidding strategies in order to recover the costs and maximize the profits. As this being a dynamic process, comprehensive literature review was required to have a firm foundation prior to detailed analysis. Analysis was done with the help of data manipulations, statistical analysis and graphical analysis using Matlab Statistic Tool Box and Microsoft Excel. The electricity price of the Singapore market in each period is investigated and found to conform to a lognormal distribution through detailed hypothesis testing. With this effective model for the price behavior, a three-step bidding method is devised based on the screening curves of the generation plants. The tested Genco comprises of one stream-coal unit, one steam-oil unit and one steam-gas unit. The bid status which is determine by a comparison between the outcome using the bid price and the real market electricity price will be used to decide which unit should be committed to operate. Subsequently, the revenue, investment cost, O&M cost, and running cost can be calculated and the result shows it is available to make profits with the proposed work.||URI:||http://hdl.handle.net/10356/18881||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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Updated on Nov 25, 2020
Updated on Nov 25, 2020
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