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Security Pricing Methodology In The Deregulated Electricity Markets

Posted on:2007-07-18Degree:MasterType:Thesis
Country:ChinaCandidate:J Y LiFull Text:PDF
GTID:2189360185987477Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
The power industry in china is now under the way of market reforming. In the new electricity market environments, the conflict between power system security and economical operation is more and more serious . In contrast to monopoly environments, the operation modes of power system and behaviors of each participant in market environments is considerably different, the security operation of power system is facing an unprecedented challenge. Hence, how to develop effective strategies to secure of power system operations has become a major research topic. This dissertation focuses on the study of security strategies and security pricing in the electricity market environments, and obtains some beneficial results.As an auxiliary service method in the deregulated electricity market, a security pricing method is proposed in this paper to solve the problem of security operation of power system in the context of decreasing security region. This is an "economic" method. It can effectively takes account of the benefit of each participant in the market and provide a decision-making method for electric power fair dispatching center. Furthermore, it can also lead the long term capital investment in the electricity market.By analyzing the challenges that system security control is facing with, the method gives a measure to secure power system operation and stability, and displays the importance of security measure at the predictive control phase.In order to maintain the system security by means of ancillary service, security pricing theory and its application in the electricity market is studied. By analyzing the risk of security and stability in power systems, considering various composing factors...
Keywords/Search Tags:Power system, Security pricing, Chance constrained programming, Genetic algorithm, Monte carlo simulation
PDF Full Text Request
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