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Journal of Applied MathematicsVolume 2014 2014, Article ID 356527, 7 pages

Research Article

College of Mathematics and Econometric, Hunan University, Changsha, Hunan 410082, China

China CITIC Bank, Changsha Shuyuan Road Branch, Changsha, Hunan 410015, China

Received 7 April 2014; Accepted 18 May 2014; Published 2 June 2014

Academic Editor: Nan-Jing Huang

Copyright © 2014 Minru Bai and Zhupei Yang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

As a major energy-saving industry, power industry has implemented energy-saving generation dispatching. Apart from security and economy, low carbon will be the most important target in power dispatch mechanisms. In this paper, considering a power system with many thermal power generators which use different petrochemical fuels such as coal, petroleum, and natural gas to produce electricity, respectively, we establish a self-scheduling model based on the forecasted locational marginal prices, particularly taking into account emission constraint, emission cost, and unit heat value of fuels. Then, we propose a distributionally robust self-scheduling optimization model under uncertainty in both the distribution form and moments of the locational marginal prices, where the knowledge of the prices is solely derived from historical data. We prove that the proposed robust self-scheduling model can be solved to any precision in polynomial time. These arguments are confirmed in a practical example on the IEEE 30 bus test system.





Autor: Minru Bai and Zhupei Yang

Fuente: https://www.hindawi.com/



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