Optimized Dispatch for Power Grid Connected with Wind Farm Based on Interval Simulation

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Abstract:

In view of the disadvantage existing in stochastic programming and fuzzy programming that in the process of modeling of wind power both of them need a huge amount of historical data information to establish precise model, and the advantage of interval planning that it only need to know the upper and lower bounds of the variable in the uncertainty modeling and interval variables contains more information than real variables, this paper puts forward the interval model of the wind power, and use the interval possible degree to deal with the interval constraint conditions. At the same time, this paper adopted the chaotic particle swarm optimization algorithm based on logic from the map to solve the model. Finally, the paper proved the accuracy and effectiveness of the model and algorithm by an example.

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Periodical:

Advanced Materials Research (Volumes 1008-1009)

Pages:

207-211

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Online since:

August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Long Jun, Mo Qunfang, Zeng Jian.A stochastic programming based short-term optimization scheduling strategy considering energy conservation for power system containing wind farms[J]. Power System Technology(2011).

Google Scholar

[2] Li Qun, Zhang, Liudong, Yin Minghui, Zhang Xiaolian, Zou Yun. Unit commitment of power grid integrated with wind farms based on fuzzy decision-making[J]. Power System Technology(2013).

Google Scholar

[3] Liang R H, LIAO Jianhao, A fuzzy-optimization approach for generation scheduling with wind and solar energy system[J]. IEEE. Trans. on Power Systems(2007).

DOI: 10.1109/tpwrs.2007.907527

Google Scholar

[4] Yu Jia, Ren Jianwen, Zhou Min. A chance-constrained programming based dynamic economic dispatch of wind farm and pumped-storage power station[J]. Power System Technology (2013).

Google Scholar

[5] Jiang C, Han X. A new uncertain optimization method based on intervals and an approximation management model[J]. CMES-Computer Modeling in Engineering and Science (2007).

Google Scholar

[6] Yuan Tiejiang, Yao qin, Tuerxun yibulayin, Li yiyan. Optimized economic and environment friendly dspatching modeling for Large scale wind power integration[J]. Proceedings of the CSEE(2010).

Google Scholar