Study on Power Load Forecasting Method Based on Ant Colony Optimization

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Abstract:

Load forecasting is one of the important working of the power system, which plays a very significant role in various departments of power system operation. Load accurate scientific prediction can make power decision-making departments economically and reasonably to adjust generator, power line, which makes it more reasonable. This paper introduces the optimal combination forecast model, and organically combine with several electric load forecasting models by the weight, come to more accurate results, with higher prediction accuracy, and the relative error is small, it has some practical value.

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733-736

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March 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Chen Jintao, Li Sheng, Jiang Zhenheng. Power load combination forecast based on ant colony algorithm[J]. Information technology, 2013(01): 51-54.

Google Scholar

[2] Lei Xiujuan. Swarm Intelligent Optimization Algorithms and Their Application[M]. Beijing, Science Press (2012).

Google Scholar

[3] Liu Zhenhong, Ma Shaohan. Discrete Optimization Algorithms[M]. Beijing, Science Press (2012).

Google Scholar

[4] Zou Gang. Study on Power Load Forecasting Method Based on Ant Colony Algorithm[D]. Chongqing: Chongqing University, (2006).

Google Scholar

[5] Li Jinying. Study on gray combined forecasting of nonlinear seasonal power load[J]. Power system Technology, 2003, 27(5): 26-28.

Google Scholar

[6] Shanghai Statistical Yearbook Year Book, 2011. Beijing: Beijng: China Statistics Press.

Google Scholar