Short-Term Load Forecasting of Microgrid by a New Advanced Prediction Strategy

Xin Yu Yin

doi:10.4028/www.scientific.net/AMM.508.231

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 508Short-Term Load Forecasting of Microgrid by a New...

Short-Term Load Forecasting of Microgrid by a New Advanced Prediction Strategy

Abstract:

Due to the complexity and volatility of microgrid load sequence, this paper proposes an Adaptive Neuro-fuzzy inference system (ANFIS) prediction algorithm using Quantum Particle Swarm Optimization (QPSO) to optimize the network parameters, combining with Wavelet analysis method for preprocessing. The example shows that the proposed approach to microgrid load forecasting is both novel and effective, can improve the accuracy of load prediction.

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Periodical:

Applied Mechanics and Materials (Volume 508)

Pages:

231-235

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.508.231

Citation:

Cite this paper

Online since:

January 2014

Authors:

Xin Yu Yin

Keywords:

ANFIS, Load Forecasting, Microgrids (MGs), QPSO, Wavelet Transform (WT)

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References

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