Electricity Peak Load Demand using De-noising Wavelet Transform integrated with Neural Network Methods
作者： Pituk Bunnoon
DOI: 10.11591/IJECE.V6I1.PP12-20
关键词:
摘要: One of most important elements in electric power system planning is load forecasts. So, this paper proposes the demand forecasts using de-noising wavelet transform (DNWT) integrated with neural network (NN) methods. This research, case study uses peak Thailand (Electricity Generating Authority Thailand: EGAT). The data will be analyzed many influencing variables for selecting and classifying factors. In decomposing signal into 2 components these are detail trend components. forecasting method algorithm used. work results shown a good performance model proposed. result may taken to one decision systems operation. Full Text: PDF DOI: http://dx.doi.org/10.11591/ijece.v6i1.8901
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