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Title:
 
Demand-Aware Electricity Price Prediction Based on LSTM and Wavelet Transform
 
Author(s):
 
K. Iwabuchi, K. Kato, D. Watari, I. Taniguchi, F. Catthoor, E. Shirazi, T. Onoye
 
Keywords:
 
Dynamic Pricing, Electricity Price Forecast, Electricity Demand
 
Topic:
 
Finance, Markets and Policies
Subtopic: Costs, Economics, Finance and Markets
Event: 38th European Photovoltaic Solar Energy Conference and Exhibition
Session: 7DV.1.4
 
Pages:
 
1668 - 1670
ISBN: 3-936338-78-7
Paper DOI: 10.4229/EUPVSEC20212021-7DV.1.4
 
Price:
 
 
0,00 EUR
 
Document(s): paper, poster
 

Abstract/Summary:


This paper proposes a novel electricity price prediction method using past electricity demand. The previous method predicts the electricity price using LSTM after wavelet transform of the past electricity price series. Wavelet transform decomposes the series into more smooth and stable series, and accurate prediction is performed by LSTM with these series. The proposed method also uses the electricity demand series, and the demand is also applied wavelet transform for effective LSTM step. Experimental results show the effectiveness of the proposed method, and the accuracy is drastically improved over the previous method.