Electrical load forcasting in intraday markets using neural network based on long-short term memory
155 viewsDOI:
https://doi.org/10.54939/1859-1043.j.mst.82.2022.91-97Keywords:
Time series, intraday electricity market, recurrent neural network (RNN), long-short-term-memory (LSTM).Abstract
Load forecasting plays an important role for buyers participating into electricity markets. Buyers need to be able to forecast load demand 15 minutes in advance for participating in the intraday market. Thus, the problem of predicting the electricity load 15 minutes in advance plays a vital role in participating into the intraday market. Due to the non-linearity and instability under natural conditions of electrical loads in small-scale power systems, accurate forecasting is still a challenge. This paper investigates the use of Long-Short-Term-Memory (LSTM) short-term memory structure based on feedback neural network structure to predict the electricity load 15 minutes in advance.
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