Autors: Perçuku A.S., Minkovska, D. V.
Title: LSTM Algorithm and IoT Data on Power Flow Forecast
Keywords: LSTM algorithm, IoT, sensor’s data, the forecast of power fl

Abstract: LSTM algorithm is an advanced version of Recurrent Neural Network and handles more accurately the time series predictions. The growth of renewable energy sources and changing of consumption nowadays lead on challenges in power system. To ensure the reliability and security on the electricity grid, the forecast of power flow on day ahead is essential. This paper presents a method by using LSTM algorithm and IoT sensor’s data to forecast the power flow on two high voltages overhead lines. The analysis of study results shows better outcomes compared with traditional method.

References

    Issue

    14th NATIONAL CONFERENCE “ELECTRONICA 2023”, 2023, Bulgaria,

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus