ISSN : 2583-2646

Smart Electricity Demand Forcasting by Using Improved LSTM Algorithm

ESP Journal of Engineering & Technology Advancements
© 2023 by ESP JETA
Volume 3  Issue 2
Year of Publication : 2023
Authors : H. Jeyalakshmi, M. Mariammal


H. Jeyalakshmi, M. Mariammal, 2023. "Smart Electricity Demand Forcasting by Using Improved LSTM Algorithm" ESP Journal of Engineering & Technology Advancements  3(2): 65-71.


Demand forcasting, which concerns the estimation of future electricity demand, is needed for the operation and management of power systems. Effective Electricity demand forecasting can relieve the conflict between power supply and demand. Furthermore, effective load forecasting can improve the efficiency of power stations and ensure the safety of the grid. It is suggested that a reduction of a few percentage points in prediction accuracy would have significant cost impact on companies operating in highly competitive power markets. In our project we are going to forecast the electricity demand by using a Deep learning algorithm which is called as Improved Long Short Term Memory. By using Improved LSTM we can able to get accurate Future predicted output.


[1] D. Bunn and E. D. Farmer, Comparative Models for Electrical Load Forecasting. New York, NY,USA: Wiley, 1985.
[2] S.J. Huang and K.-R. Shih, “Short-term load forecasting via arma model identification including non-Gaussian process considerations, ”IEEE Trans. Power Syst., vol. 18, no. 2, pp. 673–679, May 2003.
[3] A. Antoniadis, X. Brossat, J. Cugliari, and J.-M. Poggi, “A prediction interval for a function-valued forecast model: Application to load forecasting,”Int. J. Forecasting, vol. 32, no. 3, pp. 939–947, 2016.
[4] J.R. Lloyd, “Gefcom2012 hierarchical load forecasting: Gradient boosting machines and Gaussian processes.
[5] Nitin Sonaji Magar, Zafar Ul Hasan, Anand B.Humbe, 2023. "Design and Development of Optimized Cardiovascular Disease Prediction Model using Artificial Intelligence" ESP International Journal of Advancements In Science & Technology (ESP- IJAST) Volume 1, Issue 2 : 20-27
[6] Ameer Baig, Shum Sundar Bachu,Vejandla Meghana, M. Ravi Kumar, 2023. "Smart Irrigation System Using IoT" ESP International Journal of Communication Engineering & Electronics Technology (ESP- IJCEET) Volume 1, Issue 1 : 14-21


Long Short Term Memory, Forcasting, Power Supply, Demand, Effective Load Forcasting.