M. Pushpavalli, D. Dhanya, Megha Kulkarni, R. Rajitha Jasmine, B. Umarani, M. RamprasadReddy, Durga Prasad Garapati, Ajay Singh Yadav, A. Rajaram
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Enhancing Electrical Power Demand Prediction Using LSTM-Based Deep Learning Models for Local Energy Communities
The pursuit of accurate electrical power demand forecasting has led to the application of deep learning algorithms, notably demonstrating promising outcomes despite the prerequisite of substantial ...
期刊介绍：
Electric Power Components and Systems publishes original theoretical and applied papers of permanent reference value related to the broad field of electric machines and drives, power electronics converters, electromechanical devices, electrical equipment, renewable and sustainable electric energy applications, and power systems.
Specific topics covered include:
-Electric machines-
Solid-state control of electric machine drives-
Power electronics converters-
Electromagnetic fields in energy converters-
Renewable energy generators and systems-
Power system planning-
Transmission and distribution-
Power system protection-
Dispatching and scheduling-
Stability, reliability, and security-
Renewable energy integration-
Smart-grid and micro-grid technologies.
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