Live Power Generation Predictions via AI-Driven Resilient Systems in Smart Microgrids
Author:
Affiliation:
1. School of Computer Science and Informatics, Cardiff University, Cardiff, U.K
2. College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia
Funder
PSDSARC Research at Prince Sultan University, Saudi Arabia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/30/10510045/10453372.pdf?arnumber=10453372
Reference39 articles.
1. Adaptive Learning-Based Secure and Energy-Aware Resource Management for Multi-Mode Low-Carbon PIoT
2. CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production
3. Stochastic Weather Modeling-Based Protection Scheme for Hybrid PV–Wind System With Immunity Against Solar Irradiance and Wind Speed
4. Short-Term Residential Load Forecasting Based on Resident Behaviour Learning
5. Energy Management and Operational Planning of a Microgrid With a PV-Based Active Generator for Smart Grid Applications
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