| Issue |
EPJ Web Conf.
Volume 326, 2025
International Conference on Functional Materials and Renewable Energies: COFMER’05 5th Edition
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 4 | |
| Section | Renewable Energy Sources | |
| DOI | https://doi.org/10.1051/epjconf/202532602005 | |
| Published online | 21 May 2025 | |
https://doi.org/10.1051/epjconf/202532602005
Smart Building Electrical Energy Optimization Through Neural Network Techniques
Laboratory of Industrial Engineering and Surface Engineering, FST, Sultan Moulay Slimane University, BENI MELLAL BP 23000, Morocco
* Corresponding author: moad.elkamili@usms.ma
Published online: 21 May 2025
This paper presents a new approach to optimizing the use of electrical energy in smart buildings using neural network techniques. The proposed method has two main objectives: (i) to achieve energy efficiency through the application of intelligent load management; (ii) to ensure stable building system operation through the prediction of energy demand trends. A neural network-based control algorithm was developed and implemented in the building electrical systems for real-time energy optimization. This approach was validated by applying it to a smart building case, with a real-time monitoring and control prototype. Comprehensive analysis, including simulation and experiment tests, validated the system's effectiveness in reducing energy consumption while maintaining operational stability and being an effective solution to sustainable building energy management.
Key words: Neural Networks (NN) / Intelligent Control Algorithm (ICA) / Energy Efficiency Optimization / Real-Time Control (RTC) / Sustainable Building Energy Systems / Smart Building (SB)
© The Authors, published by EDP Sciences, 2025
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