Smart Building Electrical Energy Optimization Through Neural Network Techniques

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.