Empowering Energy Efficiency: Fuzzy Logic Weather Prediction in Smart Energy Management

As global energy demands rise, the imperative for environmentally friendly and renewable energy sources intensifies. This paper introduces a power management control system utilizing fuzzy logic, emphasizing its potential to optimize the electrical component of a residential system. Through comprehensive modeling and implementation in MATLAB/Simulink, the proposed system's performance is thoroughly tracked. Simultaneously, the research delves into the integration of fuzzy logic and energy management systems specifically tailored for residential areas. The study establishes a fuzzy logic-based model trained on historical weather data, encompassing variables like temperature, humidity, wind speed, and cloud cover. This model adeptly handles imprecise and uncertain weather information, showcasing superior predictive capabilities compared to traditional forecasting methods. The research underscores the pivotal role of accurate weather predictions in residential energy management, demonstrating enhanced energy efficiency and cost savings. Moreover, integrating fuzzy logic into residential energy management can revolutionize how households consume energy by leveraging accurate weather predictions to adjust energy usage dynamically. This not only enhances energy efficiency but also reduces costs for consumers while contributing to broader sustainability goals. The weather prediction accuracy was rigorously tested through a classification model, validating the reliability and adaptability of the fuzzy logic-based system in real-world scenarios.