Operation and Maintenance Phase

This paper presents a comprehensive approach to optimizing building energy management through a MATLAB-based application and graphical user interface (GUI) integrated with a Knowledge-Based Decision Support System (KBDSS). The main goal is to minimize the total energy cost of buildings by considering various parameters such as insulation levels, window properties, HVAC system specifications, and appliance usage. The proposed system utilizes optimization algorithms to identify the most efficient configurations that reduce energy consumption while maintaining user-defined comfort levels. The application consolidates user inputs and seamlessly communicates with IoT platforms like Arduino and Raspberry Pi, enabling real-time execution of optimized strategies in building environments. Through sensitivity analysis, the study determines the optimal capacities for photovoltaic panels and batteries, demonstrating that strategic increases in these capacities can significantly lower energy costs. The validated KBDSS by numerical analyses provides actionable insights and facilitates automated adjustments to building systems, enhancing energy efficiency, reducing operational costs, and promoting sustainable building operations.