AHP-based decision making to selecting energy-efficient air conditioning equipaments in a commercial building

Air conditioning equipments accounts for 47% of energy consumption in commercial buildings, with wallmounted and Split Systems representing 76.6% of total usage. Selecting energy-efficient solutions in these settings involves complex decision-making, requiring structured models that incorporate decision-makers' preferences and experiences. Common methods, such as Discounted Payback and Net Present Value (NPV), assess financial feasibility but may overlook other important criteria. This study aims to identify the most suitable energy-efficient air conditioning option or other technologies for a small commercial establishment using the AHP (Analytic Hierarchy Process) method. A literature review was conducted to identify potential alternatives that could improve energy efficiency. The current state of the facility was analyzed, comparing the performance of existing equipment with alternatives and evaluating their financial feasibility. Decision-making criteria for applying AHP were established, and interviews were held with decision-makers to construct a decision tree and assess these criteria. The modeling was conducted using IPE 1.0 software, which implements the AHP algorithm. While traditional financial analysis favored a PID controller, the AHP method revealed that replacing the current equipment with Inverter Split systems would be the optimal choice based on decision-makers' judgments. The AHP method demonstrated its effectiveness in supporting decision-making by analyzing multiple criteria, providing a rational and consistent approach to selecting the most viable alternative.