Case study on multi-objective Modified Supply-Demand-based Optimization Algorithm for energy-efficient building retrofitting

Abstract

Investing in energy-efficient retrofitting of existing buildings requires a robust decision-making framework. This study develops a multi-objective optimization technique to assist designers in minimizing payback time and maximizing energy savings within a specified initial investment. The proposed method utilizes a novel metaheuristic, the Modified Supply-Demand-Based Optimization Algorithm (MSDOA), to achieve optimal decisions. The model was tested on nine case studies involving buildings with various facilities, demonstrating its effectiveness. For example, an investment of $190,000 resulted in a payback period of less than three years and energy savings of over 10 % of the baseline consumption. The model considers initial investment, net present value (NPV), payback period, and energy targets as constraints. To evaluate the model's robustness, a sensitivity analysis was performed, examining the impact of varying initial investments, energy savings miscalculations, auditing errors, changes in electrical power costs, and interest rates. The results indicate that higher investments consistently lead to increased energy savings, though the payback period may vary. The MSDOA showed superior convergence speed compared to other algorithms, ensuring more reliable and accurate optimization outcomes. This study confirms the validity of the proposed design and highlights its potential for significant energy savings and financial benefits in building retrofitting projects.