Energy Efficiency Optimization Model for Sustainable Campus Buildings and Transportation - Atabek Movlyanov; Saltuk Buğra Selçuklu (Buildings, 2025)
University campuses face significant challenges in balancing energy efficiency, renewable energy adoption, and sustainable transportation while meeting budgetary constraints and sustainability goals. While existing optimization approaches typically address these as separate problems, this study presents an innovative multi-objective optimization framework that integrates building efficiency, renewable energy, electric vehicle charging, and sustainability scoring criteria into a unified model. The approach formulates a mixed-integer non-linear programming model with three competing objectives: minimizing primary energy consumption, minimizing investment cost, and maximizing sustainability metrics, addressing the critical need for comprehensive campus energy management tools. The optimization model was applied to the R&D Park Building of Erciyes University, utilizing actual building parameters, time-variable electricity pricing, and commercially available renewable energy technologies. Our analysis of the Pareto-optimal solutions reveals distinct trade-offs between the objectives, with primary energy consumption ranging from 1,317,860 to 4,642,770 GJ/year, investment costs between $25,735 and $485,674, and sustainability scores between 366 and 1034. Most significant for practical implementation is the balanced performance solution ($127,064), which achieves minimum energy consumption (1,367,010 GJ/year) while securing a substantial sustainability score of 538 points. The results demonstrate that while inherent trade-offs exist between competing objectives, significant sustainability improvements are achievable at intermediate investment levels, making meaningful environmental progress accessible to a broad spectrum of higher education institutions. This comprehensive optimization framework provides campus administrators with a practical decision-support tool for aligning energy systems with institutional priorities, budgetary constraints, and sustainability commitments.