From cost to efficiency: photovoltaic modules allocation to maximizing energy production while minimizing costs with building information modeling

Purpose This article aims to develop an automated building information modeling (BIM)-based process to optimize the allocation of photovoltaic (PV) modules on building roofs. The goal is to maximize energy production while minimizing implementation costs, advancing digitalization in sustainable project planning within the Architecture, Engineering, Construction and Operations (AECO) sector. Design/methodology/approach The research integrates visual programming in Dynamo with Python scripts to simulate and compare combinations of 21 PV module models from four brands. The model extracts geometric information directly from a Revit BIM model, calculates energy production and costs for each configuration, and automatically allocates the most efficient arrangement. The approach is demonstrated through two experiments and compared against a real PV system installed at the Federal University of Pernambuco (UFPE). Findings The results demonstrate that the proposed algorithm identifies the most efficient cost–production configuration of PV modules. Experiment 1 achieved the highest daily production (2,723.63 kWh/day) at a total cost of USD $387,575.45, while Experiment 2 achieved a better cost–benefit balance (2,630.09 kWh/day at USD $370,504.08). Compared to the current UFPE layout, the optimized configurations increased energy production. The study confirms that integrating BIM with algorithmic simulation enables data-driven decision-making in sustainable design. Research limitations/implications The study is limited to short-term cost and production parameters and does not include life-cycle analysis, maintenance costs or regional variations in prices and solar irradiation. Future research should integrate life-cycle assessment (LCA), LiDAR data and drone-based photogrammetry to enhance the precision of energy and economic simulations. Practical implications The model provides a decision-support tool for engineers, designers and facility managers to automate PV module allocation directly within BIM, improving efficiency in retrofit and new-building projects. It enables comparative analysis of layout alternatives, supporting cost-effective, sustainable decision-making in public and private organizations. Social implications By promoting the adoption of renewable energy through digital project automation, this research supports carbon emission reduction and contributes to global sustainability goals. The approach fosters technological innovation and energy efficiency in public institutions, strengthening the role of digital transformation in climate action. Originality/value This article advances BIM-based automation in PV system design by proposing a dual-objective optimization model that simultaneously considers energy efficiency and cost within a single BIM platform. It contributes to the digitalization of projects by transforming BIM from a documentation tool into an optimization environment for sustainable solutions.