A Decision-Making Tool for Sustainable Energy Planning and Retrofitting in Danish Communities and Districts

Muhyiddine Jradi ()
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Muhyiddine Jradi: Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark

Energies, 2025, vol. 18, issue 3, 1-27

Abstract: This study presents a novel framework for city-level energy planning and retrofitting, tailored to Danish cities and neighborhoods. The framework addresses the challenges of large-scale urban energy modeling by integrating automated processes for data collection, energy demand prediction, and renewable energy integration. It combines open-source simulation tools and validated datasets, enabling efficient and scalable predictions of energy performance across urban areas, including streets, districts, and entire cities, with minimal user input. The key components include data collection and demand modeling, energy resource estimation, performance gap evaluation, and the design of retrofitting strategies with renewable energy integration. The DanCTPlan energy planning tool, developed based on this framework, was applied to two case studies in Denmark: a single street with 101 buildings and a district comprising five streets with 1284 buildings. In the single-street case, retrofitting all buildings to meet current regulations resulted in a 60.8% reduction in heat demand and a 5.8% reduction in electricity demand, with significant decreases in peak energy demands. The district-level retrofitting measures led to a 29.5% reduction in heat demand and a 2.4% reduction in electricity demand. Renewable energy scenarios demonstrated that photovoltaic systems supplying 30% of electricity demand and solar thermal systems meeting 10% of heating demand would require capacities of 2218 kW and 3540 kW, respectively. The framework’s predictive capabilities and flexibility position it as a robust tool to support decision-makers in developing sustainable and cost-effective energy strategies, paving the way toward establishing energy-efficient and positive energy districts.

Keywords: urban energy planning; energy retrofitting; renewable energy integration; energy demand prediction; sustainable cities; positive energy districts; Danish energy planning; energy demand prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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