DOI: 10.3390/en19122906 ISSN: 1996-1073

Knowledge Discovery-Driven Intelligent Decision-Making System to Establish Public Building Envelope Prioritizing Strategies: Case Study on Romanian Building Stock

Gheorghe Grigoras, Romeo-Cristian Ciobanu, Bogdan-Constantin Neagu, Mihaela Aradoaei, Razvan-Petru Livadariu, Alina Ruxandra Caramitu

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy performance helps save energy, boost energy independence and security, lower energy costs, and reduce the need for grid investments. Standardizing energy performance assessments enables benchmarking and comparison of building efficiency, encouraging informed decision-making. In this context, the paper presents a knowledge discovery-driven intelligent decision-making system, designed, developed, and tested to identify the best strategies for prioritizing buildings in the envelope process. The system combines data mining techniques with statistical analysis to precisely rank and thoroughly evaluate low-energy-performance buildings and to develop scenario-based strategies for enveloping the buildings to achieve high energy efficiency (associated with nearly zero-energy buildings) under real-world conditions. Testing of the proposed intelligent decision-making system was conducted using a real building database of approximately 3900 records, uploaded from the Romanian central administration website. Under the highest-performance scenario of the envelope-priority strategy, which includes nearly zero-energy building standards, energy savings exceeded 50% across all categories: 51.70% for healthcare, 53.40% for residential, 60.11% for administrative and office buildings, and 69.92% for educational institutions. Overall, the average savings across all building types were 59.81% (644.86 GWh/year).

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