A model approach to the energy performance design of industrial areas: Example of Konya auto industry campus

Today, increasing energy needs and costs, environmental pollution factors such as energy-efficient design is required. Industrial areas cover important areas within the city. Improving energy performance in these areas will contribute greatly to the conservation of energy. In this context, when designing industrial areas, it is aimed to put forward a model that can take measures to improve the energy performance of buildings. Within the scope of the study, the buildings in the Eski Sanayi and Karatay Sanayi in Konya were examined. As a result of the researches conducted in the workplaces in the area, 128 different building alternatives have emerged in terms of design parameters such as size, orientation and exterior wall material properties. The annual heating energy requirements of these alternatives have been calculated by the calculation method in TSE 825. Estimating the annual heating energy demand of industrial buildings by using the calculated values is modeled with fuzzy logic technique, which is an artificial intelligence method. The calculated heating energy requirement values and the values obtained from the fuzzy logic model were compared with the multiple coefficient of determination method (R2). As a result of the comparison, it is shown that fuzzy logic model accurately predicts the annual heating energy requirement of buildings by 98.09%. This shows that the fuzzy logic model can be used to estimate the annual heating energy requirement of 98.09% accuracy according to the orientation dimension and material properties of the newly designed single volume industrial buildings. By using this model, it can be ensured that measures can be taken to increase the energy performance of the buildings to be designed. Keywords: Architecture and Artificial Intelligence, Building Energy Performance, Fuzzy Logic, Industrial Buildings