Towards Integration of Spatial Context in Building Energy Demand Assessment Supported by CityGML Energy Extension

Abstract

The quality of Building Energy Models (BEMs), as dominant techniques to simulate and analyze building behavior in terms of energy consumption, depends strongly on the weather data that is generally captured by spatially low-resolution weather stations and in 2D. The provided weather data does not satisfy the BEMs requirements in terms of accuracy and spatial details. To address this issue, WSNs (Wireless Sensor Networks) have shown a high potential in offering 3D measurements with desired resolution and quality. However, the optimal deployment of a point-based wireless sensor network in an urban area to capture information on microclimate is a challenging task due to the complexity of the integration and management of diverse affecting factors as well as the 3D nature of the urban environment and its dynamics. This paper proposes to design and develop a workflow based on CityGML-standards to represent and manage the required spatiotemporal information for BEMs and feed a knowledgebase that can be used in WSN deployment optimization algorithms. Finally, the paper presents and discusses a case study to highlight the advantages and limitations of the proposed approach.