Bing Dong is interested in an integrated computational and engineering approach/infrastructure to help both architects and engineers to achieve energy efficiency and sustainability in buildings during design and operation stages.

During the past six years, Bing Dong have conducted extensive studies on the BIM data schema, integrated building performance simulation tools, building energy performance measurement and data analysis, model-based predictive building controls, occupancy detection and environmental sensor network.

1) Aiming at investigating suitable building performance data schemas for the interoperability of different building performance simulation tool, Bing Dong compared IFC and gbXML in terms of their data representation, data structure, redundancy and expandability. Bing Dong developed a software platform to extend current energy models to high resolution dynamic control models for control design and simulation based on IFC data schema.

2) Aiming at improving building energy efficiency and encouraging code compliance, Bing Dong conduct a substantial energy performance simulation and HVAC control design works on different types of buildings and HVAC systems from residential, commercial to research laboratory buildings. The systems vary from VAV, radiant heating floor, heat pump to UFAD coupled with chilled beam, mix-mode and hybrid ventilation. All works are based on well established simulation tools such as EnergyPlus, Dymola and MATLAB.

3) Aiming at exploring the impact of current environmental sensor networks (e.g., temperature, CO2, acoustics) and information technology on the building operation and energy consumption, Bing Dong analyzed the measured data and predict the future energy usage in commercial buildings based on ANN models. Bing Dong also evaluated current different energy simulation tools in terms their data inputs, user interface, complexity of calculation algorithm and accuracy by comparing with measured data. Based on the environmental sensing setup I conducted a study on the occupancy behavior detection and prediction using Hidden Markov Model and sequential data mining methods.

4) Aiming at knowing how this dynamic occupancy schedule can impact the whole building energy consumption, Bing Dong developed a predictive real-time control system for the building heating cooling and ventilation system which optimizes the whole building energy use while maintaining indoor occupancy comfort. Finally, Bing Dong setup experiments in CMU Solar Decathlon House (2005) which is used as office now and tested my control system in different seasons for mix-mode building operation. Bing Dong also investigated the short-term weather forecasting (e.g., outdoor temperature, solar radiation), PV generation and smart grid interaction. All these works are the preparations for my future research goals.

Future Research Plan

1) Renewable Energy Integration for Sustainable Buildings

2) Advanced Control Strategies for Energy-efficient and Sustainable Buildings

3) Large-scale Sensor Network to Social Network

4) Impact of Building Energy Usage on Power Grid

5) Short-term Weather Forecasting