Xinhua Xu

Bio: Xinhua Xu is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Materials science & Building envelope. The author has an hindex of 18, co-authored 28 publications receiving 1540 citations. Previous affiliations of Xinhua Xu include Huazhong University of Science and Technology.

A grey-box model of next-day building thermal load prediction for energy-efficient control

Abstract: Accurate building thermal load prediction is essential to many building energy control strategies. To get reliable prediction of the hourly building load of the next day, air temperature/relative humidity and solar radiation prediction modules are integrated with a grey-box model. The regressive solar radiation module predicts the solar radiation using the forecasted cloud amount, sky condition and extreme temperatures from on-line weather stations, while the forecasted sky condition is used to correct the cloud amount forecast. The temperature/relative humidity prediction module uses a dynamic grey model (GM), which is specialized in the grey system with incomplete information. Both weather prediction modules are integrated into a building thermal load model for the on-line prediction of the building thermal load in the next day. The validation of both weather prediction modules and the on-line building thermal load prediction model are presented. Copyright © 2008 John Wiley & Sons, Ltd.

A review on the prediction of building energy consumption

Abstract: The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, the operation of sub-level components like lighting and HVAC systems, occupancy and their behavior. This complex situation makes it very difficult to accurately implement the prediction of building energy consumption. This paper reviews recently developed models for solving this problem, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods. Previous research work concerning these models and relevant applications are introduced. Based on the analysis of previous work, further prospects are proposed for additional research reference.

Advanced control systems engineering for energy and comfort management in a building environment—A review

Abstract: Given restrictions that comfort conditions in the interior of a building are satisfied, it becomes obvious that the problem of energy conservation is a multidimensional one. Scientists from a variety of fields have been working on this problem for a few decades now; however, essentially it remains an open issue. In the beginning of this article, we define the whole problem in which the topics are: energy, comfort and control. Next, we briefly present the conventional control systems in buildings and their advantages and disadvantage. We will also see how the development of intelligent control systems has improved the efficiency of control systems for the management of indoor environment including user preferences. This paper presents a survey exploring state of the art control systems in buildings. Attention will be focused on the design of agent-based intelligent control systems in building environments. In particular, this paper presents a multi-agent control system (MACS). This advanced control system is simulated using TRNSYS/MATLAB. The simulation results show that the MACS successfully manage the user’s preferences for thermal and illuminance comfort, indoor air quality and energy conservation.