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Abstract: It becomes popular to use computer simulation technique to evaluate the performance of energy utilizations in buildings. The hourly weather data as simulation input is a crucial factor for the successful energy system simulation, and obtaining an accurate set of weather data is necessary to represent the long-term typical weather conditions throughout a year. This paper introduces a stochastic approach, which is called the first order multivariate Markov chain model, to generate the annual weather data for better evaluating and sizing different energy systems. The process for generating the weather data time series from the multivariate Markov transition probability matrices is described using 15-years actual hourly weather data of Hong Kong. The ability of this new model for retaining the statistical properties of the generated weather data series is examined and compared with the current existing TMY and TRY data. The main statistical properties used for this purpose are mean value, standard deviation, maximum value, minimum value, frequency distribution probability and persistency probability of the weather data sequence. The comparison between the observed weather data and the synthetically generated ones shows that the statistical characteristics of the developed set of weather data are satisfactorily preserved and the developed set of weather data can predict and evaluate different energy systems more accurately. [Copyright &y& Elsevier]

Abstract: A traditional Chinese heating system, the Chinese Kang, is used by 175 million people in detached houses in the rural regions of China, especially in Northeast China. This system utilizes biomass such as corn stalks, straw, corncob and energy plants as the heat sources. The objective of this paper is to establish a set of models to simulate the energy performance of the Kang heating system in one Chinese detached house. An experimental field study was carried out to collect practical parameters in a newly constructed Chinese detached house. The dynamic performance of the Kang heating system was simulated by using IDA-ICE 4.0 embedded with an empirical model built in the field study. The results show that the simulation can obtain good overall agreement with the field measurement results. It was confirmed that the Kang model created by IDA-ICE 4.0 is capable of simulating the performance of the Kang system and of calculating energy consumption in the detached house. Moreover, the result reveals that the thermal environment in the present Chinese detached house is still poor during the severe cold season if only the Kang system is used to heat the whole house. [ABSTRACT FROM AUTHOR]