The Revised Load Factor Method For Building Cooling Load In Urban Planning Stages

Along with the rapid growth of the economy and the unceasing enhancement of people’s living standard in China, the energy consumption continues to grow and the energy efficiency is too low to satisfy its demand. Energy has been a prominent issue in China and world today. With the challenges of new energy, integrated energy saving design during urban planning stages can make sure the achievement of energy saving buildings. Load forecasting is the basis of regional energy planning and the power supply equipments. At present, the area index method is usually used to forecast cooling load during urban planning stages, which may cause the overestimate of regional cooling load. A Load Factor Method (LFM) which was proposed by our team can forecast hourly cooling load for all year8760hour.The objective of this thesis was to revise the Load Factor Method further by considering the cooling load caused by the solar radiation through the transparent and opaque envelop. By analyzing the performance analysis of solar radiation heat gained by building windows, the model of the solar radiation heat gain was established. A typical glazing solar radiation heat gain coefficient (SHGC) database was established including these five partitions. Thus the model of the instantaneous solar radiation heat gain through windows above method was constructed. According to the DeST furniture plate model, the glazing indoor heat storage plate model was also established, which converts solar radiation heat gain into instantaneous cooling load. As the same conditions, the established model and the cooling load caused by cooling load coefficient method of solar radiation heat gain through the window is contrasted; the results show that the relative error is less than20%. Thus it provided a new train of solving the problem of cooling load of the sun radiation through the window, and it provides a practical way to revisit the Load Factor model in regional energy planning.While analysising the solar radiation on the opaque envelop and calculating the cooling load of opaque envelop, the solar radiation cannot be separately calculated as a disturbance quantity. The model of envelop heat transfer heat gain is established based on the state equation method which solves the exterior-protected construction’s PRF (Period Response Factor). Heat storage model which can make the exterior-protected structure heat gain into instantaneous cooling load was constructed through the exterior-protected structure to the division of thermal radiation and convection part. It showed that the relative error is less than11%comparing with the model calculation results with the Cooling Load Factor Method which calculates results by the example calculation.Through the analysis of the significance building cooling load factors, Correct Load Factor Method (CLFM) model which included fresh air model, personnel model, light model and equipment model was established. The model was applied in cooling load forecasting for an office building in Beijing, besides compared with two other cooling load calculate methods based on the Load Factor model and the DeST simulation software. The results showed that the accuracy of correct load factor method is less than20%on predicting building cooling load, and its dynamic variation rule was the same as the measured load which proved that the application of Correct Factor Method to urban planning stage in load forecasting was very practical. Comparing the results of cooling load forecasting for different regions and building types with the DeST simulation software results, it showed that the CLFM matched the requirement in engineering of cooling load forecasting accuracy.At last, this paper developed software used for building cooling load prediction in urban planning stages by the Visual Studio2010interface and C#language programming. This software had a friendly interface and great visualization. It had the advantage of obvious less input parameters, shorter calculating time and greater visualization comparing with other load forecasting software.