Study On Hourly Building Cooling Load Prediction Method During The Urban Energy Planning Stage

Substantial increasing of energy consumption, reducing of conventional energy reserves and low energy efficiency are the main urban energy problems facing China government. However, there is not perfect urban energy planning system. The planning of power supply, heating supply and gas supply are adiminidtrated by different authorities, considered in isolation without coordination, which led to unreasonable utilization of urban energy. Therefore, an integrated urban erengy planning method is provided, which analyzes the dynamical characteristics and spatial distribution of urban energy, considers intercoordination among special energy planning and dynamical balance between energy supply and demand to achieve the goal of reasonable allocation and high efficiency of urban energy. The key to carry out this planning method is the comprehensive and accurate understanding of building cooling load characteristics. However, the conventional prediction methods on building cooling load are difficult to be used at the urban planning stage because of the limited building information and the lack of adequate statistical data on building energy.In this paper, feasible building cooling load prediction methods are discussed based on theoretical analysis, simulation and statistical analysis. First, the determination of limiting factors for a standard building, including physical factor, internal factor and external factor, is provided after analyzing the significance of building cooling load influence factors. And then the Hourly Cooling Load Factor Method (HCLFM) model and simulation model based on DeST software are developed. At last, the advantages and disadvantages of Grey Markov theory and feasibility applied in building cooling load prediction fieldare analyzed. The steps and application mode are proposed.The Hourly Cooling Load Factor Method (HCLFM) based on theoretical analysis is developed, which is composed of the building envelope cooling load predicting model, infiltration load predicting model, occupant load predicting model, lighting load predicting model and equipment load predicting model. The predicted results are verified by comparing the results of different calculation methods and analyzing errors between measured results and predicted results. The results show that the prediction relative error of buling cooling load index is less than 10% meeting accurancy requirements in engineering field and the predicted results have the same dynamic characteristics based on HCLFM as that based on DeST software. Take an office building for example; the prediction errors are less than 20% during whole cooling period. The simulation model based on DeST software is developed to predict the dynamic characreristics of building cooling load and Grey-Markov model based on statistical data is developed to predict building cooling load index. Integrating the two methods mentioned above, the application mode of hourly building cooling load prediction model is provided at the urban planning stage.According to different background conditions, the different methods provided in this paper can be applied to analyze the hourly building cooling load. HCLFM is more feasible to a specific planned plot; the method integrating DeST simulation and Grey-Markov can be used to analyze the building cooling load of a type of building of a city.In a word, the accurate prediction of the hourly building cooling load has the most importmant significance in allocating and optimizating urban energy system.