The Energy Saving Renovation of Regional Buildings Based on Bayesian Estimation
DOI:
https://doi.org/10.54097/hset.v59i.10086Keywords:
Regional architectural complex; Bayesian estimation; Energy consumption prediction model; Monte Carlo simulation; Energy parameters; Probability distribution curve.Abstract
With China's new urbanization vision and existing urban renewal and building energy efficiency improvement project, large-scale energy conservation renovation of regional buildings has become an important content of ecological environmental protection and low-carbon and an important means to improve the regional energy efficiency level. Of energy-saving reform foundation database is presented in this paper, including construction, power consumption, equipment, operation, technology and willingness to word stock, statistics obtained the regional energy complex parameter (envelope thermal performance, elevator equipment, power and efficiency of cooling and heat sources, etc.) statistical rule and can use the benchmark, build the regional buildings energy consumption prediction model based on bayesian estimation, The probability matrix of large-scale reconstruction of regional buildings is obtained. At the same time, the global sensitive parameter analysis method and the single parameter regression model of energy saving transformation factor are established, and it is found that the internal load factor has the most significant effect on energy consumption. By adjusting energy parameters, the probability distribution curve of energy saving and the distribution of normalized value under the constraint conditions of different reconstruction scenarios were simulated, and the discrete MC simulation method was used to predict the regional overall energy saving reconstruction based on renovation intention, which could realize the trade-off judgment and gradual optimization of the strategy package of energy saving measures combination.
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