应用蒙特卡罗模拟方法预测区域建筑负荷

发布时间：2018-09-05 19:28

【摘要】：目前城市区域建筑能源规划阶段单体建筑信息不完备、无法同时使用常规负荷计算软件对各建筑进行冷热电力负荷预测,本文提出采用蒙特卡罗模拟方法结合负荷计算原理预测区域建筑冷热电负荷的方法 .该方法首先构建适用于新区多功能建筑的冷热电负荷预测随机模型,并依据调研结果确定预测模型风险变量的特征分布,再利用蒙特卡罗随机模拟技术应用MATLAB语言编制程序可求解研究区域峰值冷热负荷概率分布、电力峰值分布和全年逐时负荷.论文以某新区为例,模拟了区域建筑的负荷特性,仿真结果表明:区域建筑负荷预测随机模型可以有效地模拟新区冷热电峰值负荷的频数分布和累积概率,在典型应用场景下,研究区域峰值电力负荷95%置信度下为37 MW,峰值冷负荷为50 MW,比传统方法下降6%.
[Abstract]:At present, the single building information in urban area energy planning stage is not complete, so it is impossible to use the conventional load calculation software to forecast the cooling and heat power load of each building at the same time. In this paper, a Monte Carlo simulation method combined with the principle of load calculation is proposed to predict the cold, thermal and electric loads of regional buildings. This method firstly constructs a stochastic model of cold, heat and electricity load forecasting for multi-functional buildings in the new area, and determines the characteristic distribution of the risk variables of the prediction model according to the survey results. Using Monte Carlo stochastic simulation technology and MATLAB programming language, the probability distribution of peak cooling and heat load, the peak distribution of electric power and the hourly load of the whole year can be solved. This paper takes a new area as an example to simulate the load characteristics of regional buildings. The simulation results show that the stochastic model of regional building load forecasting can effectively simulate the frequency distribution and cumulative probability of the peak load of cooling and heating electricity in the new area, and it can be used in typical application scenarios. The peak cooling load of 37 MW, at 95% confidence level in the studied area is reduced by 6% compared with the traditional method, and the peak cooling load of 50 MW, is lower than that of the traditional method.
【作者单位】：上海市建筑科学研究院;同济大学绿色建筑及新能源研究中心;
【基金】：基金项目:上海市建筑节能与绿色建筑技术创新服务平台(17DZ2292900)
【分类号】：TU831.2

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