基于BP神经网络的散热器面积设计研究

Research on Radiator Area Design Based on BP Neural Network

降低供暖系统的运行能耗是建筑行业实现节能降碳的一条必由之路,合理设计散热器面积对于供暖系统能效的提高、供暖房间热舒适性的改善和系统初投资的降低意义重大。目前,我国普遍采用基于稳态热平衡的传统散热器面积设计模型,该模型未将围护结构热惯性、室内热扰等因素纳入考虑范畴,从而导致散热器的设计面积要大于实际所需面积。对此,本研究应用建筑热环境模拟手段,构建多类房间多种供暖运行工况的模拟数据库,再基于此,运用BP神经网络构建一种新的散热器面积设计模型,并综合分析该模型的准确性和适用性,进而将其与传统散热器面积设计模型的设计效果进行分析对比。结果表明,该模型的相关系数R2高于0.724,平均绝对误差小于0.533 m^(2),均方根误差小于0.680 m^(2)。进一步,针对不同气候区、不同散热器类型及不同供水温度工况下散热器面积的设计,该模型基本能够将最低供暖室温控制在18~21℃。相对照,基于传统散热器面积设计模型的最低供暖室温却远高于设计室温,房间出现了较为严重的过热现象。因此,本研究所提出的基于BP神经网络的散热器面积设计模型能够有效缓解冬季室内过热的现象,降低能源消耗,同时最大限度减少供暖系统的投资成本。

Reducing the energy consumption of heating systems is highly needed to achieve energy saving and carbon reduction in the building sector,and the proper design of the radiator area is significant for the improvement of energy efficiency in heating systems,higher thermal comfort in heated rooms,and reduction of initial investments in systems.However,the traditional radiator design model based on steady-state heat balance usually neglects the thermal inertia of building envelopes,internal heat gains and others,which causes the oversized radiator.In this regard,a simulation database for different room types and heating operation conditions was built by means of building thermal simulation in this study.A new radiator design model based on BP neural network was developed,and its accuracy and applicability were comprehensively analyzed.Furthermore,the design effect of the model proposed was compared with that of the traditional radiator design model.Results show that the R~2 of this neural network model is higher than 0.724,and the MAE and RMSE are less than 0.533 m^(2) and 0.680 m^(2),respectively.For different climate zones,different types of radiators and different supply water temperatures,the proposed model can control the minimum indoor heating temperature within the range of 18~21℃.For traditional radiator design models,the room temperature is far higher,and experience overheating even in some rooms.In this sense,the radiator design model proposed in this study can alleviate the indoor overheating in winter,effectively reduce energy consumption,and minimize the investment cost of the heating system.