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作 者:张荣强 夏伟敏 王丹 张淼 张瑞恒 陈宁 孙佳禾 徐琴 ZHANG Rongqiang;XIA Weimin;WANG Dan;ZHANG Miao;ZHANG Ruiheng;CHEN Ning;SUN Jiahe;XU Qin(State Grid ZTE Corporation Co.,Ltd.,Beijing 100053,China;Beijing Zhongxing Property Management Co.,Ltd.,Beijing 100032,China;Jiangsu Lianhong Smart Energy Co.,Ltd.,Nanjing 210046,China)
机构地区:[1]国网中兴有限公司,北京100053 [2]北京中兴物业管理有限公司,北京100032 [3]江苏联宏智慧能源股份有限公司,江苏南京210046
出 处:《粘接》2024年第9期124-127,共4页Adhesion
摘 要:实施能源控制,降低化工材料企业能源消耗对企业实施转型升级,提升企业市场竞争力具有至关重要的意义。对化工企业厂房空调系统进行了分析,将空调系统能效比作为节能智能控制的目标。采用BAS对BP神经网络初始权值与偏置进行优化,得到了BAS-BP模型,通过该模型对厂房空调系统实施节能智能控制。将该节能智能控制模型应用于某化工材料企业中,通过520次迭代,厂房内温度区域稳定,为24.5℃,同时得到了各影响因素的值。这对化工材料企业厂房空调节能智能控制提供了数据支撑。Implementing energy control and reducing energy consumption in chemical material enterprises is of crucial significance for the transformation and upgrading of enterprises,as well as enhancing their market competitiveness.An analysis was conducted on the air conditioning system of chemical enterprise factory buildings,with the energy efficiency ratio of the air conditioning system as the goal of energy-saving intelligent control.The initial weights and biases of the BP neural network were optimized using BAS,resulting in the BAS-BP model.Through this model,energy-saving intelligent control was implemented for the factory air conditioning system.The energy-saving intelligent control model was applied to a chemical material enterprise.After 520 iterations,the temperature area inside the factory remained stable at 24.5℃,and the values of various influencing factors were obtained.This provides data support for energy-saving intelligent control of air conditioning in chemical material enterprises’factory buildings.
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