检索结果-南通市图书馆

Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

Energy Engineering 2024年第12期121卷 3617-3634页

作者： Inna Bilous dmytro Biriukov dmytro karpenko Tatiana Eutukhova Oleksandr Novoseltsev Volodymyr Voloshchuk Department of Heat and Alternative Power Engineering National Technical University of Ukraine“KPI”Kyiv03056Ukraine Department of Structural Transformation of the Fuel and Energy Complex General Energy Institute of NAS of UkraineKyiv03150Ukraine

This article focuses on the challenges ofmodeling energy supply systems for buildings,encompassing both methods and tools for simulating thermal regimes and engineering systems within *** the comfort of living or working in buildings often necessitates increased consumption of energy and material,such as for thermal upgrades,which consequently incurs additional economic *** is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions,considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in *** addition,it explores the methods and mechanisms for modeling the operating modes of electric boilers used to collectively improve energy efficiency and indoor climatic *** the developed mathematical models,the study examines the dynamic states of building energy supply systems and provides recommendations for improving their *** dynamic models are executed in software environments such as MATLAB/Simscape and Python,where the component detailing schemes for various types of controllers are ***,controllers based on reinforcement learning(RL)displayed more adaptive load level *** RL-based controllers can lower instantaneous power usage by up to 35%,reduce absolute deviations from a comfortable temperature nearly by half,and cut down energy consumption by approximately 1%while maintaining *** the energy source produces a constant energy amount,the RL-based heat controllermore effectively maintains the temperature within the set range,preventing *** conclusion,the introduced energydynamic building model and its software implementation offer a versatile tool for researchers,enabling the simulation of various energy supply systems to achieve optimal energy efficiency and indoor climate control in buildings.

关键词： Building energy management building heating system dynamic modeling reinforcement learning energy efficiency comfortable temperature

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：