检索结果-南通市图书馆

stochastic Programming for Hub Energy Management Considering Uncertainty Using two-point estimate method and Optimization Algorithm

引用

Computer Modeling in Engineering & sciences 2023年第12期137卷 2163-2192页

作者： Ali s.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PsO),and salp swarm algorithm(ssA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： stochastic energy hub scheduling energy profit uncertainty hong’s two-point estimate method improved artificial rabbits optimization

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：