考虑用户综合需求的多模式家庭能源调度策略研究  

Multi-model Home Energy Scheduling Strategy ConsideringUsers’ Comprehensive Demand

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作  者:刘魁星 游伟洁 黄一凯 LIU Kuixing;YOU Weijie;HUANG Yikai(School of Architecture,Tianjin University,Tianjin 300072,China)

机构地区:[1]天津大学建筑学院,天津300072

出  处:《建筑节能(中英文)》2025年第4期75-82,119,共9页Building Energy Efficiency

基  金:青海省科技计划资助项目(2023-ZJ-738);建筑安全与环境国家重点实验室开放基金资助项目(BSBE2022-01)。

摘  要:家庭能源调度系统作为智能电网的重要组成部分,对实现居民端电网需求响应目标至关重要。现阶段针对家庭能源调度策略研究目前主要集中在优化调度目标及模型求解计算方法上。考虑到家庭能源的使用中用户的舒适度会受到影响,应综合用户舒适度与成本,建立不同模式下的调度策略,以提高优化调度策略的灵活性。对此,提出一种考虑用户综合需求的多模式家庭能源调度策略,以用能舒适度、用电费用最低及二者兼顾的智能模式为目标函数,在给定的约束条件下,通过优化的麻雀搜索算法进行求解,为上述问题提供了解决方案。将其应用于张家口某民用住宅,在已知用户使用习惯及给定的约束条件下,相较未进行调度而言,在能耗及用能舒适度上有较好表现。研究结果验证了该方法在调度过程中兼顾用户节能需求及舒适度需求的潜力。As an important part of the smart grid,home energy scheduling system is crucial for achieving the demand response objectives of the residential grid.At this stage,the research on home energy scheduling strategy is currently focused on optimizing the scheduling objectives and model solving calculation methods.Considering that the comfort of users will be affected in the use of home energy,the scheduling strategies under different modes should be established by integrating the comfort and cost of users to improve the flexibility of the optimal scheduling strategy.In this regard,this paper proposes a multi-mode home energy scheduling strategy that considers users’comprehensive needs,with the intelligent mode of energy comfort,electricity cost minimization and both as the objective function,followed by an optimized Sparrow Search Algorithm(SSA)hunder the given constraints,which provides a solution to the above problem.Applied to a residential house in Zhangjiakou,the method shows better performance in terms of energy consumption and energy comfort compared to non-scheduling with known user habits and given constraints.The results validate the potential of the method to balance users’energy efficiency and comfort needs during the scheduling process.

关 键 词:家庭能源 能源调度 用能舒适度 

分 类 号:TU831.3[建筑科学—供热、供燃气、通风及空调工程]

 

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