摘要
随着可再生能源的快速发展,光伏发电和风力发电在综合能源系统(IES)中起着重要作用,然而它们的随机性和不稳定性需要通过储能系统来补偿。现有的IES优化配置主要集中在经济性分析,并且多数只基于确定参数场景进行优化配置。针对“双碳”目标下的建筑IES进行了单目标和多目标优化研究,考虑IES全生命周期经济成本、碳排放和绿电比例3个目标,基于不确定性参数场景,使用非支配排序遗传算法二代(NSGA-Ⅱ)结合熵权-TOPSIS法进行优化。研究结果表明,IES可以显著减少建筑能源消耗、成本和碳排放,提高建筑绿电比例,使用氢储能的IES对比基准建筑,节约年成本28.47%,减少年碳排放124.01%,提高绿电比例53.39%,比使用蓄电池的IES更加低碳经济。
With the rapid development of renewable energy,photovoltaic(PV)power generation and wind power generation play an important role in the transition to clean energy consumption in buildings.However,the randomness and instability of PV and WT need to be compensated by energy storage systems.The existing optimization configuration for the integrated energy system(IES)mainly focused on economic analysis,and most of them conducted studies based on deterministic parameters.Three objectives of IES(i.e.,life cycle cost,carbon emission and green power ratio)are considered for single objective optimization and multi-objective optimization by using Non-dominated Sorting Genetic Algorithm II(NSGA-II)combined with entropy weight-TOPSIS,and the optimization is conducted based on uncertainty parameters.The results show that the building energy consumption,costs and carbon emissions can be reduced by IES optimization,and the green power ratio in buildings can be increased.Compared with the benchmark building,the annual cost of 28.47%can be saved,the annual carbon emissions of 124.01%can be reduced,and the green power ratio of 53.39%can be increased in the IES using hydrogen energy storage.In addition,the IES using hydrogen energy storage is demonstrated to be more economic and lower-carbon than IES using batteries.
作者
吝佳凯
周奕捷
鲁月红
卢承玉
王栋
黄志甲
LIN Jiakai;ZHOU Yijie;LU Yuehong;LU Chengyu;WANG Dong;HUANG Zhijia(School of Civil Engineering and Architecture,Anhui University of Technology,Maanshan 243000,Anhui,China)
出处
《建筑节能(中英文)》
2025年第10期17-23,112,共8页
Building Energy Efficiency
关键词
综合能源系统
碳排放
多目标优化
不确定性参数
熵权-TOPSIS
integrated energy system
carbon emissions
multi-objective optimization
uncertainty parameters
entropy-weighted TOPSIS
