摘要
发展农村可再生能源,解决供给随机波动所导致的供需匹配问题至关重要。在经济可行的范围内,现有供需匹配提升作用基本已被发挥至上限,柔性用能负荷调节是从需求侧解决问题的革命性新方法。该文基于关中农村实地调研数据,分析不同类型家庭夏季用能特征,在充分考虑柔性用能负荷的前提下,建立求解以经济性与舒适性为目标的农村家庭柔性用能负荷多目标优化调度模型。结果表明:1)关中农村家庭根据用能特征可分为独居老年家庭(第一类)、三代同堂家庭(第二类)、居家青年家庭(第三类)以及务工青年家庭(第四类)。2)峰谷电价下,第二类家庭负荷调节潜力最大,用电成本削减比例最高为19.5%,不舒适指数增加比例最高为46.3%;第四类家庭负荷调节潜力最小,用电成本削减比例最高为12.3%,不舒适指数增加比例最高为17.8%。3)对于可平移类柔性负荷,第一、二、三类家庭可调节潜力均较大;对于可中断类柔性负荷,第一类家庭可调节潜力最大;对于可削减类柔性负荷,第二类家庭可调节潜力最大。
It is crucial to develop rural renewable energy and solve the supply and demand matching problem caused by random supply fluctuations.Within the scope of economic feasibility,the existing supply and demand matching has been basically played to the upper limit.Flexible energy load regulation is a revolutionary new method to solve the problem from the demand side.Based on the field survey data in Guanzhong countryside,this study analyzes the energy consumption characteristics of different types of households in summer,and establishes a multi-objective optimization scheduling model with the goal of economy and comfort under the premise of fully considering the flexible energy use load.The results show that:i)According to the characteristics of energy use,rural families in Guanzhong can be divided into Single Elderly Families(TypeⅠ),Three Generations of Family(TypeⅡ),Home Youth Families(TypeⅢ)and Working Youth Families(TypeⅣ);ii)Under peak-valley electricity price,the second type of household has the greatest potential for load regulation,with a reduction in electricity cost up to 19.5%and an increase in discomfort index up to 46.3%;The fourth type of household load adjustment potential is minimum,and the reduction rate of electricity cost is only up to 12.3%,and the discomfort index increase rate is only up to 17.8%;iii)For shiftable flexible loads,the first three types of households have relatively great adjustable potential;for interruptible flexible loads,the first type of household has the greatest adjustable potential;for curtailable flexible loads,the second type of household has the greatest adjustable potential.
作者
刘艳峰
杨燕子
罗西
Liu Yanfeng;Yang Yanzi;Luo Xi(State Key Laboratory of Green Building in Western China,Xi’an University of Architecture&Technology,Xi’an 710055,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2023年第8期110-118,共9页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(U20A20311
52008328)。
关键词
需求侧管理
多目标优化
遗传算法
柔性负荷
家庭特征
K-均值聚类
demand-side management
multi-objective optimization
genetic algorithms
flexible load
family characteristics
Kmeans clustering