摘要
在海岛可再生能源替代与电动汽车技术大规模应用的背景下,为解决偏远海岛居民的用电需求,提出了计及需求响应的电动汽车接入海岛微电网群的优化方法。首先,根据实际监测数据集对电动汽车充电行为建模,对比多种分布形式的联合评价和指标,得到拟合较好的概率分布函数。其次,选取多个海岛构成低碳化海岛能源系统,在考虑可再生能源渗透率和用户满意度的前提下,建立了以海岛微电网群的经济性和环保效益最优为目标的微电网群优化模型,利用蜘蛛蜂优化(spider wasp optimization,SWO)算法求解。最后,以浙江某海岛群为例进行验证,算例结果表明,所提海岛微电网群优化模型能够在满足可再生能源高渗透率的场景下,有效降低系统成本,更具经济性。
With the background of the island renewable energy substitution and the large-scale application of electric vehicle technology,then to solve the electricity demand of remote island residents,an optimization method for electric vehicle access to the island microgrid cluster is proposed.First,the charging behavior of electric vehicles is modelled based on an actual monitoring data set,a joint evaluation and indices of various distribution forms are compared,and a well-fitting probability distribution function is obtained.Second,this paper selects multiple islands and constructs a low-carbon island energy system.Considering renewable energy penetration and user satisfaction,the optimization model of the microgrid cluster is established,with the aim of optimizing the economic and environmental benefits of the cluster.The spider wasp optimization(SWO)algorithm is used for analysis.Finally,taking an island cluster in Zhejiang as an example,the calculations show that the proposed island microgrid cluster optimization model can effectively reduce the system cost and be more economical when there is a high penetration rate of renewable energy.
作者
黄冬梅
吕嘉欣
时帅
李媛媛
傅望安
王晓亮
HUANG Dongmei;LÜJiaxin;SHI Shuai;LI Yuanyuan;FU Wang’an;WANG Xiaoliang(School of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 201306,China;School of Electric Power Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Clean Energy Branch of Huaneng(Zhejiang)Energy Development Co.,Ltd.,Hangzhou 310014,China;East China Sea Area and Island Center,MNR,Shanghai 200136,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2024年第9期88-98,共11页
Power System Protection and Control
基金
国家重点研发计划项目资助(2021YFC3101602)
华能集团总部科技项目“HNKJ20-H66基于深远海的海上风电选址和支撑技术研究”资助。
关键词
海岛微电网群
电动汽车
需求响应
蜘蛛蜂优化算法
island microgrid cluster
electric vehicle
demand response
spider wasp optimization(SWO)
