摘要
为了考虑风光不确定性给微网运行带来的风险,针对独立型微网的容量优化配置,提出一种基于生成对抗网络(generative adversarial network,GAN)场景模拟和条件风险价值(conditional value at risk,CVaR)的容量随机优化配置模型。首先利用GAN模拟大量风光出力场景,再用K-medoids聚类进行消减得到若干典型场景;其次,以微网供电可靠性为约束,以经济性和可再生能源利用率为目标函数,通过CVaR度量因风光资源不确定性给微网系统带来的运行风险,并将其以平均风险损失的形式与目标函数相结合,构建微网电源容量随机优化配置模型;最后,采用电源损失风险和负荷风险损失指标对配置结果进行评价。仿真算例表明,相比于仅采用典型年风光资源数据进行配置的传统方法,文中提出的模型对于规划周期内可能出现的运行场景适应性更好。
A stochastic optimization model based on scenario simulation using generative adversarial network(GAN)and conditional value at risk(CVaR)is proposed for stand-alone microgrid capacity configuration for the purpose of considering the operation risks resulted from the uncertainties of wind and solar resources.Firstly,we use GAN to generate a lot of scenarios of wind and solar outputs.Several typical scenarios are obtained through scenario reduction using K-medoids algorithm.Secondly,the power supply reliability is taken as a constraint,the economy and renewable energy utilization are regarded as objective functions,the operation risks caused by the uncertainties of wind and solar resources are measured by the CVaR.A stochastic capacity configuration optimization model is proposed by combining the risks(i.e.in the form of average risk loss)and the above objective functions.Finally,the results are evaluated with two risk indexes of power loss and load loss.Simulation results show that compared with the traditional methods performing capacity configuration only using wind and solar resource data in typical years,the proposed model can better adapt to possible operation scenarios during the planning period.
作者
李康平
张展耀
王飞
姜利辉
张晶晶
俞伊丽
米增强
LI Kangping;ZHANG Zhanyao;WANG Fei;JIANG Lihui;ZHANG Jingjing;YU Yili;MI Zengqiang(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China;State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source(North China Electric Power University),Baoding 071003,Hebei Province,China;Hebei Key Laboratory of Distributed Energy Storage and Micro-grid(North China Electric Power University),Baoding 071003,Hebei Province,China;China Resources Power Holdings Company Limited,Shenzhen 518001,Guangdong Province,China;Songjiang Electric Power Supply Company,State Grid Shanghai Electric Power Company,Songjiang District,Shanghai 201600,China)
出处
《电网技术》
EI
CSCD
北大核心
2019年第5期1717-1725,共9页
Power System Technology
基金
国家自然科学基金项目(51577067)
北京市自然科学基金项目(3162033)
新能源电力系统国家重点实验室开放课题(LAPS18008)
国家电网公司科技项目(NY7116021
kjgw2018-014)
中央高校基本科研业务费项目(2018QN077)~~
