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作 者:杨林峰[1,2] 任宇晨 李捷[3] 雷宁 潘珊珊 YANG Linfeng;REN Yuchen;LI Jie;LEI Ning;PAN Shanshan(School of Computer and Electronic Information,Guangxi University,Nanning 530004,China;Guangxi Key Laboratory of Multimedia Communications and Network Technology,Guangxi University,Nanning 530004,China;School of Big Data,Guangxi Vocational and Technical College,Nanning 530226,China;State Grid Ningxia Eletric Power Yinchuan Powor Supply Company,Yinchuan 750001,China;School of Science,Guangxi University of Science and Technology,Liuzhou 545616,China)
机构地区:[1]广西大学计算机与电子信息学院,广西南宁530004 [2]广西大学广西多媒体通信与网络技术重点实验室,广西南宁530004 [3]广西职业技术学院大数据学院,广西南宁530226 [4]国网宁夏电力有限公司银川供电公司,宁夏银川750001 [5]广西科技大学理学院,广西柳州545616
出 处:《广西大学学报(自然科学版)》2023年第3期631-640,共10页Journal of Guangxi University(Natural Science Edition)
基 金:国家自然科学基金项目(51767003);广西自然科学基金项目(2020GXNSFAA297173,2020GXNSFDA238017,2021GXNSFBA075012);广西中青年教师基本能力提升项目(2019KY1210,2020KY08005)。
摘 要:为了最小化微电网运行成本,提出了一个考虑微电网中分布式能源不确定性的两阶段半预期鲁棒优化模型。通过考虑未来部分时段的信息,半预期鲁棒优化模型尽可能地接近实际调度情况。分布式能源的不确定性被描述为由盒式约束和控制集合大小约束所结合产生的不确定集合。模型中的决策变量使用线性决策规则进行线性逼近,将两阶段鲁棒优化模型转换为多阶段鲁棒模型。最后使用约束生成算法有效地求解多阶段鲁棒模型。对微电网配电系统进行了仿真,证明所提出的半预期鲁棒优化模型的正确性和有效性。结果表明,充分考虑分布式能源不确定性的半预期鲁棒优化模型与传统的鲁棒优化模型相比,更具有经济性和鲁棒性。A two-stage semi-anticipated robust optimization model that takes into account the uncertainty of distributed energy in microgrid is proposed to minimize microgrid operating costs.The semi-anticipated robust model is made as close as possible to the actual scheduling situation by considering information about future partial periods.Uncertainty of distributed energy sources is described as an uncertain set produced by box constraints and a control set size constraint.The dispatch decision in the model is linearly approximated using the linear decision rule,which can convert a two-stage robust model into a multi-stage robust model.The constraint generation algorithm is used to solve the multi-stage optimization model more effectively.The simulation of the microgrid distribution system is carried out to prove the correctness and effectiveness of the proposed two-stage semi-anticipated robust optimization model.The results show that the semi-anticipated robust optimization model which fully regards the uncertainty of distributed energy sources is more economical and robust compared to the traditional robust optimization model.
分 类 号:TM734[电气工程—电力系统及自动化]
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