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作 者:张棠茜 何宇[1] 蒋慕凝 秦廷翔 朱兆强 陈泽霜 ZHANG Tangqian;HE Yu;JIANG Muning;QIN Tingxiang;ZHU Zhaoqiang;CHEN Zeshuang(The Electrical Engineering College,Guizhou University,Guiyang 550025,China;Power China Guizhou Engineering Co.,Ltd.,Guiyang 550002,China)
机构地区:[1]贵州大学电气工程学院,贵州贵阳550025 [2]中国电建集团贵州工程有限公司,贵州贵阳550002
出 处:《电子科技》2024年第10期40-47,共8页Electronic Science and Technology
基 金:黔科合支撑([2022]一般014)。
摘 要:为提高风电并网能力并降低碳排放,文中提出了一种考虑碳交易和电动汽车的两阶段分布鲁棒低碳经济调度模型。引入碳交易成本,通过电动汽车的储能技术和风力发电的协同配合来降低系统的碳排放量,提高系统对风电的消纳能力。考虑到风电的不确定性,利用历史风电出力数据的矩信息,采用基于通用矩不确定性的分布鲁棒优化方法,建立分布鲁棒模糊集以刻画不确定的风电出力特性。利用对偶原理和线性决策规则将分布鲁棒模型转换为二次规划模型,并通过CPLEX对模型进行求解。实验结果表明,所提方法使风电消纳量提高了11.35%,碳排放量减少了1579 t,验证了两阶段分布鲁棒模型的有效性和优越性。In order to enhance the consumption capacity of wind power and reduce carbon emissions,this study proposes a two-stage distributionally robust low-carbon economic dispatch model that takes into account carbon trading and electric vehicles.Carbon trading costs are introduced in the proposed study,and the cooperation between electric vehicle energy storage and wind power generation is utilized to reduce the system's carbon emissions and to increase the wind power consumption capacity.Considering the uncertainty of wind power,a distributionally robust optimization method based on the general moment uncertainty is established.The fuzzy set of distributionally robust is established using the moment information of the historical wind power output data that can be obtained to characterize the uncertain wind power output characteristics.The distributionally robust model is transformed into a quadratic programming model using duality and linear decision rules,and the model is solved through CPLEX.Experimental results show that the wind power consumption capacity increases by 11.35%and carbon emissions decrease by 1579 t under the proposed method,which verifies the effectiveness and superiority of the two-stage distributionally robust model.
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