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作 者:王长浩 高红均[1] 周文毅 郭明浩[1] 刘俊勇[1] WANG Changhao;GAO Hongjun;ZHOU Wenyi;GUO Minghao;LIU Junyong(College of Electrical Engineering,Sichuan University,Chengdu 610065,Sichuan Province,China)
机构地区:[1]四川大学电气工程学院,四川省成都市610065
出 处:《电网技术》2024年第11期4427-4435,I0004,共10页Power System Technology
基 金:国家重点研发计划项目:“支撑20%新能源电量占比场景下的电网智能调度关键技术”(2022YFB2403400)。
摘 要:随着新能源装机容量与发电量占比的快速攀升,传统火电机组装机容量大幅降低,为平移新能源出力的随机性和波动性,迫切需要将负荷侧纳入调度优化。为此,提出一种考虑准线需求响应的高比例新能源电力系统调度模型。首先,构建考虑新能源出力存在极端出力和极端爬坡情况的不确定性场景集;其次,根据各节点负荷结构特点,刻画节点负荷响应能力差异,并加入正则化项对准线形状进行约束,在此基础上提出了考虑负荷响应能力的节点负荷准线模型;再次,将准线需求响应引入日前调度,建立高比例新能源电力系统两阶段调度优化模型;最后,通过对IEEE-30节点系统的算例分析表明,所提调度方法能够有效抑制新能源的不确定性,增强高比例新能源电力系统的新能源消纳能力和电力可靠供应能力。With the rapid increase of the installed capacity of new energy and the proportion of power generation,the installed capacity of traditional thermal power units has been greatly reduced.It is urgent to incorporate the load side into scheduling optimization to shift the randomness and volatility of new energy output.Therefore,this paper proposes a high-proportion new energy power system scheduling model considering customer directrix demand response.First,a high-proportion new energy output uncertainty scenario set is constructed considering the extreme output and climb of new energy output.Secondly,according to the load structure characteristics of each node,the difference in node load response capacity is described,and the regularization term is added to constrain the shape of the directrix.A nodal customer directrix model considering load response capacity is proposed on this basis.Thirdly,the linear demand response is introduced into day-ahead scheduling,and the two-stage scheduling optimization model of a high-proportion new energy power system is established.Finally,an example analysis of the IEEE-30 node system shows that the proposed scheduling method can effectively suppress the uncertainty of new energy and enhance the new energy consumption capacity and reliable power supply capacity of a high-proportion new energy power system.
分 类 号:TM721[电气工程—电力系统及自动化]
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