摘要
为提高电力系统在新能源出力波动与负荷不确定性下的低碳运行能力,设计了一种基于高斯混合模型和置信间隙决策理论的电力系统鲁棒调度策略。首先,为更加准确地描述源荷不确定性特征,对比了多种不确定性拟合方法,进而选取能够刻画多峰特征的高斯混合模型来构建源荷不确定性模型;然后,基于置信间隙决策理论构建以系统运行成本最小化为目标的鲁棒优化模型;最后,基于Python编程语言进行仿真验证。结果表明,该方法在新能源波动和负荷不确定性场景下表现出更优的经济性与鲁棒性,有效提升了系统的低碳调度能力。
In order to enhance the low-carbon operational capability of the power system under the fluctuations of renewable energy output and load uncertainty,this paper proposes a robust scheduling strategy for power systems based on Gaussian mixture model and confidence interval decision theory.First,in order to describe the characteristics of source-load uncertainty more accurately,the paper compares various uncertainty modeling methods and selects the Gaussian mixture model capable of characterizing multi-peak features to construct the source-load uncertainty model,and then,based on confidence interval decision theory,constructs a robust optimization model with the objective of minimizing system operating costs.Finally,the paper uses the Python programming language to perform simulation verification.The results show that the proposed method exhibits better economic efficiency and robustness under scenarios of renewable energy fluctuations and load uncertainty,effectively enhancing the system's low-carbon scheduling capability.
作者
张嘉蕾
罗建佳
刘正阳
唐芳芳
关燕鹏
ZHANG Jialei;LUO Jianjia;LIU Zhengyang;TANG Fangfang;Guan Yanpeng(School of Electric Power,Civil Engineering and Architecture,Shanxi University,Taiyuan Shanxi 030031,China;School of Automation and Software Engineering,Shanxi University,Taiyuan Shanxi 030031,China)
出处
《湖北电力》
2025年第2期64-70,共7页
Hubei Electric Power
基金
国家自然科学基金项目(项目编号:62473242)。
关键词
风光荷储
低碳经济调度
置信间隙
鲁棒优化
高斯混合模型
电力系统
新能源
wind-solar-load-storage
low-carbon economic scheduling
confidence interval
robust optimization
Gaussian mixture model
electric power system
renewable energy
