含源荷相似度和曲线波动度约束的源荷储协调优化模型  

Source-load-storage Coordinated Optimization Model With Source-load Similarity and Curve Volatility Constraints

作　　者：周任军[1] 李斌[1] 黄婧杰 唐夏菲 彭院院 方绍凤 石亮缘 ZHOU Renjun;LI Bin;HUANG Jingjie;TANG Xiafei;PENG Yuanyuan;FANG Shaofeng;SHI Liangyuan(Hunan Province Collaborative Innovation Center of Clean Energy and Smart Grid(Changsha University of Science and Technology),Changsha 410004,Hunan Province,China;Guangzhou Power Supply Bureau Co.,Ltd.,Guangzhou 510620,Guangdong Province,China)

机构地区：[1]湖南省清洁能源与智能电网协同创新中心(长沙理工大学),湖南省长沙市410004 [2]广州供电局有限公司,广东省广州市510620

出　　处：《中国电机工程学报》2020年第13期4092-4101,共10页Proceedings of the CSEE

基　　金：国家自然科学基金项目(91746118,71331001);湖南省自然科学基金项目(2019JJ40302)。

摘　　要：电力系统源网荷储协调运行必将改变原始源荷曲线,为了定量刻画协调运行的效果,针对源荷曲线的数据分布特性与形态波动特征,提出一种新能源-负荷相似度指标和曲线波动度指标。改进时间序列相似性度量方法,求取负荷曲线与新能源出力曲线的数值、形态相似性距离,作为新能源-负荷相似度指标;计算曲线各相邻时段平均波动程度,作为曲线波动度指标。应用指标建立了含相似度与波动度指标约束的源荷协调两阶段优化模型。第一阶段,以上述两指标为约束,以传统机组运行成本最小、新能源与负荷的总调节量最小、新能源消纳量最大为目标,得到期望的总负荷曲线和新能源出力曲线;第二阶段,基于变分模态分解将原始曲线与期望曲线差值序列分解为低频序列与高频序列,作为能量型、功率型电池的充放电功率约束;以云储能与需求响应总调节成本最低为目标,将原始曲线调整为期望曲线。算例表明,所提指标和模型能有效减少弃风弃光、降低系统运行成本、改善各功率曲线性状,可为储能调度、需求侧管理以及源网荷储协调优化提供有效的理论支撑。The coordinated operation of the source-grid-load-storage of the power system will change the original curves of generation power and load power.In order to quantitatively describe the effect of coordinated operation,a renewable energy-load similarity and curve volatility indicator were proposed for the data distribution and morphological characteristics of source-load curves.The renewable energy-load similarity distance was obtained by using the improved time series similarity measure method to obtain the numerical value and morphological similarity distance of renewable energy and load curve.In order to calculate the average volatility of each adjacent period of metric curves,a curve volatility indicator was proposed.The indicators were applied to establish a two-stage optimization model of source-load coordination with similarity and volatility index constraints.In the first stage,under the above-mentioned index constraints,the goals were to minimize the operating cost of the traditional unit,minimize the total adjustment of renewable energy and load curves,and maximize the consumption of renewable energy.The expected total load and renewable energy output curves were obtained.In the second stage,based on the variational mode decomposition,the difference sequence of original curve and the expected curve were decomposed into low and high frequency sequence,which were used as the charging and discharging power constraints of energy-type and power-type.The total adjustment cost of cloud energy storage and demand responses were taken as the objective function,the original curve was adjusted to the desired curve.The illustrative example shows that the proposed indicators and models can effectively reduce wind and solar energy curtailment,reduce the system operating cost,improve the power curve characteristics,and provide effective theoretical support for storage scheduling,demand side management and the coordinated optimization of source-grid-load-storage.

关 键 词：源荷储协调 新能源消纳 源荷相似度指标 波动度指标 云储能 

分 类 号：TM732[电气工程—电力系统及自动化]