摘要
研究风电场内的机组组合优化调度,可提高机组的运行效率,改善风电场有功输出,降低系统运行成本。首先,对风电机组的历史运行数据进行分析,提出风速和机组输出功率的时段动态概率分布综合建模方法,并根据获得的时段动态概率分布模型得到机组的动态运行特征矩阵;其次,利用模糊C均值算法对风电场内机组进行动态聚类分析,在各个调度时段内将机组划分为常规机组和调度机组;最后,以风电机组疲劳损伤量最小为目标,建立基于风电机组动态分类的风电场优化调度模型。通过算例分析,该模型的有效性得到验证。
Integrating wind power that contains uncertainty and volatility in a large scale would bring great challenges to the operation and scheduling of power systems.The research on the unit commitment problem inside a wind farm contributes to improving operating efficiency of wind turbines,increasing output power of wind farm,and reducing the operation cost.Firstly,historical data of wind turbines is analyzed,based on which a comprehensive modeling method is proposed.Then,through the method dynamic probability distribution model can be built,based on which the characteristic matrix of wind turbine that changes over time is formulated.Secondly,the fuzzy C-means(FCM)clustering algorithm is used to classify wind turbines within a wind farm dynamically.Considering classification,the turbines are further labeled as conventional and dispatchable in different periods.At last,optimal scheduling model of a wind farm is proposed with the objective of minimizing fatigue damage of wind turbines.The effeteness of the proposed model is verified by the case study.
作者
李茜
毛雅铃
王武双
曲广龙
张安安
Li Qian;MaoYaling;Wang Wushuang;Qu Guanglong;Zhang An’an(College of Electrical Engineering and Information,Southwest Petroleum Universit,Chengdu 610500,China;State Grid Chengdu Power Supply Company,Chengdu 610042,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2021年第6期419-424,共6页
Acta Energiae Solaris Sinica
基金
国家重点研发计划(2017YFE0112600)
西南石油大学青年教师“过学术关”项目(201699010069)。
关键词
风电
风电机组
聚类
疲劳损伤
概率密度函数
优化调度
wind power
wind turbine
clustering
fatigue damage
probability density function
optimization dispatch
