电力建设
電力建設
전력건설
ELECTRIC POWER CONSTRUCTION
2015年
8期
84-88
,共5页
郭昆亚%熊雄%金鹏%孙芊%井天军
郭昆亞%熊雄%金鵬%孫芊%井天軍
곽곤아%웅웅%금붕%손천%정천군
智慧城市%负荷特性%分类与综合%量子粒子群算法%模糊聚类
智慧城市%負荷特性%分類與綜閤%量子粒子群算法%模糊聚類
지혜성시%부하특성%분류여종합%양자입자군산법%모호취류
smart city%load characteristic%classification and synthesis%quantum particle swarm algorithm%fuzzy clustering
为解决应用传统模糊C均值( fuzzy C ̄means, FCM)算法进行电力负荷模式提取时存在的对初始聚类中心敏感、聚类数目不易确定等问题,构建表征聚类效果的目标函数,并针对传统智能寻优算法易收敛、陷入局部最优等缺陷,采用一种量子编码的粒子群算法进行全局寻优以确定最佳聚类中心及分类数目,在确定最佳聚类中心及聚类数目基础上,构建能够全面反映各类型负荷的特征向量,最后通过与传统FCM算法下的计算结果进行对比,验证了该方法在用电识别方面的有效性及正确性。
為解決應用傳統模糊C均值( fuzzy C ̄means, FCM)算法進行電力負荷模式提取時存在的對初始聚類中心敏感、聚類數目不易確定等問題,構建錶徵聚類效果的目標函數,併針對傳統智能尋優算法易收斂、陷入跼部最優等缺陷,採用一種量子編碼的粒子群算法進行全跼尋優以確定最佳聚類中心及分類數目,在確定最佳聚類中心及聚類數目基礎上,構建能夠全麵反映各類型負荷的特徵嚮量,最後通過與傳統FCM算法下的計算結果進行對比,驗證瞭該方法在用電識彆方麵的有效性及正確性。
위해결응용전통모호C균치( fuzzy C ̄means, FCM)산법진행전력부하모식제취시존재적대초시취류중심민감、취류수목불역학정등문제,구건표정취류효과적목표함수,병침대전통지능심우산법역수렴、함입국부최우등결함,채용일충양자편마적입자군산법진행전국심우이학정최가취류중심급분류수목,재학정최가취류중심급취류수목기출상,구건능구전면반영각류형부하적특정향량,최후통과여전통FCM산법하적계산결과진행대비,험증료해방법재용전식별방면적유효성급정학성。
In allusion to such defects as sensitive to initial clustering center and not convenient to determine clustering number during utilizing traditional fuzzy C ̄Means ( FCM) algorithm to extract power load patterns, this paper constructed objective function to reflect clustering effect, and used a quantum particle swarm algorithm for global optimization to determine the optimal clustering center and classification aiming at the defects of traditional intelligent optimization algorithm, such as easy convergence, falling into local optimum, etc. After determining the optimal clustering center and clustering number, the characteristics vector was constructed to fully reflect each kind of load. At last, by compared with the calculated results of traditional FCM algorithm, the effectiveness and correctness of the proposed algorithm in electricity recognition were verified.