本文關(guān)鍵詞： 非侵入負荷監(jiān)測 負荷分解 負荷辨識 欠定求解 特征濾波　出處：《電力系統(tǒng)自動化》2017年20期 　論文類型：期刊論文

【摘要】：通過非侵入采集模式下電流信號的欠定求解實現(xiàn)了負荷分解,獲取了各獨立負荷的完整電流,在負荷分解基礎(chǔ)上實現(xiàn)了狀態(tài)辨識。利用居民用戶的負荷操作習慣將難以求解的欠定問題優(yōu)化建模,轉(zhuǎn)化為一維欠定問題,將求解模型建立為單位時間間隔僅從采集信號中分離兩路信號。依據(jù)電流頻域信號的稀疏性通過兩步迭代收縮閾值算法得到最優(yōu)解,使每個投入運行的負荷均可獨立分解。通過先驗方式獲取用電網(wǎng)絡(luò)各負荷的特征電流形成特征濾波器組,對分解電流進行頻域濾波,通過對濾波后頻率分量的量化判決實現(xiàn)負荷辨識。利用實際采集的用電數(shù)據(jù)驗證了算法的有效性,能夠有效實現(xiàn)負荷分解,并準確判斷負荷狀態(tài)。
[Abstract]:The load decomposition is realized by solving the underdetermined current signal in the non-invasive acquisition mode, and the complete current of each independent load is obtained. On the basis of load decomposition, the state identification is realized. By using the load operation habits of resident users, the difficult underdetermined problem is modeled and transformed into one-dimensional underdetermined problem. The solution model is established as a unit time interval to separate only two signals from the collected signal, and the optimal solution is obtained by two-step iterative shrinkage threshold algorithm according to the sparsity of the current frequency domain signal. Each load in operation can be decomposed independently. The characteristic current of each load of power network is obtained by a prior method to form a characteristic filter bank, and the decomposition current is filtered in frequency domain. The load identification is realized by quantifying the frequency component after filtering, and the validity of the algorithm is verified by the actual electric data collected. The load decomposition can be realized effectively and the load state can be judged accurately.
【作者單位】： 華北電力大學(xué)電氣與電子工程學(xué)院;國網(wǎng)江蘇省電力公司電力科學(xué)研究院;
【基金】：中央高�；究蒲袠I(yè)務(wù)費專項資金資助項目(2016MS13) 國家重點研發(fā)計劃資助項目(2016YFB0901104)~~
【分類號】：TM714
【正文快照】： 上網(wǎng)日期:2017-08-08。0引言智能電網(wǎng)的發(fā)展使傳統(tǒng)電力工業(yè)向高度集約化、知識化、技術(shù)化方向轉(zhuǎn)變,需求側(cè)管理的重要性日益凸顯[1]。通過需求側(cè)管理優(yōu)化低壓用戶端,實現(xiàn)有效的負荷管理,能夠在合理有效用電的基礎(chǔ)上減少電量消耗和電力需求,提高電能利用效率[2]。實現(xiàn)用電的全面，

本文編號：1442609