【摘要】：家電負(fù)荷識別是智能用電的重要環(huán)節(jié),傳統(tǒng)侵入式負(fù)荷監(jiān)測具有成本高、安裝維護(hù)復(fù)雜的缺點(diǎn),因此以非侵入式負(fù)荷監(jiān)測為基礎(chǔ)研究家電負(fù)荷識別算法。結(jié)合系統(tǒng)辨識的基本原理和方法,以穩(wěn)態(tài)電流、穩(wěn)態(tài)電壓為特征,提出一種基于局部平均分解(LMD)和模型匹配的家電負(fù)荷識別算法。通過預(yù)先獲取用電網(wǎng)絡(luò)中各負(fù)荷的穩(wěn)態(tài)數(shù)據(jù),構(gòu)建線性和非線性模型庫。利用LMD算法將混合信號分解為單個(gè)負(fù)荷的用電數(shù)據(jù),通過預(yù)篩選確定分離數(shù)據(jù)所屬模型庫,根據(jù)模型匹配原則進(jìn)行負(fù)荷識別。仿真結(jié)果表明,所提算法可以準(zhǔn)確識別出各負(fù)荷的運(yùn)行狀態(tài),運(yùn)算效率高,并能有效應(yīng)對用電網(wǎng)絡(luò)中有新負(fù)荷加入的情況。
[Abstract]:Load identification of household appliances is an important part of intelligent power consumption. Traditional invasive load monitoring has the disadvantages of high cost and complex installation and maintenance. Therefore, based on non-invasive load monitoring, the load identification algorithm of household appliances is studied. Combined with the basic principles and methods of system identification, a load identification algorithm based on local average decomposition (LMD) and model matching for household appliances is proposed, which is characterized by steady current and steady voltage. The linear and nonlinear model libraries are constructed by obtaining the steady state data of each load in the power network in advance. The mixed signal is decomposed into the electric data of a single load by LMD algorithm. The model base of the separated data is determined by pre-screening, and the load identification is carried out according to the principle of model matching. The simulation results show that the proposed algorithm can accurately identify the running state of each load, has high computational efficiency, and can effectively deal with the situation where new loads are added to the power network.
【作者單位】： 華北電力大學(xué)電氣與電子工程學(xué)院;國網(wǎng)物資有限公司;
【基金】：中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金資助項(xiàng)目(2016MS13)~~
【分類號】：TM714

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