非侵入式負載監測系統(Non-Intrusive Load Monitoring system, NILMs)係指監測系統只需要安裝一組電壓及電流的量測器於電力入口端(Electrical Service Entry, ESE)，藉由分析於電力服務端所量測到的訊號與透過各種電力特徵的萃取及負載辨識技巧，即可得知系統下各負載的狀態及使用情形。
本文提出之負載辨識演算法係利用多組電力特徵並藉由串列式分析，透過濾波器的概念得到負載辨識結果。另外，對於台灣電壓波動導致電力特徵變化，本文提出線性化導納(Linearized Admittance)預測的方法，可有效改善電力波動的影響並大幅降低電力特徵資料庫的儲存空間。對於辨識工具的選擇，本文使用內積運算(Inner Product)作為系統辨識工具，可省略事前長時間的資料訓練即可達到與傳統辨識工具類似的辨識結果。最後，由各實驗案例的負載辨識結果可知，使用本文提出之辨識演算法，將可提高系統辨識率、改善電壓波動對電力特徵的影響、降低資料庫儲存空間、提升系統效率等優點。

Non-Intrusive load monitoring systems (NILMs) can determine the operating intervals and power consumptions of electrical loads in a system from measurements made at electrical service entry (ESE) point. In contrast to the conventional monitoring system, NILMs reduce sensor costs by installing sensors only at the ESE and identifies appliances by defining their power signature.

In this thesis, we proposed a new NILM method based on cascaded strategy to enhance the power signatures and is compared with the traditional methods, which use merely one characteristic, such as the real power for power signature. Moreover, we also proposed to use the linearized admittances to reduce the influence of voltage fluctuations on power signatures and the volume of database. For load identification, the inner product was proposed in this thesis. In contrast to the conventional identification tool, inner product can reduce the time for data training and obtain good results. Finally, as experimental results show, the proposed method yields better detection rate than the conventional methods.

參考文獻

[1] G.W Hart, “Nonintrusive appliance load monitoring,” Proc. IEEE, vol. 80, no. 12, pp. 1870-1891, Dec. 1992.
[2] C. Laughman, K. Lee, R. Cox, S. Shaw, S.B. Leeb, L. Norford, and P. Armstrong, “Power Signature Analysis,” IEEE Power & Energy Magzine, vol. 1, no. 2, pp. 56-63, March/April. 2003.
[3] A.I. Cole, and A. Albicki, “Data Extraction for Effective Non-Intrusice Identification of Residential Power Loads,” IEEE Conf. on Instrumentation and Measurement Technology, vol. 2, pp. 812-815, May. 1998.
[4] A.I. Cole, and A. Albicki, “Algorithm for Non-Intrusive Identification of Residential Appliances,” Proc. IEEE, vol.3, pp. 338-341, May/Jun 1998.
[5] J. Liang, S. K. K. Ng, G. Kendall, J. W. M. Cheng, “Load signature study  part I: basic concept, structure, and methodology,” IEEE Transactions on Power Delivery, vol. 25, no. 2, pp. ,551-560, April 2010
[6] J. Liang; Ng, S.; Kendall, G.; Cheng, J., "Load signature study IV part II: Disaggregation framework, simulation and applications," Power and Energy Society General Meeting, 2010 IEEE , vol., no., pp.1,1, 25-29 July 2010
[7] S.B. Leeb, J.L. Kirtley, Jr., M.S. LeVan, and J.P. Sweeney, “Development and validation of a transient event detector,” AMP Journal of Technology, vol. 3, Nov. 1993.
[8] S.B. Leeb, and J.L. Kirtley, Jr., “A multiscale transient event detector for nonintrusive load monitoring,” International Conference on Industrial Electronics, Control, and Instrumentation, Maui, Hawaii, pp. 354-359, Nov. 1993.
[9] Lam, H. Y.; Fung, G. S K; Lee, W. K., "A Novel Method to Construct Taxonomy Electrical Appliances Based on Load Signaturesof," Consumer Electronics, IEEE Transactions on , vol.53, no.2, pp.653,660, May 2007.
[10] Fernandes, R. A S; Nunes da Silva, I.; Oleskovicz, M., "Data Mining Applied to Identification of Harmonic Sources in Residential Consumers," Latin America Transactions, IEEE (Revista IEEE America Latina) , vol.9, no.3, pp.302,310, June 2011.
[11] A. Cole, and A. Albicki, “Nonintrusive Identification of Electrical Loads in a Three-Phase Environment Based on Harmonic Content,” IEEE Conf. on Instrumentation and Measurement Technology, vol.1, pp. 24-29, 2000.
[12] M. Akbar, and D.Z.A. Khan, “Modified Nonintrusive Appliance Load Monitoring For Nonlinear Devices,” IEEE International Multitopic Conference, pp. 1-5, Dec. 2007.
[13] Chang, H.; Lian, K.; Su, Y.; Lee, W., "Power Spectrum-Based Wavelet Transform for Non-Intrusive Demand Monitoring and Load Identification," Industry Applications, IEEE Transactions on , vol.PP, no.99, pp.1,1, 0, 2013.
[14] H.H. Chang, C.L. Lin, and H.T. Yang, “Load Recognition for Different Loads with the Same Real Power and Reactive Power in a Non-Intrusive Load-monitoring System,” Computer Supported Cooperative Work in Design, 12th International Conference on CSCWD 2008, 16-18, pp.1122-1127, April. 2008.
[15] H.H. Chang, C.L. Lin, and L.S. Weng, “Application of artificial intelligence and non-intrusive energy-managing system to economic dispatch strategy for cogeneration system and utility,” Computer Supported Cooperative Work in Design, 13th International Conference on CSCWD 2009, 22-24, pp.740-745, April. 2009.
[16] H.H. Chang, C.L. Lin, and L.S. Weng, “Applying a non-intrusive energy-management system to economic dispatch for a cogeneration system and power utility,” ELSEVIER Applied Energy, pp. 2335-2343, April. 2009.
[17] H.H. Chang, C.L. Lin, and J.K. Lee, “Load Identification in Nonintrusive Load Monitoring Using Steady-State and Turn-on Transient Energy Algorithms,” Computer Supported Cooperative Work in Design, 14th International Conference on CSCWD 2010, 14-16, pp.27-32, April. 2010.
[18] Y.H. Lin, and M.S. Tsai, “A Novel Feature Extraction Method for the Development of Nonintrusive Load Monitoring System based on BP-ANN,” International Symposium on Computer Communication Control and Automation 2010, 5-7, pp. 215-218, May. 2010.
[19] S.G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 674-693, Jul. 1989.
[20] S. Santoso, E.J Powers, W.M. Grady, and P. Hofmann, “Power Quality Assessment via Wavelet Transform Analysis,” IEEE Transactions on Power Delivery, pp. 924-930, Apr. 1996.
[21] Z.L. Gaing, “Wavelet-Based Neural Network for Power Disturbance Recognition and Classification,” IEEE Transactions on Power Delivery, pp. 1560-1568, Oct. 2004.
[22] 蘇易清，以小波轉換為主之非侵入式負載監測，碩士論文，國立台灣科技大學，台北，2012