摘要
對電力業者來說，用戶之用電行為關係到用電負載之變化，也影響到供電成本的問題。以往對於用電行為之推估大多是屬於區域性的預測，並無針對單一用戶進行觀察。本研究主要針對多用戶之用電行為做叢集化之動作，期能以資料挖掘的方式比對單一用電戶間之用電行為，找出其間相似者，並將之分入同一叢集中。並在這之中找出適用於此種大量資料之挖掘動作的方法，使整個分析的動作可以用一種更快，而且亦足夠精確的方式進行。 在叢集化完成之後，為了能夠在有新用電戶加入時，能夠依其資料，將之分入適當的叢集中，本研究於實驗中也提到決策樹分類之做法，期能在尚未有用戶之用電行為發生時就能將之分入適當叢集。
並列摘要
Power usage is most concerned by power suppliers. Since it will affect the cost of power supply and peak load. Most of past research focused on forecasting peak load of a single area but didn’t care about single customer’s power usage. Our research focuses on multiple-customer-clustering. We try to compare every single customer’s power usage and find out most similar customers and assign them to same cluster. We also try to found a method that can make the clustering faster and still accurate. After clustering, we want to classification new customer into a cluster fit to them. We discuss the ability of using decision-tree to classify a new customer into a suitable cluster by using their base data.
參考文獻
[ALSS95] R. Agrawal, K.I. Lin, H.S. Sawhney and K. Shim, “Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases”, In Proc. Of the 21st VLDB Conference, pp. 490-501, 1995.
[CF99] Kin-pong Chan and Ada Wai-chee Fu, “Efficient Time Series matching by Wavelets”, In Proc. of 15th International Conference on Data Engineering, pp. 126-133, 1999.
[CW99] K.K.W. Chu and A.-C. Fu, “Fast Time-Series Searching with Scaling and Shifting”, In Proc. of 15th International Conference on Data Engineering, pp.126-133, 1999.
[FRM94] C.Faloutsos, M. Ranganathan, and Y. Manolopoulos, “Fast Subsequence Matching in Time-Series Databases”, In proc. Of the ACM SIGMOD Conference on Management of Data, May 1994.
[GK95] D. Goldin and P. Kanellakis, “On Similarity queries for time-series data: constraint specification and implementations”, In International Conference on the Principles and Practice of Constraint Programming, pp. 137-153, 1995.
延伸閱讀
- Chen, Y. C. (2012). 探勘時間間隔循序特徵樣式之相關研究 [doctoral dissertation, National Chiao Tung University]. Airiti Library. https://doi.org/10.6842/NCTU.2012.00302
- 吳嬑雯（2016）。電力用戶屬性關聯性之研究〔碩士論文，國立屏東科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0042-1805201714161595
- 侯承育（2016）。基於巨量資料分析電器使用時間與衰退曲線之關聯性〔碩士論文，國立中正大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0033-2110201614064534
- 張峻彬（2005）。Production Decline Analysis Using Concept of Time Series。石油季刊，41(2)，1-14。https://doi.org/10.30128/JP.200506.0001
- Wu, L. X. (2020). A Recurrent Neural Network Based Energy Management-Household Electricity Consumption Forecast [master's thesis, National Chiao Tung University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0030-1504202111211061