Symbolic Aggregate Approximation (SAX) Based Customer Baseline Load (CBL) Method

摘要

Various Demand Response (DR) programs are operated around the world to reduce energy use for home and commercial building. For example, Smart bills and in-home displays are used to save energy. Technical issue associated with the calculation of Customer Baseline Load (CBL) may arise for various reasons. This paper presents a Symbolic Aggregate Approximation (SAX) based CBL method for handling anomalous smart meter data to improve the accuracy of the CBL calculation. In this paper, similar electricity consumers which show similar power usage patterns, are identified, and the anomalous smart meter data is adjusted by using power usage patterns of similar consumers. A case study is presented to show the effectiveness of the proposed Symbolic Aggregate Approximation (SAX) based CBL method.