Electric load information system based on non-intrusive power monitoring

Abstract

Obtaining high quality information economically and reliably is always a difficult objective to achieve. The electric power industry and consumers recently face many challenges, such as deregulation, autonomous power systems and power quality. The knowledge of the nature and state of the power systems will undoubtedly be the key in meeting these challenges. The Non-Intrusive Power Monitor is a novel attempt to collect such information with a minimal physical installation. Raw voltage and current are measured at a single location to yield harmonic power signals. They typically carry the fingerprints of the electric loads present in a system, and their analysis can produce such information as the operational and diagnostic status of the loads. The power signals can also be used for the system identification, parameter estimation and energy consumption optimization study. In this research, the power signals are mostly modeled as stochastic processes and various detection, estimation and pattern recognition algorithms are developed to extract desired information. A constant load status identifier is developed in this thesis which can identify the ON and OFF status of electric loads, both from their steady-state power consumptions and transient patterns. The identifier can also classify multiple load events occurring at a same time and estimate states without load events. The power consumed by a variable speed drive is also estimated using the correlations between the fundamental powers and higher harmonic powers. The harmonic signal generated by the imbalance of a rotating machine is estimated to monitor the drive, i.e. its speed and magnitude of the imbalance. The algorithms are thoroughly tested using the data collected at real buildings, and some of them are implemented on-line.

(cont.) This thesis focuses on developing mathematical models and signal processing algorithms for the customers at the end of the AC distribution system. Its results will directly benefit the developments of a ubiquitous electric meter in a deregulated market, a diagnostic or prognostic tool for mission-critical systems and an intelligent power quality monitor.