13 research outputs found
Forced Oscillation Source Location via Multivariate Time Series Classification
Precisely locating low-frequency oscillation sources is the prerequisite of
suppressing sustained oscillation, which is an essential guarantee for the
secure and stable operation of power grids. Using synchrophasor measurements, a
machine learning method is proposed to locate the source of forced oscillation
in power systems. Rotor angle and active power of each power plant are utilized
to construct multivariate time series (MTS). Applying Mahalanobis distance
metric and dynamic time warping, the distance between MTS with different phases
or lengths can be appropriately measured. The obtained distance metric,
representing characteristics during the transient phase of forced oscillation
under different disturbance sources, is used for offline classifier training
and online matching to locate the disturbance source. Simulation results using
the four-machine two-area system and IEEE 39-bus system indicate that the
proposed location method can identify the power system forced oscillation
source online with high accuracy.Comment: 5 pages, 3 figures. Accepted by 2018 IEEE/PES Transmission and
Distribution Conferenc
Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications
The design of an effective and reliable communication network supporting smart grid applications requires the selection of appropriate communication technologies and protocols. The objective of this study is to study and quantify the capabilities of an advanced metring infrastructure (AMI) to support the simultaneous operation of major smart grid functions. These include smart metring, price-induced controls, distribution automation, demand response, and electric vehicle charging/discharging applications in terms of throughput and latency. OPNET is used to simulate the performance of selected communication technologies and protocols. Research findings indicate that smart grid applications can operate simultaneously by piggybacking on an existing AMI infrastructure and still achieve their latency requirements