Showing posts with label conference paper. Show all posts
Showing posts with label conference paper. Show all posts

Wednesday, May 10, 2017

Spring 2017 conference papers for NAPS submission


Often times, Ph.D. students with psychological burden on paper writing would request that they be excused from paper submission to a conference. The excuse is that time can be saved for more in-depth study and for the final journal paper writing. The responsible and correct answer is, as always, no.  Any Ph.D. student survival guide would show that paper writing is an essential skill and there is no reason to trust there will be a journal paper before a conference paper. Usually, there are three stages to have a solid paper out. Stage 1: notes; Stage 2: conference paper; and Stage 3: journal paper. 

The spring 2017 semester sees a total of 11 conference papers. Coverage of the papers includes 1) dynamics and control; 2) optimization; and 3) system identification.

On the topic of dynamics, the following papers address converter droop control, synchronous machine modeling, converter cascaded control, and interconnected power system dynamics.
1.  I. Alsaleh and L. Fan, "DQ Current-based Droop Control for Microgrids."
2. Z. Wang and L. Fan, "Space Vector based Synchronous Machine Modeling."
3. Y. Zhou, Z. Miao, Y. Li and L. Fan, " Robust Cascaded Control for Converters. "
4. L. Bao, Z. Miao and L. Fan, "Smart Grid Cyber Attacks to Excite Interarea Oscillations."

On the topic of optimization, the following papers address PMU placement formulation as MIP and nonlinear programming, SDP relaxation AC OPF’s two applications, Using Benders’ decomposition to solve a model predictive control for multi-level modular converters, AC OPF-based financial transmission right auction model while considering loss allocation, and distributed computing using alternating direction method of multipliers (ADMM) for nonconvex AC OPF.
1. A. Almunif and L. Fan, "Optimal PMU Placement for State Estimation in Power Systems."
2. A. Alassaf and L. Fan, "Economic Dispatch with Heavy Loading and Maximum Loading Identification using Convex Relaxation of AC OPF."
3. M. Ma and L. Fan, "Bender's Decomposition for Model Predictive Control of an MMC."
4. A. Alburidy and L. Fan, " Loss Allocation in AC OPF-based FTR Auction Models."
5. R. Kar, M. Zhang, Z. Miao, and L. Fan, "ADMM for nonconvex AC OPF."

On the topic of system identification, the following two papers address how to estimate a synchronous generator’s parameters using PMU data and how to estimation a battery’s SoC and circuit parameters using measurements.
1. Y. Xu, Y. Li, and Z. Miao, "Nonlinear Least-Square Estimation-based Parameter Identification of a Synchronous Generator," submitted, NAPS 2017.
2. M. Zhang, Z. Miao and L. Fan, "Battery Identification based on Real-World Data," submitted, NAPS 2017.

All students are commented for their ability of project management, hardwork, and team spirit. 

Thursday, September 2, 2010

PMU data-based fault location techniques

H. Yin and L. Fan, "PMU data-based fault location techniques," NAPS 2010, U of Texas at Arlington, Sep. 26-28, 2010.

Accurate fault location promotes the reliability of the power system. This paper reviews various fault location techniques for transmission lines and presents PMU-based fault location methods. In 1950, the traveling waves-based fault location was first proposed. It calculates the fault location by measuring the relative time of the traveling wave arrives at the ends of transmission line. However, the high sampling rate limits its application. Then, fault location based on impedance was also developed. This method measures the voltage and current of one or two ends of the transmission line to calculate the fault impedance. Thus, the fault location could be known if the impedance of the transmission line is uniform. What’s more, distributed parameter transmission line model based method is also presented. In this paper, two-ended data are assumed to be measured by PMUs. Three-phase and one-phase transmission lines with two sources are tested in PSCAD. Simulation results of fault location methods based on negative-sequence impedance and distributed parameter transmission line models are also
given.

Index Terms—Fault location, Transmission line, Negative sequence impdance, PMU