There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

On robust estimation of the location parameter

In the world, wind power is rapidly becoming a generation technology of significance. Unpredictability and variability of wind power generation is one of the fundamental difficulties faced by power system operators. Good forecasting tools are urgent needed under the relevant issues associated with the integration of wind energy into the power system. This paper gives a bibliographical survey on the general background of research and developments in the fields of wind speed and wind power forecasting. Based on the assessment of wind power forecasting models, further direction for additional research and application is proposed.

A review on the forecasting of wind speed and generated power

http://pierrepinson.com/31761/Literature/foley2012.pdf

Current methods and advances in forecasting of wind power generation

In this paper we present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances. The approach is based on wavelet transform analysis, particularly the dyadic-orthonormal wavelet transform. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. We demonstrate and test our proposed technique to detect and localize disturbances with actual power line disturbances. In order to enhance the detection outcomes, we utilize the squared wavelet transform coefficients of the analyzed power line signal. Based on the results of the detection and localization, we carry out an initial investigation of the ability to uniquely characterize various types of power quality disturbances. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance.

Power quality assessment via wavelet transform analysis

Analysis of voltage regulation impacts on distribution circuits due to electric vehicle (EV) battery loads requires accurate representation of the charging system. An EV charger consists of power electronic switches with PWM control to achieve desired charging characteristics while minimizing harmonic injections to the secondary service entrance. A detailed device-level model is accurate but it requires a significant amount of time to run due to the high switching frequency of the converter. For this reason, a novel and generic model of EV battery chargers is proposed and developed for evaluating distribution voltage regulation issues. The proposed model is developed based on the average-value modeling (AVM) approach. It includes a rectifier circuit along with PWM control, boost converter and battery banks. Average dynamics of the switching circuit are obtained by averaging the effects of fast switching in the device that occur within a prototypical switching interval. The proposed AVM is validated against a switching model and the actual measurements taken at an EV charging facility and is found to be very accurate in approximating EV charger behavior.

Average-Value Model of Electric Vehicle Chargers

The steady-state performance of low frequency AC (LFAC) systems for bulk power transmission is proposed and investigated in this paper. It is demonstrated that the LFAC is superior to the conventional 60 Hz AC system in terms of power transfer capability and voltage stability. An existing power system can increase its power transfer capability by up to more than eleven times if it operates at 5 Hz. In low operating frequency conditions, the transmission overhead line reactance is significantly lowered and thus results in less voltage drop along the line. If the system operating frequency is in the range of 1 to 10 Hz, the voltage profile along a transmission line is comparable to the surge impedance loading at the no-load condition or approaches that of the HVDC system at the full-load condition. More importantly, the V-P and Q-V characteristic curves show that the dependency of voltage on the real and reactive power flow is greatly reduced. In other words, the sensitivity of voltage on reactive power variations is diminished and results in a more stable voltage and a higher stability margin for the LFAC system compared to the conventional 60 Hz system.

Steady-State Analysis and Performance of Low Frequency AC Transmission Lines

This user guide is intended to accompany a software package containing a Matrix Laboratory (MATLAB) script and related functions for processing phasor measurement unit (PMU) data. This package and guide have been developed by the National Renewable Energy Laboratory and the University of Texas at Austin. The objective of this data processing exercise is to discover events in the vast quantities of data collected by PMUs. This document attempts to cover some of the theory behind processing the data to isolate events as well as the functioning of the MATLAB scripts. The report describes (1) the algorithms and mathematical background that the accompanying MATLAB codes use to detect events in PMU data and (2) the inputs required from the user and the outputs generated by the scripts.

/pdf/pmu-data-event-detection-a-user-guide-for-power-engineers-21shqsyu4h.pdf

PMU Data Event Detection: A User Guide for Power Engineers

Quantifying wind power variability is essential to power system operators, since wind power variability has a significant effect on the system operating reserve requirements and an underestimation of these requirements can severely affect the reliability of the system. Moreover, quantifying wind power variability, regardless of its uncertainty, can provide important characteristics generators must have so as to accommodate wind power fluctuations. The objective of this paper is to provide a metric to quantify short-term wind power variability. The general idea lies in comparing and quantifying the variability of a source using its range of outputs over a given period, conditioned on certain influential variables. The proposed conditional range metric (CRM) can be thought of as an “interval estimation” of the wind power over a given length time interval and can be used in conjunction with state-of-the-art forecasting as a valuable input in enhancing decision making under uncertainty.

Quantifying Short-Term Wind Power Variability Using the Conditional Range Metric

This panel summary presents the time-domain modeling of a distribution system where two wind turbines are interconnected. The distribution system is based on the IEEE 34-bus test feeder. The panel summary details the modeling of a wind turbine and analyzes the system power flow. Both modeling and power flow analysis are performed in the time-domain.

Surya Santoso

Papers

Average-Value Model of Electric Vehicle Chargers

Steady-State Analysis and Performance of Low Frequency AC Transmission Lines

PMU Data Event Detection: A User Guide for Power Engineers

Quantifying Short-Term Wind Power Variability Using the Conditional Range Metric

Induction machine test case for the 34-bus test feeder: a wind turbine time-domain model