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

Capacitor banks are commonly connected to the power system to enhance its reliability by providing voltage support, improving power factor, and increasing the system capacity. They are usually switched in and out of the system according to the amount of connected load. This paper analyzes measurement data of a distribution utility with capacitor banks located downstream from the power quality monitor. It was observed that the amount of reactive power injected into the system was larger than the necessary, resulting in power factor over correction. The paper then provides an analysis method to determine the capacitor bank size to achieve a desired power factor correction. An algorithm is also proposed to override a switching control (usually time, voltage, or temperature), such that the switching is performed only if the power factor is below a preset minimum value. Moreover, it is advised to switch each phase individually, as the reactive power flow differs significantly between the three phases.

Analysis of power factor over correction in a distribution feeder

In recent years, there is worldwide development in railway transportation and it has gained significant importance. Different flexible alternating current transmission system (FACTS) devices, including static var compensator, static synchronous compensator, and railway power quality conditioner, have been proposed to improve system stability and power quality in railway traction power. With rapid railway growth, further research has been made to enhance the performance of FACTS devices in railway. This paper provides an overview of advances in FACTS devices for applications in railway traction power supply systems. It identifies different FACTS device study for railway traction power supply and make comparisons among them.

Recent Advances of FACTS Devices for Power Quality Compensation in Railway Traction Power Supply

This panel paper summarizes wind power development in recent years, and describes challenges of wind power integration. During the panel session, data mining and analysis techniques will be proposed to help solve these challenges

Applications of Data Mining and Analysis Techniques in Wind Power Systems

Several major outages have been traced to the failure of remote backup protection elements in distance relays. Experience has shown that coordination of remote backup zones in stepped-distance protection can be vulnerable during stressed conditions. Furthermore, relay settings are typically biased for high dependability, resulting in lower security especially when several unexpected events coincide. An incorrect response by a relay during such a condition can trigger or propagate the disturbance. Therefore, a new framework for Model-Based Relaying is introduced to supervise and secure the operation of remote backup protection elements, such as Zone 3. The framework utilizes the fact that while a single relay can observe a 3-phase fault or stressed system condition with similar apparent impedances, other system parameters will be significantly different. Therefore, the framework proposes to include the capability in relays to quickly run circuit model simulations at the relay level. The proposed method aims to work in parallel with and supervise the conventional distance relay's zone 3 for discrimination between 3-phase faults and stressed conditions using the output of local circuit model simulations. Several case studies are evaluated to demonstrate that dependability is not degraded for true fault conditions and security is enhanced for stressed system conditions.

Model-based relaying supervision for mitigation of cascading outages

Distance relay operation due to power swing conditions should be blocked in order to prevent unnecessary line trips leading to the formation of unplanned islands and the propagation of outages In this work, a machine learning classification approach to improve the detection of symmetrical faults during power swing conditions in conventional distance relays is presented The approach is intended to augment existing power swing blocking methods and trains a classifier with a focus on accuracy and interpretability The contribution of the approach is the training of classifiers that maintain performance of other methods, while providing interpretable results Training and test data is generated from time-domain simulations of the IEEE 9-Bus system for 17280 scenarios The following classifiers are compared and evaluated: support vector machine, random forest, gradient tree boosting, decision tree, and k-nearest neighbors Utilizing mutual information for feature selection and only local measurements, our results show performance comparable to prior methods and provides the ability to view the decision boundary for greater understanding of the classifier output Trade-offs between interpretability and performance are also assessed

Surya Santoso

Papers

Analysis of power factor over correction in a distribution feeder

Recent Advances of FACTS Devices for Power Quality Compensation in Railway Traction Power Supply

Applications of Data Mining and Analysis Techniques in Wind Power Systems

Model-based relaying supervision for mitigation of cascading outages

Symmetrical fault detection during power swings: An interpretable supervised learning approach