Shelli K. Starrett

Nonlinear measures of mode-machine participation [transmission system stability]

This work investigates the significance of higher-order terms on the modal behavior of a large, stressed power systems transient response. Second-order analysis indicates that many more frequencies of oscillation may have significant influence on the power system response. These additional frequencies result from second-order interactions of the linear modes and cannot be studied using linear analysis. A methodology based on the normal-form method is developed and utilized to describe the stressed, nonlinear system response. This methodology is used to extend linear concepts, such as eigenvectors and mode-state participation, to include second-order modal affects on power system performance. Data from the 50-generator IEEE test system is used in this investigation.

Effective Wind Farm Sizing Method for Weak Power Systems Using Critical Modes of Voltage Instability

Current methods for determining wind farm maximum sizes which do not consider voltage stability margins (VSMs) may result in reducing the overall levels of wind generation in a system. In this paper, new methods have been developed to increase wind penetration level by placing new wind generation at voltage stability strong wind injection buses. Placing new generation at these buses has the least impact on VSMs not only in the vicinity of new wind generation, but also throughout the power system. The new methods provide a comprehensive methodology for the identification of system weaknesses for each wind penetration level. The new methods incorporate modal analysis as well as traditional voltage stability methods (Q-V curves) in sizing and placing new wind farms. The study shows that the location of SVCs is also key to increasing wind penetration. Wind penetration can be increased when placing SVCs at the weakest buses in the system instead of only locating them at the wind generation buses.

Fuzzy logic control schemes for static VAR compensator to control system damping using global signal

Abstract This paper presents a simple way of achieving damping of phase angle oscillations and improving transient stability of an interconnected power system network using fuzzy logic. The output of the fuzzy logic controller is fed to an already existing Static VAR compensator (SVC). Different input measurements and their combinations are tested and the effectiveness of the fuzzy controller for achieving stability has been demonstrated on a four-generator, two-area system using simulation studies. The inputs tested are line power, angular speed, machine angle, frequency and combination of these. The paper also compares the damping effectiveness of the fuzzy controlled SVC (FCS) and a conventional power system stabilizer (CPSS).

Using artificial neural networks and regression to predict percentage of applied nitrogen leached under turfgrass

Abstract The objective of this study was to develop an Artificial Neural Network (ANN) model that accurately predicts the percentage of applied nitrogen (N) that leaches through the upper 50 cm of soil under a variety of conditions. The statistical regression models were used for comparison with the ANN model. The Sum of the Squared Error (SSE) between the anticipated values (from research data) and the predicted values (produced by the model) was calculated to be 0.3 for the ANN model and 0.1 for the third order regression. In this particular project, the first and second order regression equations are not useful; however, the third order equation could be used by turf managers along side the ANN model to accurately predict leachate under given field conditions. These models enable the turfgrass manager to determine the effects of management practices on N leaching.

Fate of amended urea in turfgrass biosystems

Abstract The fate of nitrogen (N) has been studied under several agronomic crops and agricultural profiles, but relatively little information has been collected from areas managed as turfgrass. The turfgrass industry has become the focus of environmental concerns in recent years and is often identified as a source of ground water contaminate. The objectives of this study were to: i) investigate the hydrology of 20‐cm diameter by 50‐cm deep undisturbed soil columns covered with a Kentucky bluegrass (Poa pratensis L.) turf under a heavy (one 2.54‐cm application) and a light (four 0.64‐cm applications) irrigation regime, and to ii) quantify the fate of 15N‐labeled urea when it is applied to an undisturbed soil columns having intact macropores. Clipping, verdure, and thatch/mat samples were taken from each column, and the soil was excavated in 10‐cm layers at the end of the 7‐day test period. A glass collection chamber was used to collect volatilized N and a plastic bag for leachate collection. All samples we...

Maximizing wind penetration using voltage stability based methods for sizing and locating new wind farms in power system

Current methods in which maximum sizes of new wind farms are determined do not take into consideration their impact on future wind penetration levels. In this paper, two methods are proposed to determine maximum sizes of multiple new wind farms for maximizing wind penetration levels. In both methods, each new wind farm size is determined using an iterative process where each wind farms size is incremented by a fixed value and its impact on voltage stability margins (VSMs) is observed. Incremented wind farms which result in less negative impact on VSMs are sized larger until reaching voltage instability. Proposed methods are applied to western Kansas power system where three new wind farms are to be sized. Results of applying these new methods shows that wind penetration can be maximized by placing new larger wind farms in areas where the transmission system is strong and has high VSMs.

Distance learning for power professionals: virtual classrooms allow students flexibility in location and time

The number of universities offering distance learning courses in power systems has increased significantly over the last few years. Therefore, it has become critical to evaluate distance learning with respect to student learning, pedagogy, delivery media, logistics, and cost. This paper presents the results of a survey conducted to determine distance learning resources in power systems. Benefits of distance learning and a brief history of distance learning in power systems at Kansas State University are also provided. The different media for delivery of lectures to students are discussed and some strategies for interaction between faculty and students to improve learning are presented.

Modeling pesticide leaching from golf courses using artificial neural networks

Abstract The objective of this work was to develop a computer model that accurately predicted pesticide leaching of pesticides applied to turfgrass areas. After much investigation, the number of inputs used to train the Artificial Neural Networks (ANN) was reduced to pesticide solubility, pesticide soikwater partitioning coefficient (Koc), time after application, and the irrigation application practice. For comparison reasons, 1st and 2nd order polynomial regression models were developed. An artificial neural network is a form of artificial intelligence enabling the program to learn relationships instead of the relationships being defined by the programmer. The ANN proved to be a feasible modeling technique for pesticide leaching. The ANN predictions for the test cases had much less error than the 1st or 2nd order regression equations (sum of the squared error between measured and predicted values were 17.4, 528.4, and 522.3, respectively). An interactive World Wide Web (www) site has been developed where...

Method for assessing system impact of increasing wind farm sizes above their maximum limits

Current methods for determining wind farm maximum size use conservative voltage stability approach based on maximum wind speed occurring simultaneously with peak loading conditions. Wind patterns at a wind farm site may never allow the wind farm to produce its maximum capacity during the hours of heavy loading conditions. In this paper, a new method is proposed to determine wind farm maximum size which incorporates voltage stability margins and wind patterns at the wind farm site into sizing a wind farm. It provides a method to increase wind farm maximum size with an option of curtailing wind generation under certain conditions based on voltage stability margins. The proposed method is applied to a wind farm in western Kansas power system. Results of applying the new method show that wind farm maximum size can be increased if the system is operated with wind curtailment control to maintain voltage stability.

Modeling power system load using adaptive neural fuzzy logic and Artificial Neural Networks

The modern power system consists of an integrated, complex, dynamic system. This dynamic system and its power system operation and control needs to be analyzed with numerical simulation. Among many components in the power system operation, load model is one of the least known models. The commonly used models include the ZIP load model and exponential load model. Load parameter representation for dynamic performance can be complicated and non-linear. The dynamic characteristics of power system loads are used for obtaining power system controls, operations and stability limits. Different approaches can be made to determine models for power system loads. In this paper, the authors used adaptive-neural network-based fuzzy inference system (ANFIS) and Artificial Neural Networks (ANN) to model power system loads.