Power and Energy Systems
Power and Energy Systems Group
The Power and Energy Systems Group focuses on electricity generation, and transmission and distribution systems to study various design and operation issues for effective utilization of electrical energy. The group also focuses on exploration and applications of renewable energy sources such as wind and solar.
In one project sponsored by the K-State Electrical Power Affiliates Program, researchers are studying voltage stability issues related to the fundamental nature of voltage collapse, modeling of the loads and their relationship to voltage stability, and effects of the integration of wind turbines on voltage stability. The research includes the utilization of artificial intelligence, primarily artificial neural networks and fuzzy logic, to identifying load models for classification and prediction of voltage stability problems. Another project, also supported by the Power Affiliates Program, focuses on improving the robustness of the power grid through distributed solar and wind generation. The power grid is being evaluated as a complex network with the aim of improving the robustness of the grid against cascading failures by adopting strategies such as intentional detachment of a part of the network to reduce the effect of failure of a node or a link on other connected components of the network. This detached portion can be powered by distributed sources of energy such as wind and solar power. Work is in progress to simulate the cascading effect and to evaluate the impact of topology of the network on the cascading failures.
The National Science Foundation provided funding for a project on investigation of influence of environmental factors, such as lightning, wind, trees, and squirrels on outages in electricity distribution systems. Several models based on neural networks, wavelet transform and Bayesian models have been developed to analyze these effects. These models are useful for electric utilities for year-end analysis of the performance of their system. Results of these analyses provide guidance to utilities on future operation and maintenance expenses to improve system performance. In addition, research was conducted on optimal utilization of small wind and solar generation systems with energy storage. An intelligent dispatch algorithm was developed, which uses load profile of the house, energy available from the on-site renewable generator, and battery conditions to make decisions on buying, selling or storing the energy on an hourly basis under different rate scenarios. Research is in progress to include options of real-time price and of deferring loads in the household to a later time for optimizing the benefits. This research, supported by the K-State Engineering Power Affiliates Program, is very important for promoting small wind and solar generation projects and to meet the renewable portfolio standards.
This project will demonstrate a Holonic Multiagent System Architecture capable of adaptively controlling future electrical power distribution systems (PDS), which are expected to include a large number of renewable power generators, energy storage devices, and advanced metering and control devices. The project will produce a general, extensible, and secure cyber architecture based on holonic multiagent principles to support adaptive PDS. It will produce new analytical insights to quantify the impact of information delay, quality and flow on the design and analysis of the PDS control architecture. Finally, it will develop a novel methodology for comprehensive automation of PDS for higher efficiency, reliability, security, and resiliency with high penetration of distributed renewable resources.
Influence of Environmental Factors on Outages in Electricity Distribution Systems
Environmental factors such as lightning, wind, tree, and squirrels cause a majority of outages in distribution systems. Their effects follow random processes with higher probability of outages under worse conditions. Understanding effects of environmental variables is important for utilities to increase reliability of electricity distribution systems. The National Science Foundation is providing funding to Dr. Anil Pahwa and Dr. Sanjoy Das to investigate these effects. Due to the complex nature of interaction of these factors with distribution systems, modeling becomes difficult. In this project, we are investigating regression, neural networks, wavelet decomposition and Bayesian models to study effects of environmental variables on distribution systems. For example, to study the influence of lightning and wind, we have used non-linear regression models with maximum daily wind gust and sum of lightning strokes in a day as inputs and outages as outputs. Applying these models to five years of data (2005-2009) obtained for service territories of Manhattan, Lawrence and Topeka show that the model with linear relationship for lightning and quadratic relationship for wind to outages gives the best performance. Future research will focus on exponential regression models, neural networks and Bayesian models.
The Kansas Wind Applications Center missions are to educate electrical engineers on the basics of
wind energy, and to be a source of information on wind energy for the people of Kansas who want to
harvest wind power for the benefit of themselves, their children and the state. Research projects
include the following:
- siting of small wind turbines, including means of assessing surface roughness and turbulence;
- networking of distributed generation sources for reliability, especially in islanded conditions; and
- development of curricula for use in K-12 and informal educational settings, such as 4-H, focusing on topics of energy and sustainability.
The WAC also runs the Wind for Schools program in which small wind turbines are installed at
K-12 schools throughout Kansas for educational purposes. Undergraduate students assist with
school selection, communications and siting. The WAC coordinates a variety of industry donors to
accomplish the installations with minimal costs to the schools and enhanced cooperation with electric utilities. Through 2009, seven turbines had been installed at Kansas schools. The Wind Applications Center is funded by the Department of Energy under its Wind Powering America program.
Wind generation has received significant attention over the past decade, but most of the focus has been on large wind farms. The focus of this project, supported by the U.S. Department of Energy, is to investigate the feasibility of owning a wind generator by electricity distribution co-operative. Dr. Anil Pahwa and a graduate student are using the hourly load data of a co-operative in western Kansas and weather data for this research.