AbstractsPhysics

"The use of renewable energy systems to power groundwater remediation systems seems like an inherently good idea because of potential cost savings and environmental benefits associated with reduced greenhouse gas emissions. Small wind turbine systems marketed for single residence applications may be the appropriate size for remediation systems, and such wind turbines are readily available at reasonable cost. Another benefit of using domestic wind turbine systems is that they are straightforward to install and operate with minimal training. One of the major drawbacks associated with using wind turbines at remediation sites is that site-specific wind velocity data is typically used to predict the quantity of energy that will be generated, and the time and cost of site-specific data collection may be prohibitive given the overall cost of a small wind turbine system. The four papers presented in this dissertation describe the collection of wind turbine performance data at the former Nebraska Ordnance Plant Superfund site. Wind velocity data collected at nearby weather stations associated with a regional climate database were used to predict the wind velocity at the wind turbine and the associated wind turbine performance. The wind turbine was operated in both grid inter-tie mode and off-grid mode. Stochastic analysis using Monte Carlo models was used to account for the inherent variability associated with wind velocity and other inherently random variables. Economic analyses were performed, energy efficiency (EE) was identified as another energy source, and weather station selection criteria were evaluated. Energy analysis has revealed that significant energy is consumed in non-pumping activities such as heating of the equipment shelter for operator comfort. Economic analysis has also shown the value of groundwater remediation processes that use little or no electricity (which enhance the use of green power). Monte Carlo models of the wind and energy generated reveal that for the study site a remote metrological site downwind of wind turbine site produces a most accurate simulation of wind and energy. The Monte Carlo model was also operated using 1, 12, 20 or 24 years of data and found to give an accurate simulation of wind and energy using only one year of off-site weather data. This indicates the potential for using regional climate weather stations in a MCP (Measure - Correlate - Predict) that employs a Monte Carlo procedure" – Abstract, p. iv-v.