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Wind generation presents variability on every time scale, which must be accommodated by the electric grid. Limited quantities of wind power can be successfully integrated by the current generation and demand-side response mix but, as deployment of variable resources increases, the resulting variability becomes increasingly difficult and costly to mitigate. In Chapter 2, we model a co-located power generation/energy storage block composed of wind generation, a gas turbine, and fast-ramping energy storage. A scenario analysis identifies system configurations that can generate power with 30% of energy from wind, a variability of less than 0.5% of the desired power level, and an average cost around $70/MWh. While energy storage technologies have existed for decades, fast-ramping grid-level storage is still an immature industry and is experiencing relatively rapid improvements in performance and cost across a variety of technologies. Decreased capital cost, increased power capability, and increased efficiency all would improve the value of an energy storage technology and each has cost implications that vary by application, but there has not yet been an investigation of the marginal rate of technical substitution between storage properties. The analysis in chapter 3 uses engineering-economic models of four emerging fast-ramping energy storage technologies to determine which storage properties have the greatest effect on cost-of-service. We find that capital cost of storage is consistently important, and identify applications for which power/energy limitations are important. In some systems with a large amount of wind power, the costs of wind integration have become significant and market rules have been slowly changing in order to internalize or control the variability of wind generation. Chapter 4 examines several potential market strategies for mitigating the effects of wind variability and estimate the effect that each strategy would have on the operation and profitability of wind farms. We find that market scenarios using existing price signals to motivate wind to reduce variability allow wind generators to participate in variability reduction when the market conditions are favorable, and can reduce short-term (30-minute) fluctuations while having little effect on wind farm revenue.

The interactions between predators and prey are a fundamental component of ecology and have direct relevance to the management and conservation of ecosystems around the World. Advances in global positioning system (GPS) collar technology have enabled researchers to gain insight into predator behavior, identify predation events in the field, and also build predictive predation models. Using GPS data from 26 collared cougars across three study areas, I investigated: 1) the mechanisms driving individual specialization in cougars and, 2) the utility of cluster models to predict predation events within and across study systems. In addressing the former, I used a subset of data from only a single study area including 13 cougars. I identified one specialist individual (P06) as having a unique diet relative to the population resulting from the continued selection of beaver (Castor canadensis). P06 actively hunted beaver by selecting for streams and creeks within his home range disproportionality to their availability and also traveled significantly slower while within beaver habitat indicative of the slow, stalk and ambush cougar hunting strategy. When predation by specialist cougars targets sensitive or rare species, targeted (rather than broad) management actions will be more effective in reducing unwanted predation on sensitive species. To address the utility of predictive models, I used logistic regression to discriminate between kill and no-kill GPS clusters and modeled the binary response as function of multiple spatiotemporal variables. I generated within study area estimates of predation using a top model selected from a candidate set using an information criterion (AIC), and estimated predation across study areas using simple models with only temporal variables. Within study area estimates of predation were ≥91% accurate, while across study area estimates averaged 81% (SD = 6%) accuracy. Cluster models serve as a valuable tool to estimate general predation within and across study areas, although there are a number of instances when their use is not recommended. When prey species of interest rare or endangered, occur near human activity, are relatively small, or have range overlaps with other similarly sized cougar prey, rigorous field efforts will be required to produce accurate estimates of predation.

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Thesis (M.S.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 74-75). / xi, 75 leaves, bound ill. 29 cm