Operations and Planning in Sustainable Power Systems

Thesis (Ph.D.)--University of Washington, 2016-06

Effect of cooling and re-warming on cerebral and whole body electrical impedance

Cerebral electrical impedance is useful for the detection of cerebral edema following hypoxia in newborn infants. Thus it may be useful for determining neurological outcome or monitoring treatment. Hypothermia is a promising new therapy currently undergoing trials, but will alter impedance measurements. This study aimed to define the relationship between temperature and both cerebral and whole body electrical impedance, and to derive correction factors for adjustment of impedance measurements during hypothermia. In eight anaesthetized 1-2 day old piglets rectal, tympanic and scalp temperatures were monitored continuously. Following baseline readings at a rectal temperature of 39degreesC, piglets were cooled to 32degreesC. Four piglets were re-warmed. Cerebral and whole body impedance were measured at each 0.5degreesC as rectal temperature decreased. There was a strong linear relationship between both cerebral and whole body impedance and each of the temperatures measured. There was no difference in the relationship between impedance and rectal, tympanic or scalp temperatures. The relationship for impedance and rectal temperature was the same during cooling and re-warming. Using the correction factors derived it will be possible to accurately monitor cerebral and whole body fluid distribution during hypothermic treatment.

Effect of smoke inhalation on viscoelastic properties and ventilation distribution in sheep

Smoke inhalation injuries are the leading cause of mortality from burn injury. Airway obstruction due to mucus plugging and bronchoconstriction can cause severe ventilation inhomogeneity and worsen hypoxia. Studies describing changes of viscoelastic characteristics of the lung after smoke inhalation are missing. We present results of a new smoke inhalation device in sheep and describe pathophysiological changes after smoke exposure. Fifteen female Merino ewes were anesthetized and intubated. Baseline data using electrical impedance tomography and multiple-breath inert-gas washout were obtained by measuring ventilation distribution, functional residual capacity, lung clearance index, dynamic compliance, and stress index. Ten sheep were exposed to standardized cotton smoke insufflations and five sheep to sham smoke insufflations. Measured carboxyhemoglobin before inhalation was 3.87 +/- 0.28% and 5 min after smoke was 61.5 +/- 2.1%, range 50-69.4% ( P < 0.001). Two hours after smoke functional residual capacity decreased from 1,773 +/- 226 to 1,006 +/- 129 ml and lung clearance index increased from 10.4 +/- 0.4 to 14.2 +/- 0.9. Dynamic compliance decreased from 56.6 +/- 5.5 to 32.8 +/- 3.2 ml/ cmH(2)O. Stress index increased from 0.994 +/- 0.009 to 1.081 +/- 0.011 ( P < 0.01) ( all means +/- SE, P < 0.05). Electrical impedance tomography showed a shift of ventilation from the dependent to the independent lung after smoke exposure. No significant change was seen in the sham group. Smoke inhalation caused immediate onset in pulmonary dysfunction and significant ventilation inhomogeneity. The smoke inhalation device as presented may be useful for interventional studies.

Tradeoffs of different types of species occurrence data for use in systematic conservation planning

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

Transmission planning in a deregulated environment

The worldwide trend for the deregulation of the electricity generation and transmission industries has led to dramatic changes in system operation and planning procedures. The optimum approach to transmission-expansion planning in a deregulated environment is an open problem especially when the responsibilities of the organisations carrying out the planning work need to be addressed. To date there is a consensus that the system operator and network manager perform the expansion planning work in a centralised way. However, with an increasing input from the electricity market, the objectives, constraints and approaches toward transmission planning should be carefully designed to ensure system reliability as well as meeting the market requirements. A market-oriented approach for transmission planning in a deregulated environment is proposed. Case studies using the IEEE 14-bus system and the Australian national electricity market grid are performed. In addition, the proposed method is compared with a traditional planning method to further verify its effectiveness.

Electrical impedance tomography in extremely prematurely born infants and during high frequency oscillatory ventilation analyzed in the frequency domain

Functional electrical impedance tomography (EIT) measures relative impedance change that occurs in the chest during a distinct observation period and an EIT image describing regional relative impedance change is generated. Analysis of such an EIT image may be erroneous because it is based on an impedance signal that has several components. Most of the change in relative impedance in the chest is caused by air movement but other physiological events such as cardiac activity change in end expiratory level or pressure swings originating from a ventilator circuit can influence the impedance signal. We obtained EIT images and signals in spontaneously breathing healthy adults, in extremely prematurely born infants on continuous positive airway pressure and in ventilated sheep on conventional mechanical or high frequency oscillatory ventilation (HFOV). Data were analyzed in the frequency domain and results presented after band pass filtering within the frequency range of the physiological event of interest. Band pass filtering of EIT data is necessary in premature infants and on HFOV to differentiate and eliminate relative impedance changes caused by physiological events other than the one of interest.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Probabilistic world modelling for distributed team planning

This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that tbe action selection mechanism of a member in a robot team cm select am effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probsbilistie view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried ont to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.