Optimization Techniques for Modern Power Systems Planning, Operation and Control

Recent developments in computing, communication and improvements in optimization techniques have piqued interest in improving the current operational practices and in addressing the challenges of future power grids. This dissertation leverages these new developments for improved quasi-static analysis of power systems for applications in power system planning, operation and control. The premise of much of the work presented in this dissertation centers around development of better mathematical modeling for optimization problems which are then used to solve current and future challenges of power grid. To this end, the models developed in this research work contributes to the area of renewable integration, demand response, power grid resilience and constrained contiguous and non-contiguous partitioning of power networks. The emphasis of this dissertation is on finding solutions to system operator level problems in real-time. For instance, multi-period mixed integer linear programming problem for applications in demand response schemes involving more than million variables are solved to optimality in less than 20 seconds of computation time through tighter formulation. A balanced, constrained, contiguous partitioning scheme capable of partitioning 20,000 bus power system in under one minute is developed for use in time sensitive application area such as controlled islanding

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Thermal stress analysis of butt welded joint / Karthikeyan Balasubramaniam

In industries’ welding plays a vital role in joining process. Many of the structures presently built in space rockets, deep diving submarines and very heavy containment vessels for nuclear reactors could not have been constructed without the proper application of welding technology. It is well known fact that during welding the metal at the welding zone gets melted and then solidifies, which results in shrinkage in all the directions. Residual strain and stress distributions coming from shrinking are largely influenced by the nature and configuration of the welding process, metallurgical characteristics of weld and the geometrical shape of the weld joint. The material characteristic mainly depends on the thermal history cycle through which the specimen goes through in the process. So these thermal history cycles are to be known in order to get a better knowledge of the welding phenomenon and to minimize the risk of failures. This work describes the detail finite element procedure for determination of heat flow pattern and stress distribution on cylinder modeled with stainless steel and aluminum during welding. In this, Modified Double Ellipsoidal Distribution Pattern was modeled and considered for the weld pool design. Elasto-plastic material properties at various temperatures were also considered for simulation. A variable welding speed was used during welding and effect of the nonlinear welding speed was also studied. Transient thermal histories at various points were determined and compared with available published data. The cooling curve could be obtained from the descending region of the Transient thermal histories curve at various locations. By this metallurgical characteristic of the material at the weld zone and heat affected zone can be obtained during welding simulation process. The problems of distortion and stress distribution were also carried out. A customized programming was developed to for the welding simulation

Design and operation of a pilot plant for biodiesel production from triglycerides

In the wake of the events of September 11th 2001, the quest to relieve the nation’s dependence on petroleum fuels have taken a new urgency, there is a renewed interest in use of renewable biogenic fuels in particular -- the “biodiesel.” Biodiesel generally refers to fatty acid methyl esters of monohydric alcohols -- predominantly the methyl alcohol. The principal sources of fatty acids are vegetable oils - soybean oil and canola oil. However, there are other “cheaper” sources of fatty acids that include beef tallow, poultry fats, pork fats and the used cooking oils. The first two are available in abundance in the mid-western and south-central United States. In fact conversion of the cheaper material into biodiesel would not only provide an opportunity to produce cheaper biodiesel but alleviate waste disposal related environmental problems for the poultry and the beef processing industries. These problems are indeed very large and will continue to grow because of the “Mad Cow Syndrome” and its association with the recycling of animal products in the animal feeds. Thus the animal fats and used cooking oils represent the cheapest sources of raw materials for biodiesel production. However, in contrast to the well researched and developed technologies for conversion of vegetable oils to biodiesel, the conversion of animals fats and used cooking oils to biodiesel have not been researched extensively. This work focused on producing biodiesel from low-cost feedstocks such as chicken fats and used cooking oils. A batch type pilot plant was designed and fabricated to produce biodiesel from triglycerides. Detailed analysis and experimental work was done to optimize the process parameters. The product quality was monitored using Thin Layer Chromatography (TLC), a qualitative technique. The concentration of the fatty acid methyl esters in the product was estimated using High Performance Liquid Chromatography (HPLC), a quantitative technique. This work concluded with the optimum process specification and recommendations for further research --Abstract, pages iv-v

A virtual engineering framework to support progressive interaction in engineering design

Engineering design encompasses a series of non-trivial decision making phases in generating initial solutions, developing mathematical models, performing analysis, and optimizing designs. Engineering analysis and optimization are the phases that often significantly slow down the design process. Thorough designer exploration on the solution space increases the likelihood of determining the most feasible solution but, at the expense of longer lead times. The exploratory capabilities of the designer could be enhanced by creating an interactive virtual engineering framework. This research presents progressive interaction with the designer-in-the-loop whose intelligence is blended with the computational power to suitably control the optimization. Progressive interaction is a human-guided preference articulation method where the designer intelligence continuously controls the engineering analysis and optimization by visualization, modification and controlled re-optimization. Based on the designer's knowledge and the knowledge available from the interaction system, the designer preferences can be modified anytime to expedite optimization. Progressive interaction not only helps the designer discover the hidden relationship between the decision variables but it also uncovers the implicit constraints and other performance limitations of the design. In summary, this research work proposes human-guided, progressive interaction as a solution to complex engineering optimization problems. The proposed solution is demonstrated using three test cases: (1) Interactive image segmentation and optimization, (2) Designer interaction to support shape optimization of a finned dissipater, and (3) Interactive analysis, optimization and design of hydraulic mixing nozzle.</p

System and Analysis for Low Latency Video Processing using Microservices

The evolution of big data processing and analysis has led to data-parallel frameworks such as Hadoop, MapReduce, Spark, and Hive, which are capable of analyzing large streams of data such as server logs, web transactions, and user reviews. Videos are one of the biggest sources of data and dominate the Internet traffic. Video processing on a large scale is critical and challenging as videos possess spatial and temporal features, which are not taken into account by the existing data-parallel frameworks. There are a broad range of users who want to apply sophisticated video processing pipelines such as transcoding, feature extraction, classification, scene cut detection and digital compositing to video contentParallel video processing poses several significant research challenges to the existing data processing frameworks. Current systems are capable of processing videos but with higher resource startup times, a small degree of parallelism, low average resource utilization, coarse-grained billing, and higher latency. This research proposes a low latency software run-time for processing a single video efficiently by orchestrating cloud-based microservices. The system leverages lightweight microservices provided by Amazon Web Services Lambda framework

Situational Awareness System for Power Grids

The continuing increase of demand for electrical energy has resulted in power grids being operated closer to its operating limits. At the same time, integration of renewable energy sources introduces conditions of high uncertainty and high variability. Maintaining power system reliability under these conditions is a challenging task. Development in telecommunications and other advances have enabled more accurate and faster influx of data. However, more data does not equate to more information. With the plethora of data available it becomes necessary to extract information that a control room operator can act upon. Situational awareness (SA) in simple terms is to understand the current state of the system and based on that understanding project how things are to evolve over time. The situational awareness platform presented in this paper extracts information from data for the next time instance i.e. a step ahead of time and maps this data with geographic coordinates of utility assets. The geographic information system (GIS) provides a visual indication of health of individual units as well as that of the entire system

Assessing the Need and State of Power System and Transportation System Co-Simulation

According to the Environmental Protection Agency, the power and transport systems contribute over 50&#x0025; of greenhouse gas emissions in the United States. The combination of renewable energy resources and electrified transportation play a crucial role in helping countries meet their carbon neutrality goals. Coordinated planning of the power and transportation systems is necessary to ensure reliable, efficient, and economic operation of both systems. This paper surveys applications of large-scale transportation electrification, vehicle-to-grid charging, prosumer behavior, sector coupling, route optimization, and charging demand and estimation. The co-simulation frameworks available for coupling the power and transport systems to further study these applications are also surveyed. Most of the existing literature utilizes stochastic transportation models or ad-hoc co-simulation approaches which do not promote scalability, extensibility, and interoperability. It is proposed to extend the Hierarchical Engine for Large-Scale Infrastructure Co-simulation to communicate with an agent based transportation simulator for examining these interconnected applications