The present work deals with the implementation of the test system Nordic32 proposed by Cigre task force 38-02-08. This test system which consists of 32 buses is a representation of the Swedish transmission and is suitable for the simulation of transient stability and long term dynamics. This work provides a detailed description about the steps followed to create both the static part of the system for load flow calculations and the controllers that the generators are equipped with. Furthermore, the thesis closes with a basic study concerning the modal analysis and the voltage stability of the system revealing some weaknesses that need further examination.

The high cost of grid extension to rural areas, often characterized by scattered communities with low load densities, requires the use of low cost electrification technologies to ensure economic viability. In Single Wire Earth Return (SWER) power distribution networks, the earth itself forms the current return path of the single phase system leading to significant cost savings on conductors, poles and poletop hardware compared to conventional systems. However, challenges exist in SWER with regard to earthing and safety as well as the dependence on earth conductivity to supply consumer loads. This work presents models for the optimal planning of SWER distribution networks. The earth return path is modeled as a conductor based on the Carson line model taking into consideration specific ground properties of the considered location. A load flow algorithm for radial SWER networks is subsequently formulated whereby both overhead line and ground voltages and currents are determined. First, heuristic planning models are developed based on the SWER load flow model. The objective of the heuristic models is to determine the optimum feeder configuration and overhead conductor subject to SWER load flow constraints and load growth over several time periods. Whereas the resulting solutions are good, they may not necessarily be globally optimum. Optimization models are then developed using mixed integer non-linear programming (MINLP) with the aim of obtaining global solutions to the SWER network planning problem. Since the MINLP formulations are limited to the accurate analysis of limited size networks, considerations and approximations for the analysis of larger networks are presented. The developed models are applied to a case study in Uganda to test their practical application. In addition, comparative studies are done to determine how the proposed optimization models compare with previous distribution planning models. The numerical analysis includes the impact of deterministic distributed generation on the SWER planning problem. Results showed consistent performance of the proposed heuristic and optimization models, which also compared well with conventional models. The optimization models gave more cost-effective solutions to the SWER planning problem than the heuristic models. However, the former models had higher computational cost than the latter. The inclusion of distributed generation allowed for cheaper network solutions to be obtained. The models are applicable to the planning of Single Wire Earth Return networks for isolated mini-grids, grid-extension to previously un-electrified rural areas as well as the upgrade of SWER feeders in existing installations. / <p>QC 20121207</p> / Sustainable Technological Development in the Lake Victoria Region

Indiana University-Purdue University Indianapolis (IUPUI) / The following thesis looks into modeling a chilled water system equipped with variable speed drives on different piece of equipment and optimization of system setpoints to achieve energy savings. The research was done by collecting data from a case-study and developing a system of component models that could be linked to simulate the overall system operation.

Huge amount of medical data has been generated in practical experiments which makes data analysis a challenging problem. This requires novel techniques to be developed. The improvements in computational power suggest to use computerbased modeling approaches to process a large set of data. One of the important systems in the human body to be investigated is the immune system. The previous studies of medical scientists and ongoing experiments at Karolinska Institute provide information about the human immune system. This information includes attributes of human immune system’s blood cells and the interactions between these cells. This interactions are provided as ‘if-then’ logical rules. Each rule verifies a condition on the attribute of one cell and it may initiate interaction processes to modify the attributes of other cells. A specific temporal value is associated to each process to quantify the speed of that process in the body (i.e., slow, medium, fast). We propose an agent-based model (ABM) to study human immune system cells and their interactions. The ABM is selected to overcome the complexity of large amount of data and find emergent properties and behavior patterns of the cells. Immune system cells are modeled as autonomous agents which have interactions with each other. Different values of a cell attributes define possible states of the cell and the collection of states of all cells constructs the state of the whole agent-based model. In order to consider the state transitions of the cells, we used a finite state machine (FSM). The first state is constructed from the input initial values for the cells and considering the logical time of 1. In each step, the program goes one time unit further and computes next state by applying the changes based on the cells’ interactions rules. This evolution of states in time is similar to game of life (GOL) automaton. The final model based on three modeling approaches of ABM, FSM and GOL are used to test medical hypothesis related to human immune system. This model provides a useful framework for medical scientists to do experiments on the cells’ attributes and their interaction rules. Considering a set of cells and their interactions, the proposed framework shows emergent properties and behavior patterns of the human immune system.

No description available.

Uncertainty analysis is an important part of system design. The formula for error propagation through a system model that is most-often cited in literature is based on a first-order Taylor series. This formula makes several important assumptions and has several important limitations that are often ignored. This thesis explores these assumptions and addresses two of the major limitations. First, the results obtained from propagating error through nonlinear systems can be wrong by one or more orders of magnitude, due to the linearization inherent in a first-order Taylor series. This thesis presents a method for overcoming that inaccuracy that is capable of achieving fourth-order accuracy without significant additional computational cost. Second, system designers using a Taylor series to propagate error typically only propagate a mean and variance and ignore all higher-order statistics. Consequently, a Gaussian output distribution must be assumed, which often does not reflect reality. This thesis presents a proof that nonlinear systems do not produce Gaussian output distributions, even when inputs are Gaussian. A second-order Taylor series is then used to propagate both skewness and kurtosis through a system model. This allows the system designer to obtain a fully-described non-Gaussian output distribution. The benefits of having a fully-described output distribution are demonstrated using the examples of both a flat rolling metalworking process and the propeller component of a solar-powered unmanned aerial vehicle.

<p>  </p> <p>As consumer adoption and total energy consumption of electric vehicles continues to rapidly increase, it is important to develop comprehensive system modeling frameworks that consider the complex interactions of their mechanical, electrical, and thermal subsystems to guide component technology development. This thesis studies the influence of cabin glass properties on the performance of an electric vehicle thermal system and overall cabin design considerations. The work first builds a generic long-range electric vehicle dynamic thermal system model while considering the system architecture, component sizing, control scheme, and glass properties. This comprehensive system model is used to assess the influence of cabin glass radiative properties on vehicle performance. The system model incorporates simplified models for all salient components in the electric traction drive, cabin HVAC, and battery subsystems, and uses a higher fidelity cabin thermal model that is able to capture the individual properties of the cabin glass used in the vehicle. To study the cabin model in isolation, a heat-up scenario is used to find that a cabin air temperature reduction of 8 °C through the use of different glass properties alone. Additionally, the cabin model is run repeatedly to produce a large data set that is trained using a machine learning regression model. This surrogate regression model that is used to reduce the computational time allowing for fast studies of glass properties and build an application engineering tool. The overall system performance is then evaluated under a dynamic NEDC drive cycle which is repeated until battery depletion to determine a vehicle range. A system validation is done on the HVAC subsystem by using steady-state thermodynamic analysis and comparing to the dynamic system model. This results in good agreement between four different subsystem modeling approaches. The system model is used to study five different glazing design cases, each corresponding to different transmission and reflection properties of the glass, by predicting their impact on the vehicle range. The cases span all theoretically possible glass properties while also enabling inspection of practical glass technologies that are available or under development to be adopted in modern electric vehicles. The influence of glass on vehicle range is then further compared at various locations across the United States to understand and illustrate the effects of ambient conditions and solar load. The system model predicts a vehicle range of 188.5 miles under a high solar loading scenario typical for Phoenix, AZ using traditional glass properties, which increases to a range of 221.6 miles using high-performance glass properties, representing a significant potential gain of 33.1 miles using technologies available on the market today. Under this same loading scenario, the glass properties at their extreme physical limits could theoretically affect the vehicle range by up to 92.5 miles. The influence of the glass properties is location-specific, and the model predicts that using the same glass at different locations can affect the range of vehicle by up to 100.8 miles for traditional glass properties and 73.4 miles for high-performance glass properties. </p>

Biomass is one of the renewable energy sources being used widely for power generation. This research work includes developing a comprehensive model for a biomass based power generation system as well as analyzing the technical, economical, and environmental impacts. The research objectives include modeling of the system, stability studies, and sensitivity analysis using MATLAB/Simulink. A mathematical model for the gas turbine has been developed and successfully interconnected with the distribution network. Transient stability of the power system has been carried out for four bus and six bus test case systems. Maximum rotor speed deviation, oscillation duration, rotor angle, and mechanical power have been taken as the stability indicators to analyze the system characteristics. Additionally, the sensitivity of the system to the changes of gas turbine parameters has been investigated under balanced and unbalanced fault scenarios. The economical and environmental impacts of the biomass have been analyzed using HOMER software developed by the National Renewable Energy Laboratory (NREL). The net present cost of the four biomass resources namely agricultural resources, forest residues, animal waste, and energy crops were obtained and the comparison of the costs of the biomass fuels as well as the diesel have been carried out. To investigate the environmental impact, carbon emissions of the different biomass fuels have been explored using HOMER.

No description available.

The present work studies the disturbances created in the electric system of a pumped storage power plant, which is an hydraulic generation facility where the machines can work as turbines or pumps, by the operation of a static frequency converter (SFC). The SFC is used for starting the synchronous machines at the station when in the pump mode. During the starting process several equipment is connected to the SFC being possible to get affected by the disturbances generated. These disturbances mainly include the creation of transient overvoltages during the commutation of the semiconductor devices of the SFC and the introduction of harmonics in the network currents and voltages. This work analyzes the possible effects of the SFC operation over the station equipment based on computer simulations. For this purpose, the complete system was modeled and the starting process simulated in a computer transient simulator program. The work begins with a general review of the effects of electric disturbances over high voltage equipment and in particular of the disturbances generated by power electronics conversion equipment. Then the models for the different kind of equipment present in the system are discussed and formulated. The control system that governs the operation of the SFC during the starting process is analyzed later as well as the operation conditions. Once the model of the system is set up, the harmonic analysis of the electric network is done by frequency domain and time domain methods. Time domain methods are also employed for the analysis of the commutation transient produced by the SFC operation. Finally, the simulation results are used to evaluate the impact of the SFC operation on the station equipment, especially on the generator step up transformer. / Master of Science