Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed.

Micromachining Of Passive Planar Micromixer On Poly (Methyl Methacrylate) Substrate With Excimer Laser Ablation

Excimer laser ablation technique was introduced into this work to fabricate a passive planar micromixer on the PMMA substrate. T-junction shaped and width-changed S-shaped microchannels were both designed in this micromixer to enhance mixing effect. The mixing experiment of distilled water and Rhodamine B with injection flow rate of 500 and 1,500 mu m/s validates the mixing effectivity of this micromixer, and indicates the feasibility of excimer laser ablation in the microfabrication of mu-TAS device.

Dynamics and scaling of self-excited passive vortex generators for underwater propulsion

A series of experiments was conducted on the use of a device to passively generate vortex rings, henceforth a passive vortex generator (PVG). The device is intended as a means of propulsion for underwater vehicles, as the use of vortex rings has been shown to decrease the fuel consumption of a vehicle by up to 40% Ruiz (2010).

The PVG was constructed out of a collapsible tube encased in a rigid, airtight box. By adjusting the pressure within the airtight box while fluid was flowing through the tube, it was possible to create a pulsed jet with vortex rings via self-excited oscillations of the collapsible tube.

A study of PVG integration into an existing autonomous underwater vehicle (AUV) system was conducted. A small AUV was used to retrofit a PVG with limited alterations to the original vehicle. The PVG-integrated AUV was used for self-propelled testing to measure the hydrodynamic (Froude) efficiency of the system. The results show that the PVG-integrated AUV had a 22% increase in the Froude efficiency using a pulsed jet over a steady jet. The maximum increase in the Froude efficiency was realized when the formation time of the pulsed jet, a nondimensional time to characterize vortex ring formation, was coincident with vortex ring pinch-off. This is consistent with previous studies that indicate that the maximization of efficiency for a pulsed jet vehicle is realized when the formation of vortex rings maximizes the vortex ring energy and size.

The other study was a parameter study of the physical dimensions of a PVG. This study was conducted to determine the effect of the tube diameter and length on the oscillation characteristics such as the frequency. By changing the tube diameter and length by factors of 3, the frequency of self-excited oscillations was found to scale as f~D_0^{-1/2} L_0^0, where D_0 is the tube diameter and L_0 the tube length. The mechanism of operation is suggested to rely on traveling waves between the tube throat and the end of the tube. A model based on this mechanism yields oscillation frequencies that are within the range observed by the experiment.

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Deep near-infrared spectroscopy of high-redshift galaxies: the physical growth of passive systems

The assembly history of massive galaxies is one of the most important aspects of galaxy formation and evolution. Although we have a broad idea of what physical processes govern the early phases of galaxy evolution, there are still many open questions. In this thesis I demonstrate the crucial role that spectroscopy can play in a physical understanding of galaxy evolution. I present deep near-infrared spectroscopy for a sample of high-redshift galaxies, from which I derive important physical properties and their evolution with cosmic time. I take advantage of the recent arrival of efficient near-infrared detectors to target the rest-frame optical spectra of z > 1 galaxies, from which many physical quantities can be derived. After illustrating the applications of near-infrared deep spectroscopy with a study of star-forming galaxies, I focus on the evolution of massive quiescent systems.

Most of this thesis is based on two samples collected at the W. M. Keck Observatory that represent a significant step forward in the spectroscopic study of z > 1 quiescent galaxies. All previous spectroscopic samples at this redshift were either limited to a few objects, or much shallower in terms of depth. Our first sample is composed of 56 quiescent galaxies at 1 < z < 1.6 collected using the upgraded red arm of the Low Resolution Imaging Spectrometer (LRIS). The second consists of 24 deep spectra of 1.5 < z < 2.5 quiescent objects observed with the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE). Together, these spectra span the critical epoch 1 < z < 2.5, where most of the red sequence is formed, and where the sizes of quiescent systems are observed to increase significantly.

We measure stellar velocity dispersions and dynamical masses for the largest number of z > 1 quiescent galaxies to date. By assuming that the velocity dispersion of a massive galaxy does not change throughout its lifetime, as suggested by theoretical studies, we match galaxies in the local universe with their high-redshift progenitors. This allows us to derive the physical growth in mass and size experienced by individual systems, which represents a substantial advance over photometric inferences based on the overall galaxy population. We find a significant physical growth among quiescent galaxies over 0 < z < 2.5 and, by comparing the slope of growth in the mass-size plane dlogR_e/dlogM_∗ with the results of numerical simulations, we can constrain the physical process responsible for the evolution. Our results show that the slope of growth becomes steeper at higher redshifts, yet is broadly consistent with minor mergers being the main process by which individual objects evolve in mass and size.

By fitting stellar population models to the observed spectroscopy and photometry we derive reliable ages and other stellar population properties. We show that the addition of the spectroscopic data helps break the degeneracy between age and dust extinction, and yields significantly more robust results compared to fitting models to the photometry alone. We detect a clear relation between size and age, where larger galaxies are younger. Therefore, over time the average size of the quiescent population will increase because of the contribution of large galaxies recently arrived to the red sequence. This effect, called progenitor bias, is different from the physical size growth discussed above, but represents another contribution to the observed difference between the typical sizes of low- and high-redshift quiescent galaxies. By reconstructing the evolution of the red sequence starting at z ∼ 1.25 and using our stellar population histories to infer the past behavior to z ∼ 2, we demonstrate that progenitor bias accounts for only half of the observed growth of the population. The remaining size evolution must be due to physical growth of individual systems, in agreement with our dynamical study.

Finally, we use the stellar population properties to explore the earliest periods which led to the formation of massive quiescent galaxies. We find tentative evidence for two channels of star formation quenching, which suggests the existence of two independent physical mechanisms. We also detect a mass downsizing, where more massive galaxies form at higher redshift, and then evolve passively. By analyzing in depth the star formation history of the brightest object at z > 2 in our sample, we are able to put constraints on the quenching timescale and on the properties of its progenitor.

A consistent picture emerges from our analyses: massive galaxies form at very early epochs, are quenched on short timescales, and then evolve passively. The evolution is passive in the sense that no new stars are formed, but significant mass and size growth is achieved by accreting smaller, gas-poor systems. At the same time the population of quiescent galaxies grows in number due to the quenching of larger star-forming galaxies. This picture is in agreement with other observational studies, such as measurements of the merger rate and analyses of galaxy evolution at fixed number density.

Optimization of the pyrolysis process for the production of a biomass derived reducing agent and hydrogen-rich gases

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Passive Q-switching of short-length Tm3+-doped silica fiber lasers by polycrystalline Cr2+:ZnSe microchips

We demonstrate passive Q-switching of short-length double-clad Tm3+-doped silica fiber lasers near 2 mu m pumped by a laser diode array (LDA) at 790 nm. Polycrystalline Cr2+:ZnSe microchips with thickness from 0.3 to 1 mm are adopted as the Q-switching elements. Pulse duration of 120 ns, pulse energy over 14 mu] and repetition rate of 53 kHz are obtained from a 5-cm long fiber laser. As high as 530 kHz repetition rate is achieved from a 50-cm long fiber laser at similar to 10-W pump power. The performance of the Q-switched fiber lasers as a function of fiber length is also analyzed. (c) 2008 Elsevier B.V. All rights reserved.