Full AC analysis of value of DER to the grid and optimal DER scheduling

This paper presents part of the work ComEd and Quanta Technology have performed to quantify the locational and temporal value of DER to avoid distribution grid upgrade investments. It focuses on the formulation of a robust and efficient algorithm for DER optimal dispatch on a distribution feeder to mitigate the violation of current and voltage limits using the allocated cost of capacity and locational marginal value of real and reactive DER injection/withdrawal.     

Self-Synchronous and Self-Referenced Coherent Beam Combination for Large Optical Arrays

A novel and highly accurate electronic technique for phase locking arrays of optical fiber amplifiers is demonstrated. This is the only electronic phase locking technique that does not require a reference beam. The measured phase error for this system is lambda /20. A model for calculating the signal-shot noise-limited phase errors and the phase-modulation-induced phase errors is developed. For the first time, nine fiber amplifiers are coherently combined. The total power in the phase locked array is 100 W.     

Tailoring HASE rheology through polymer design: Effects of hydrophobe size, acid content, and molecular weight

Hydrophobically modified alkali-soluble emulsion (HASE) polymers are an important class of rheology modifiers for waterborne coatings applications. They are typically prepared as terpolymers by emulsion polymerization of ethyl acrylate (EA), methacrylic acid (MAA), and an associative macromonomer. The viscosity development and shear responses of HASE solutions depend on a number of factors. This article presents rheological data reflecting the impacts of three key variables: hydrophobe size, acid content, and molecular weight, on model HASE thickening and rheological performance. The relative contributions of hydrophobic association, chain expansion, and polymer chain length are discussed. In steady shear flow, all thickener solutions approached some constant low-shear viscosity at small deformation rates. At the same molar composition, larger hydrophobe size resulted in higher viscosity development and greater shear thinning behavior. The amount of acid monomer in HASE polymers can influence the balance between hydrophobic attraction and electrostatic repulsion forces. It was found that a minimum of 15 wt% MAA was required to effect dissolution and thickening of the model HASE polymers. Increasing the MAA level yielded higher zero-shear viscosity and storage modulus G’ with maximal values being obtained at 40% MAA. The molecular weight of the model thickeners was controlled by the amount of chain transfer agent (CTA) added during polymerization. When the CTA level was below 0.1 wt% based on total monomers, the polymer solutions displayed shear-thinning behavior. A small increase in CTA concentration beyond 0.1% resulted in a dramatic change to Newtonian flow, and the solution viscosity was nearly two orders of magnitude lower. The model thickeners were also tested in a vinyl acrylic architectural paint formulation. The effects of each individual factor on paint thickener efficiency, high-shear, and low-shear properties are discussed and compared with solution rheology for predictive relationships. Presented at the 81st Annual Meeting of the Federation of Societies for Coatings Technology, November 11–12, 2003, in Philadelphia, PA.     

Speeding Up HMM Decoding and Training by Exploiting Sequence Repetitions

We present a method to speed up the dynamic program algorithms used for solving the HMM decoding and training problems for discrete time-independent HMMs. We discuss the application of our method to Viterbi’s decoding and training algorithms (IEEE Trans. Inform. Theory IT-13:260–269, 1967), as well as to the forward-backward and Baum-Welch (Inequalities 3:1–8, 1972) algorithms. Our approach is based on identifying repeated substrings in the observed input sequence. Initially, we show how to exploit repetitions of all sufficiently small substrings (this is similar to the Four Russians method). Then, we describe four algorithms based alternatively on run length encoding (RLE), Lempel-Ziv (LZ78) parsing, grammar-based compression (SLP), and byte pair encoding (BPE). Compared to Viterbi’s algorithm, we achieve speedups of Θ(log n) using the Four Russians method, using RLE, using LZ78, using SLP, and Ω(r) using BPE, where k is the number of hidden states, n is the length of the observed sequence and r is its compression ratio (under each compression scheme). Our experimental results demonstrate that our new algorithms are indeed faster in practice. We also discuss a parallel implementation of our algorithms. A preliminary version of this paper appeared in Proc. 18th Annual Symposium on Combinatorial Pattern Matching (CPM), pp. 4–15, 2007. Y. Lifshits’ research was supported by the Center for the Mathematics of Information and the Lee Center for Advanced Networking. S. Mozes’ work conducted while visiting MIT.     

A self-stabilizing transformer for population protocols with covering

Developing self-stabilizing solutions is considered to be more challenging and complicated than developing classical solutions, where a proper initialization of the variables can be assumed. Hence, to ease the task of the developers, some automatic techniques have been proposed to design self-stabilizing algorithms. In this paper, we propose an automatic transformer for algorithms in an extended population protocol model. Population protocols is a model that was introduced recently for networks with a large number of resource-limited mobile agents. We use a variant of this model. First, we assume agents having characteristics (e.g., moving speed, communication radius) affecting their intercommunication “speed”, which is reflected by their cover times. Second, we assume the existence of a special agent with an unbounded memory, the base station. The automatic transformer takes as an input an algorithm solving a static problem (and meeting some additional rather natural requirements) and outputs a self-stabilizing algorithm for the same problem. The transformer is built using a re-execution approach (the technique consisting of executing an algorithm repeatedly in order to obtain its self-stabilizing version). We show that in the model we use, a transformer based on such an approach is impossible without the assumption of an unbounded memory agent.     

Retina subjected to components of ischemia in vitro. Selective vulnerability and minimum lethal exposure of neurons and glia to oxygen and/or glucose deprivation and to loss of exchange with incubating medium

Rabbit retinas were incubated at 37 C in media lacking oxygen, glucose, or both, or sealed in a small compartment without medium to convert them to a "closed system." They were then returned to control medium before being fixed for microscopy. Other retinas were incubated only in control medium and then fixed. Conversion of the retina to a closed system caused irreversible damage to all cell types within 40 minutes. Combined deprivation of oxygen and glucose also irreversibly damaged the neuronal cells within 40 minutes, but Mueller cells,the principal glial cells of the retina, were not irreversibly altered by 90 minutes of the deprivation. Deprivation of oxygen alone caused irreversible damage to receptor cells in 80 minutes, but the cells of the inner nuclear layer, ganglion cells, and Mueller cells retained normal structure for at least 180 minutes. Deprivation of glucose alone damaged receptor cells in 160 minutes and the other neuronal cells in 180 minutes, but did not irreversibly damage Mueller cells by 200 minutes.     

Deterministic Resource Discovery in Distributed Networks

The resource discovery problem was introduced by Harchol-Balter, Leighton, and Lewin. They developed a number of algorithms for the problem in the weakly connected directed graph model. This model is a directed logical graph that represents the vertices’ knowledge about the topology of the underlying communication network. The current paper proposes a deterministic algorithm for the problem in the same model, with improved time, message, and communication complexities. Each previous algorithm had a complexity that was higher at least in one of the measures. Specifically, previous deterministic solutions required either time linear in the diameter of the initial network, or communication complexity $O(n^3)$ (with message complexity $O(n^2)$), or message complexity $O(|E_0| \log n)$ (where $E_0$ is the arc set of the initial graph $G_0$). Compared with the main randomized algorithm of Harchol-Balter, Leighton, and Lewin, the time complexity is reduced from $O(\log^2n)$ to\pagebreak[4] $O(\log n )$, the message complexity from $O(n \log^2 n)$ to $O(n \log n )$, and the communication complexity from $O(n^2 \log^3 n)$ to $O(|E_0|\log ^2 n )$. \par Our work significantly extends the connectivity algorithm of Shiloach and Vishkin which was originally given for a parallel model of computation. Our result also confirms a conjecture of Harchol-Balter, Leighton, and Lewin, and addresses an open question due to Lipton.     

Parameter reference immutability: formal definition, inference tool, and comparison

Knowing which method parameters may be mutated during a method’s execution is useful for many software engineering tasks. A parameter reference is immutable if it cannot be used to modify the state of its referent object during the method’s execution. We formally define this notion, in a core object-oriented language. Having the formal definition enables determining correctness and accuracy of tools approximating this definition and unbiased comparison of analyses and tools that approximate similar definitions. We present Pidasa, a tool for classifying parameter reference immutability. Pidasa combines several lightweight, scalable analyses in stages, with each stage refining the overall result. The resulting analysis is scalable and combines the strengths of its component analyses. As one of the component analyses, we present a novel dynamic mutability analysis and show how its results can be improved by random input generation. Experimental results on programs of up to 185 kLOC show that, compared to previous approaches, Pidasa increases both run-time performance and overall accuracy of immutability inference.     

An Integrated Assessment of the Impacts of Hydrogen Economy on Transportation, Energy Use, and Air Emissions

This paper presents an analysis of the potential system-wide energy and air emissions implications of hydrogen fuel cell vehicle (H ₂-FCV) penetration into the U.S. light duty vehicle (LDV) fleet. The analysis uses the U.S. EPA MARKet ALlocation (MARKAL) technology database and model to simultaneously consider competition among alternative technologies and fuels, with a focus on the transportation and the electric sectors. Our modeled reference case suggests that economics alone would not yield H₂-FCV penetration by 2030. A parametric sensitivity analysis shows that H₂-FCV can become economically viable through reductions in H ₂-FCV costs, increases in the costs of competing vehicle technologies, and increases in oil prices. Alternative scenarios leading to H₂-FCV penetration are shown to result in very different patterns of total system energy usage depending on the conditions driving H₂-FCV penetration. Overall, the model suggests that total CO₂ emissions changes are complex, but that CO₂ emission levels tend to decrease slightly with H₂-FCV penetration. While carbon capture and sequestration technologies with H ₂ production and renewable technologies for H₂ production have the potential to achieve greater CO₂ reductions, these technologies are not economically competitive within our modeling time frame without additional drivers     

Fast computation of limit cycles in an industrial application

A model problem is described that requires the study of a system of the form v(t) = F _P (v(t), t) which depends on a set of parameters P, and where 1. The problem comes from an industrial application where it is a kernel of an optimization procedure. The optimization depends on computing the limit cycle, and the problem needs to be solved repeatedly. Short computation time is therefore essential. The naive approach is to integrate the equation forward in time, starting from an arbitrary initial condition, until the transients disappear and the limit cycle is approximated within a given tolerance. This approach is too slow and thus impractical in the context of the optimization procedure. The problem involves two types of asymptotic considerations: long-time asymptotics and small-parameter asymptotics. Here a simple approach is demonstrated, based on implementing the averaging method. This reduces the solution time to the point that the optimization procedure becomes feasible.