Multi-agent modelling for the simulation of a simple smart microgrid

The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission, and one logical layer for element communication. A simple case study is presented to analyse the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.

Complete agent based simulation of mini-grids

EuroPES 2009

An agent-based multi-scale wind generation model

(EuroPES 2009)

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.

Surface-Bound Selectin-Ligand Binding Is Regulated By Carrier Diffusion

Two-dimensional (2D) kinetics of receptor-ligand interactions governs cell adhesion in many biological processes. While the dissociation kinetics of receptor-ligand bond is extensively investigated, the association kinetics has much less been quantified. Recently receptor-ligand interactions between two surfaces were investigated using a thermal fluctuation assay upon biomembrane force probe technique (Chen et al. in Biophys J 94:694-701, 2008). The regulating factors on association kinetics, however, are not well characterized. Here we developed an alternative thermal fluctuation assay using optical trap technique, which enables to visualize consecutive binding-unbinding transition and to quantify the impact of microbead diffusion on receptor-ligand binding. Three selectin constructs (sLs, sPs, and PLE) and their ligand P-selectin glycoprotein ligand 1 were used to conduct the measurements. It was indicated that bond formation was reduced by enhancing the diffusivity of selectin-coupled carrier, suggesting that carrier diffusion is crucial to determine receptor-ligand binding. It was also found that 2D forward rate predicted upon first-order kinetics was in the order of sPs > sLs > PLE and bond formation was history-dependent. These results further the understandings in regulating association kinetics of surface-bound receptor-ligand interactions.

Parametric Analysis for Monitoring 2D Kinetics of Receptor-Ligand binding

Thermal fluctuation approach is widely used to monitor association kinetics of surface-bound receptor-ligand interactions. Various protocols such as sliding standard deviation (SD) analysis (SSA) and Page's test analysis (PTA) have been used to estimate two-dimensional (2D) kinetic rates from the time course of displacement of molecular carrier. In the current work, we compared the estimations from both SSA and modified PTA using measured data from an optical trap assay and simulated data from a random number generator. Our results indicated that both SSA and PTA were reliable in estimating 2D kinetic rates. Parametric analysis also demonstrated that such the estimations were sensitive to parameters such as sampling rate, sliding window size, and threshold. These results furthered the understandings in quantifying the biophysics of receptor-ligand interactions.

IL-8-induced L-selectin shedding regulates its binding kinetics to PSGL-1

L-selectin plays a crucial role in inflammation cascade by initiating the tethering and rolling of leukocytes on endothelium wall. While many L-selectin molecules are rapidly shed from the cell surface upon activation, the remaining membrane-anchored L-selectin may still play an important role in regulating leukocyte rolling and adhesion with different binding kinetics. Here we developed an in vitro model to activate Jurkat cells via interlukin-8 (IL-8) and quantified the two-dimensional (2D) binding kinetics, using a micropipette aspiration assay, of membrane-anchored L-selectin to P-selectin glycoprotein ligand 1 (PSGL-1) ligand coupled onto human red blood cells (RBCs). The data indicated that L-selectin shedding reduced the amount of membrane-anchored L-selectin and lowered both its reverse and forward rates. These results suggested that the rolling dynamics of activated leukocytes was determined by two opposite impacts: reducing the surface presentation would enhance the rolling but lowering the kinetic rates would decrease the rolling. This finding provides a new insight into understanding how L-selectin shedding regulates leukocyte rolling and adhesion.

Design, synthesis and characterization of sequence-specific DNA-cleaving metalloproteins

This thesis describes research pursued in two areas, both involving the design and synthesis of sequence specific DNA-cleaving proteins. The first involves the use of sequence-specific DNA-cleaving metalloproteins to probe the structure of a protein-DNA complex, and the second seeks to develop cleaving moieties capable of DNA cleavage through the generation of a non-diffusible oxidant under physiological conditions.

Chapter One provides a brief review of the literature concerning sequence-specific DNA-binding proteins. Chapter Two summarizes the results of affinity cleaving experiments using leucine zipper-basic region (bZip) DNA-binding proteins. Specifically, the NH_2-terminal locations of a dimer containing the DNA binding domain of the yeast transcriptional activator GCN4 were mapped on the binding sites 5'-CTGACTAAT-3' and 5'ATGACTCTT- 3' using affinity cleaving. Analysis of the DNA cleavage patterns from Fe•EDTA-GCN4(222-281) and (226-281) dimers reveals that the NH_2-termini are in the major groove nine to ten base pairs apart and symmetrically displaced four to five base pairs from the central C of the recognition site. These data are consistent with structural models put forward for this class of DNA binding proteins. The results of these experiments are evaluated in light of the recently published crystal structure for the GCN4-DNA complex. Preliminary investigations of affinity cleaving proteins based on the DNA-binding domains of the bZip proteins Jun and Fos are also described.

Chapter Three describes experiments demonstrating the simultaneous binding of GCN4(226-281) and 1-Methylimidazole-2-carboxamide-netropsin (2-ImN), a designed synthetic peptide which binds in the minor groove of DNA at 5'-TGACT-3' sites as an antiparallel, side-by-side dimer. Through the use of Fe•EDTA-GCN4(226-281) as a sequence-specific footprinting agent, it is shown that the dimeric protein GCN4(226-281) and the dimeric peptide 2- ImN can simultaneously occupy their common binding site in the major and minor grooves of DNA, respectively. The association constants for 2-ImN in the presence and in the absence of Fe•EDTA-GCN4(226-281) are found to be similar, suggesting that the binding of the two dimers is not cooperative.

Chapter Four describes the synthesis and characterization of PBA-β-OH-His- Hin(139-190), a hybrid protein containing the DNA-binding domain of Hin recombinase and the putative iron-binding and oxygen-activating domain of the antitumor antibiotic bleomycin. This 54-residue protein, comprising residues 139-190 of Hin recombinase with the dipeptide pyrimidoblamic acid-β-hydroxy-L-histidine (PBA-β-OH-His) at the NH2 terminus, was synthesized by solid phase methods. PBA-β-OH-His-Hin(139- 190) binds specifically to DNA at four distinct Hin binding sites with affinities comparable to those of the unmodified Hin(139-190). In the presence of dithiothreitol (DTT), Fe•PB-β-OH-His-Hin(139-190) cleaves DNA with specificity remarkably similar to that of Fe•EDTA-Hin(139-190), although with lower efficiency. Analysis of the cleavage pattern suggests that DNA cleavage is mediated through a diffusible species, in contrast with cleavage by bleomycin, which occurs through a non-diffusible oxidant.

Insights into the mechanism of human erythrocyte hexose transport : a transferred NOE study of glucose binding to GLUT1

This study examines binding of α- and β-D-glucose in their equilibrium mixture to the glucose transporter (GLUT1) in human erythrocyte membrane preparations by an ^1H NMR method, the transferred NOE (TRNOE). This method is shown theoretically and experimentally to be a sensitive probe of weak ligand-macromolecule interactions. The TRNOEs observed are shown to arise solely from glucose binding to GLUT1. Sites at both membrane faces contribute to the TRNOEs. Binding curves obtained are consistent with a homogeneous class of sugar sites, with an apparent K_D which varies (from ~30 mM to ~70 mM for both anomers) depending on the membrane preparation examined. Preparations with a higher proportion of the cytoplasmic membrane face exposed to bulk solution yield higher apparent KK_Ds. The glucose transport inhibitor cytochalasin B essentially eliminates the TRNOE. Nonlinearity was found in the dependence on sugar concentration of the apparent inhibition constant for cytochalasin B reversal of the TRNOE observed in the α anomer (and probably the β anomer); such nonlinearity implies the existence of ternary complexes of sugar, inhibitor and transporter. The inhibition results furthermore imply the presence of a class of relatively high-affinity (K_D < 2mM) sugar sites specific for the α anomer which do not contribute to NMR-observable binding. The presence of two classes of sugar-sensitive cytochalasin B sites is also indicated. These results are compared with predictions of the alternating conformer model of glucose transport. Variation of apparent K_D in the NMR-observable sites, the formation of ternary complexes and the presence of an anomer-specific site are shown to be inconsistent with this model. An alternate model is developed which reconciles these results with the known transport behavior of GLUT1. In this model, the transporter possesses (at minimum) three classes of sugar sites: (i) transport sites, which are alternately exposed to the cytoplasmic or the extracellular compartment, but never to both simultaneously, (ii) a class of sites (probably relatively low-affinity) which are confined to one compartment, and (iii) the high-affinity α anomer-specific sites, which are confined to the cytoplasmic compartment.

Indentification and characterization of a novel CA^(2+)-binding protein in avian erythrocytes

A novel Ca^(2+)-binding protein with Mr of 23 K (designated p23) has been identified in avian erythrocytes and thrombocytes. p23 localizes to the marginal bands (MBs), centrosomes and discrete sites around the nuclear membrane in mature avian erythrocytes. p23 appears to bind Ca^(2+) directly and its interaction with subcellular organelles seems to be modulated by intracellular [Ca^(2+)]. However, its unique protein sequence lacks any known Ca^(2+)-binding motif. Developmental analysis reveals that p23 association to its target structures occurs only at very late stages of bone marrow definitive erythropoeisis. In primitive erythroid cells, p23 distributes diffusely in the cytoplasm and lacks any distinct localization. It is postulated that p23 association to subcellular structures may be induced in part by decreased intracellular [Ca^(2+)]. In vitro and in vivo experiments indicate that p23 does not appear to act as a classical microtubule-associated protein (MAP) but p23 homologues appear to be expressed in MB-containing cells of a variety of species from different vertebrate classes. It has been hypothesized that p23 may play a regulatory role in MB stabilization in a Ca^(2+)-dependent manner.

Binucleated (bnbn) turkey erythrocytes were found to express a truncated p23 variant (designated p21) with identical subcellular localization as p23 except immunostaining reveals the presence of multi-centrosomes in bnbn cells. The p21 sequence has a 62 amino acid deletion at the C-terminus and must therefore have an additional ~40 amino acids at the N-terminus. In addition, p21 seems to have lost the ability to bind Ca^(2+) and its supramolecular interactions are not modulated by intracellular [Ca^(2+)]. These apparent differences between p23 and p21 raised the possibility that the p23/p21 allelism could be the Bn/bn genotype. However, genetic analysis suggested that p23/p21 allelism had no absolute correlation with the Bn/bn genotype.

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.

Identification of fucose-α(1-2)-galactose binding proteins in the mammalian brain

Fucose-α(1-2)-galactose (Fucα(1-2)Gal) carbohydrates have been implicated in cognitive functions. However, the underlying molecular mechanisms that govern these processes are not well understood. While significant progress has been made toward identifying glycoconjugates bearing this carbohydrate epitope, a major challenge remains the discovery of interactions mediated by these sugars. Here, we employ the use of multivalent glycopolymers to enable the proteomic identification of weak affinity, low abundant Fucα(1-2)Gal-binding proteins (i.e. lectins) from the brain. End-biotinylated glycopolymers containing photoactivatable crosslinkers were used to capture and enrich potential Fucα(1-2)Gal-specific lectins from rat brain lysates. Candidate lectins were tested for their ability to bind Fucα(1-2)Gal, and the functional significance of the interaction was investigated for one such candidate, SV2a, using a knock-out mouse system. Our results suggest an important role for this glycan-lectin interaction in facilitating synaptic changes necessary for neuronal communication. This study highlights the use of glycopolymer mimetics to discover novel lectins and identify functional interactions between fucosyl carbohydrates and lectins in the brain.