Power system stability of a small sized isolated network supplied by a combined wind-pumped storage generation system: a case study in the Canary Islands

Massive integration of renewable energy sources in electrical power systems of remote islands is a subject of current interest. The increasing cost of fossil fuels, transport costs to isolated sites and environmental concerns constitute a serious drawback to the use of conventional fossil fuel plants. In a weak electrical grid, as it is typical on an island, if a large amount of conventional generation is substituted by renewable energy sources, power system safety and stability can be compromised, in the case of large grid disturbances. In this work, a model for transient stability analysis of an isolated electrical grid exclusively fed from a combination of renewable energy sources has been studied. This new generation model will be installed in El Hierro Island, in Spain. Additionally, an operation strategy to coordinate the generation units (wind, hydro) is also established. Attention is given to the assessment of inertial energy and reactive current to guarantee power system stability against large disturbances. The effectiveness of the proposed strategy is shown by means of simulation results.

A multi-agent system with distributed bayesian reasoning for network fault diagnosis

In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

ACKNOWLEDGMENTS MW and RVD have been supported by the German Federal Ministry for Education and Research (BMBF) via the Young Investigators Group CoSy-CC2 (grant no. 01LN1306A). JFD thanks the Stordalen Foundation and BMBF (project GLUES) for financial support. JK acknowledges the IRTG 1740 funded by DFG and FAPESP. MT Gastner is acknowledged for providing his data on the airline, interstate, and Internet network. P Menck thankfully provided his data on the Scandinavian power grid. We thank S Willner on behalf of the entire zeean team for providing the data on the world trade network. All computations have been performed using the Python package pyunicorn [41] that is available at https://github.com/pik-copan/pyunicorn.

A network of interacting transcriptional regulators involved in Drosophila neural fate specification revealed by the yeast two-hybrid system

Neural fate specification in Drosophila is promoted by the products of the proneural genes, such as those of the achaete–scute complex, and antagonized by the products of the Enhancer of split [E(spl)] complex, hairy, and extramacrochaetae. As all these proteins bear a helix-loop-helix (HLH) dimerization domain, we investigated their potential pairwise interactions using the yeast two-hybrid system. The fidelity of the system was established by its ability to closely reproduce the already documented interactions among Da, Ac, Sc, and Extramacrochaetae. We show that the seven E(spl) basic HLH proteins can form homo- and heterodimers inter-se with distinct preferences. We further show that a subset of E(spl) proteins can heterodimerize with Da, another subset can heterodimerize with proneural proteins, and yet another with both, indicating specialization within the E(spl) family. Hairy displays no interactions with any of the HLH proteins tested. It does interact with the non-HLH protein Groucho, which itself interacts with all E(spl) basic HLH proteins, but with none of the proneural proteins or Da. We investigated the structural requirements for some of these interactions by site-specific and deletion mutagenesis.

The Yeast GRD20 Gene Is Required for Protein Sorting in the trans-Golgi Network/Endosomal System and for Polarization of the Actin Cytoskeleton

The proper localization of resident membrane proteins to the trans-Golgi network (TGN) involves mechanisms for both TGN retention and retrieval from post-TGN compartments. In this study we report identification of a new gene, GRD20, involved in protein sorting in the TGN/endosomal system of Saccharomyces cerevisiae. A strain carrying a transposon insertion allele of GRD20 exhibited rapid vacuolar degradation of the resident TGN endoprotease Kex2p and aberrantly secreted ∼50% of the soluble vacuolar hydrolase carboxypeptidase Y. The Kex2p mislocalization and carboxypeptidase Y missorting phenotypes were exhibited rapidly after loss of Grd20p function in grd20 temperature-sensitive mutant strains, indicating that Grd20p plays a direct role in these processes. Surprisingly, little if any vacuolar degradation was observed for the TGN membrane proteins A-ALP and Vps10p, underscoring a difference in trafficking patterns for these proteins compared with that of Kex2p. A grd20 null mutant strain exhibited extremely slow growth and a defect in polarization of the actin cytoskeleton, and these two phenotypes were invariably linked in a collection of randomly mutagenized grd20 alleles. GRD20 encodes a hydrophilic protein that partially associates with the TGN. The discovery of GRD20 suggests a link between the cytoskeleton and function of the yeast TGN.

THE DESIGN OF A POWER SYSTEM FOR A WIRELESS SENSOR NETWORK FOR LONG-TERM OPERATION

Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.

The development of UTCS/NETSIM/ICG: an integrated urban traffic control system - network simulation - interactive computer graphics program. Final report.

Transportation Department, Office of University Research, Washington, D.C.

The national highway system: the backbone of America's intermodal transportation network.

Mode of access: Internet.

International global positioning system network for space science missions.

Mode of access: Internet.

NOR network transduction system : principles of the NETTRA system /

Bibliography: p. 209-212.

The network security center : a system level approach to computer network security /

Includes bibliographical references (p. 55).

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.