Load-unload response ratio and accelerating moment/energy release critical region scaling and earthquake prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.

Distribution of a nematocyst-bearing sponge in relation to potential coral donors

Haliclona sp. 628 (Demospongiae, Haplosclerida, Chalinidae), a sponge found on the reef slope below 5 in depth on the Great Barrier Reef, has two unusual characteristics. It contains a symbiotic dinoflagellate, Symbiodinium sp., similar in structure to the dinoflagellate found within Acropora nobilis (S. microadriaticum), and it contains coral nematocysts randomly distributed between the ectosome and endosome and usually undischarged in intact sponge tissue. Given the unusual occurrence of nematocysts in Haliclona sp. 628, the focus of this study was to determine the distribution of this species of sponge on the reef slope at Heron Island Reef in relation to the distribution of potential coral donors. A combination of line and belt transects was used to estimate the abundance of Halielona sp. 628 and a co-occurring congener, Haliclona sp. 1031, which does not contain nematocysts, at three widely separated sites on the reef slope at Heron Island Reef. The abundance of different types of substratum (sand, sand-covered coral rubble, dead A. nobilis, live A. nobilis, other live coral, and other dead coral) along the transects and the substratum to which each sponge colony was attached were also recorded. Despite the predominance of live A. nobilis and sand-covered rubble at all sites, between 30 and 55% of Haliclona sp. 628 colonies were attached to dead A. nobilis which comprised less than 8% of the available substratum along any transect. In contrast, Haliclona sp. 1031 was found significantly more frequently on other dead corals and less frequently on live A. nobilis than would be expected based on the availability of the different substrata in the sites. Potential explanations to account for the distribution of Haliclona sp. 628 in relation to potential coral donors are discussed.

The characteristics of six species of living hollow-bearing trees and their importance for arboreal marsupials in the dry sclerophyll forests of southeast Queensland, Australia

Six species of trees located in the dry sclerophyll forests of southeast Queensland were studied to ascertain which was most suitable to be retained as hollow-bearing trees for nesting and denning by arboreal marsupials. Generally for all tree species, the number of entrances to hollows was positively correlated with the diameter at breast height (DBH) and the growth stage, and entrance diameters also increased in trees with a larger DBH. However, there were differences between the species; Corymbia citriodora had few hollows until the individuals were very large while Eucalyptus crebra had low numbers of hollows throughout its entire size range. It was concluded that a mixture of tree species provided a range of hollow sizes and positions that would be suitable for nesting and denning by arboreal marsupials in those forests. There were large differences between tree species in the relationship between tree size and estimated age. Five of the tree species took between 186 and 230 years to begin to produce hollows while E. crebra took up to 324 years. This suggests that tree species other than E. crebra may be the most preferred for retention in areas where hollow-bearing tree densities are lower than the prescribed level. Other data also suggests there are likely to be enough trees in larger size classes that would begin to form hollows within the next 50 years to compensate for an expected loss of hollow-bearing stags during that same period. In terms of forest operation, the retention of six hollow-bearing trees/ha would represent an estimated loss of 7.3-15% wood production. (C) 2003 Elsevier Science B.V. All rights reserved.

A reduced load approximation accounting for link interactions in a loss network

This paper is concerned with evaluating the performance of loss networks. Accurate determination of loss network performance can assist in the design and dimen- sioning of telecommunications networks. However, exact determination can be difficult and generally cannot be done in reasonable time. For these reasons there is much interest in developing fast and accurate approximations. We develop a reduced load approximation that improves on the famous Erlang fixed point approximation (EFPA) in a variety of circumstances. We illustrate our results with reference to a range of networks for which the EFPA may be expected to perform badly.

Molybdenum Complexes Bearing the Tris(1-pyrazolyl)methanesulfonate Ligand: Synthesis, Characterization and Electrochemical Behaviour

The tris(1-pyrazolyl)methanesulfonate lithium salt Li(Tpms) [Tpms = SO3C(pz)(3)-] reacts with [Mo(CO)(6)] in NCMe heated at reflux to yield Li[Mo(Tpms)(CO)(3)] (1), which, upon crystallization from thf, forms the coordination polymer [Mo(Tpms)(CO)(2)(mu-CO)Li(thf)(2)](n) (2). Reaction of 1 with I-2, HBF4 or AgBF4 yields [Mo(Tpms)I(CO)(3)] (3), (Mo(Tpms)-H(CO)(3)] (5) or (Mo(Tpms)O-2](2)(mu-O) (7), respectively. The high-oxidation-state dinuclear complexes [{Mo(Tpms)O(mu-O)}(2)] (4) and [{Mo(tpms)OCl)(2)](mu-O) (6) are formed upon exposure to air of solutions of 3 and 5, respectively. Compounds 1-7, which appear to be the first tris(pyrazolyl)methanesulfonate complexes of molybdenum to be reported, were characterized by IR, H-1 and C-13 NMR spectroscopy, ESI-MS, elemental analysis, cyclic voltammetry and, in the cases of Li(Tpms) and compounds 2, 4.2CH(3)CN, 6.6CHCl(3) and 7, by X-ray diffraction analyses. Li(Tpms) forms a 1D polymeric structure (i.e., [Li(tpms)](n)} with Tpms as a tetradentate N2O2 chelating ligand that bridges two Li cations with distorted tetrahedral coordination. Compound 2 is a 1D coordination polymer in which Tpms acts as a bridging tetradentate N3O ligand and each Li(thf)(2)(+) moiety is coordinated by one bridging CO ligand and by the sulfonyl group of a contiguous monomeric unit. In 4, 6 and 7, the Tpms ligand is a tridentate chelator either in the NNO (in 4) or in the NNN (in 6 and 7) fashion. Complexes 1, 3 and 5 exhibit, by cyclic voltammetry, a single-electron oxidation at oxidation potential values that indicate that the Tpms ligand has an electron-donor character weaker than that of cyclopentadienyl.

Synthesis, characterization and redox behaviour of benzoyldiazenido- and oxorhenium complexes bearing N,N- and S,S-type ligands

The reactions of [ReCl2{eta(2)-N2C(O)Ph}(PPh3)(2)](1) with 2-aminopyrimidine (H(2)Npyrm), 2,2'-bipyridine (bpy) and tetraethylthiuram disulfide (tds), in MeOH upon reflux, lead to the new eta(1)-(benzoyldiazenido)-rhenium(III) complexes [ReCl{eta(1)-N2C(O)Ph}(HNpyrm)(PPh3)(2)](2)and [ReCl2{eta(1)-N2C(O)Ph}(bpy)(PPh3)] (3), and the known oxo(diethyldithiocarbamato)dirhenium(v)complex [Re2O2(mu O){Et2NC(S)S}(4)](4), respectively. The Et2NC(S)S ligands in 4 result from S-S bond rupture of tds molecules. The obtained compounds have been characterized by IR, H-1, P-31{H-1} and C-13{H-1} NMR spectroscopies, FAB(+)-MS, elemental and single-crystal X-ray diffraction (for 2 and 4)analyses. Complex 2 represents the first structurally characterized Re compound derived from 2-aminopyrimidine. Besides, the redox behaviour of 2-4 in CH2Cl2 solution has been studied by cyclic voltammetry, and the Lever electrochemical ligand parameter (E-L)has been estimated, for the first time, for HNpyrm. The electrochemical results are discussed in terms of electronic properties of the Re centres and the ligands.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Ruthenium(II) Arene Complexes Bearing Tris(pyrazolyl)methanesulfonate Capping Ligands.Electrochemistry, Spectroscopic, and X-ray Structural Characterization

Novel [Ru(L)(Tpms)]Cl and [Ru(L)(Tpms(Ph))]Cl complexes (L = p-cymene, benzene, or hexamethylbenzene, Tpms = tris(pyrazolyl)-methanesulfonate, Tpms(Ph) = tris(3-phenylpyrazoly)methanesulfonate) have been prepared by reaction of [Ru(L)(mu-Cl)(2)](2) with Li[Tpms] and Li[Tpms(Ph)], respectively. [Ru(p-cymene)(Tpms)]BF4 has been synthesized through a metathetic reaction of [Ru(p-cymene)(Tpms)]Cl with AgBF4. [RuCl(cod)(Tpms)] (cod = 1,5-cyclooctadiene) and [RuCl(cod)(Tpms(Ph))] are also reported, being obtained by reaction of [RuCl2(cod)(MeCN)(2)] with Li[Tpms] and Li[Tpms(Ph)], respectively. The structures of the complexes and the coordination modes of the ligands have been established by IR, NMR, and single-crystal X-ray diffraction (for [RuL(Tpms)]X (L = p-cymene or HMB, X = Cl; L = p-cymene, X = BF4)) studies. Electrochemical studies showed that each complex undergoes a single-electron R-II -> R-III oxidation at a potential measured by cyclic voltammetry, allowing to compare the electron-donor characters of the tris(pyrazolyl)methanesulfonate and arene ligands, and to estimate, for the first time, the values of the Lever E-L ligand parameter for Tmps(Ph), HMB, and cod.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.