Intramolecular electronic energy transfer in bichromophoric macrocyclic complexes

Efficient intramolecular electronic energy transfer (EET) has been demonstrated for three novel bichromophoric compounds utilizing a macrocyclic spacer as the bridge between the electronic energy donor and acceptor fragments. As their free base forms, emission from the electronically excited donor is absent and the acceptor emission is reductively quenched via photoinduced oxidation of proximate amine lone pairs. As their Zn(II) complexes, excitation of the donor results in sensitization of the electronic acceptor emission.

Using siting algorithms in the design of marine reserve networks

Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

Development of a more efficient classifying cyclone

A more efficient classifying cyclone (CC) for fine particle classification has been developed in recent years at the JKMRC. The novel CC, known as the JKCC, has modified profiles of the cyclone body, vortex finder, and spigot when compared to conventional hydrocyclones. The novel design increases the centrifugal force inside the cyclone and mitigates the short circuiting flow that exists in all current cyclones. It also decreases the probability of particle contamination in the place near the cyclone spigot. Consequently the cyclone efficiency is improved while the unit maintains a simple structure. An international patent has been granted for this novel cyclone design. In the first development stage-a feasibility study-a 100 mm JKCC was tested and compared with two 100 min commercial units. Very encouraging results were achieved, indicating good potential for the novel design. In the second development stage-a scale-up stage-the JKCC was scaled up to 200 mm in diameter, and its geometry was optimized through numerous tests. The performance of the JKCC was compared with a 150 nun commercial unit and exhibited sharper separation, finer separation size, and lower flow ratios. The JKCC is now being scaled up into a fill-size (480 mm) hydrocyclone in the third development stage-an industrial study. The 480 mm diameter unit will be tested in an Australian coal preparation plant, and directly compared with a commercial CC operating under the same conditions. Classifying cyclone performance for fine coal could be further improved if the unit is installed in an inclined position. The study using the 200 mm JKCC has revealed that sharpness of separation improved and the flow ratio to underflow was decreased by 43% as the cyclone inclination was varied from the vertical position (0degrees) to the horizontal position (90degrees). The separation size was not affected, although the feed rate was slightly decreased. To ensure self-emptying upon shutdown, it is recommended that the JKCC be installed at an inclination of 75-80degrees. At this angle the cyclone performance is very similar to that at a horizontal position. Similar findings have been derived from the testing of a conventional hydrocyclone. This may be of benefit to operations that require improved performance from their classifying cyclones in terms of sharpness of separation and flow ratio, while tolerating slightly reduced feed rate.

Explicit/implicit partitioning and a new explicit form of the generalized alpha method

Most finite element packages use the Newmark algorithm for time integration of structural dynamics. Various algorithms have been proposed to better optimize the high frequency dissipation of this algorithm. Hulbert and Chung proposed both implicit and explicit forms of the generalized alpha method. The algorithms optimize high frequency dissipation effectively, and despite recent work on algorithms that possess momentum conserving/energy dissipative properties in a non-linear context, the generalized alpha method remains an efficient way to solve many problems, especially with adaptive timestep control. However, the implicit and explicit algorithms use incompatible parameter sets and cannot be used together in a spatial partition, whereas this can be done for the Newmark algorithm, as Hughes and Liu demonstrated, and for the HHT-alpha algorithm developed from it. The present paper shows that the explicit generalized alpha method can be rewritten so that it becomes compatible with the implicit form. All four algorithmic parameters can be matched between the explicit and implicit forms. An element interface between implicit and explicit partitions can then be used, analogous to that devised by Hughes and Liu to extend the Newmark method. The stability of the explicit/implicit algorithm is examined in a linear context and found to exceed that of the explicit partition. The element partition is significantly less dissipative of intermediate frequencies than one using the HHT-alpha method. The explicit algorithm can also be rewritten so that the discrete equation of motion evaluates forces from displacements and velocities found at the predicted mid-point of a cycle. Copyright (C) 2003 John Wiley Sons, Ltd.

Fast, scalable master equation solution algorithms. IV. Lanczos iteration with diffusion approximation preconditioned iterative inversion

In this paper we propose a second linearly scalable method for solving large master equations arising in the context of gas-phase reactive systems. The new method is based on the well-known shift-invert Lanczos iteration using the GMRES iteration preconditioned using the diffusion approximation to the master equation to provide the inverse of the master equation matrix. In this way we avoid the cubic scaling of traditional master equation solution methods while maintaining the speed of a partial spectral decomposition. The method is tested using a master equation modeling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long-lived isomerizing intermediates. (C) 2003 American Institute of Physics.

Fast, scalable master equation solution algorithms. III. Direct time propagation accelerated by a diffusion approximation preconditioned iterative solver

In this paper we propose a novel fast and linearly scalable method for solving master equations arising in the context of gas-phase reactive systems, based on an existent stiff ordinary differential equation integrator. The required solution of a linear system involving the Jacobian matrix is achieved using the GMRES iteration preconditioned using the diffusion approximation to the master equation. In this way we avoid the cubic scaling of traditional master equation solution methods and maintain the low temperature robustness of numerical integration. The method is tested using a master equation modelling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long lived isomerizing intermediates. (C) 2003 American Institute of Physics.

High energy radiation grafting of fluoropolymers

Fluoropolymers are known as chemically inert materials with good high temperature resistance, so they are often the materials of choice for harsh chemical environments. These properties arise because the carbon-fluorine bond is the strongest of all bonds between other elements and carbon, and, because of their large size, fluorine atoms can protect the carbon backbone of polymers such as poly(tetrafluoroethylene), PTFE, from chemical attack. However, while the carbon-fluorine bond is much stronger than the carbon hydrogen bond, the G values for radical formation on high energy radiolysis of fluoropolymers are roughly comparable to those of their protonated counterparts. Thus, efficient high energy radiation grafting of fluoropolymers is practical, and this process can be used to modify either the surface or bulk properties of a fluoropolymer. Indeed, radiation grafted fluoropolymers are currently being used as separation membranes for fuel cells, hydrophilic filtration membranes and matrix substrate materials for use in combinatorial chemistry. Herein we present a review of recent studies of the high energy radiation grafting of fluoropolymers and of the analytical methods available to characterize the grafts. (C) 2003 Elsevier Ltd. All rights reserved.

Light pollution and energy efficiency: a case study of the village of Vialonga

Since industrialization and the formation of larger urban centers in the nineteenth century, pollution of the environment was always present in daily life in various ways, namely in the form of light. Light pollution can cause various consequences, both for humans and for their ecosystem, producing effects on environmental, social, economic and scientific level. In Portugal, the lighting is responsible for 3% of total electricity consumption, energy costs are in some cases more than 50% towards the costs incurred by municipalities with energy, checking-in recent years a trend similar to that improvement of illumination levels in the region (about 4 to 5% per year). Proper use of lighting brings many benefits both to the citizen and environment, since greater energy efficiency can contribute to reducing CO2 emissions, energy costs, as well as to decrease the use of resources not-renewable and/or contamination of renewable resources, which can occurs in the process of obtaining electricity. The present study has a main goal to analyze the illuminance levels associated to the public lighting of the village of Vialonga, Vila Franca de Xira (Portugal), to verify if it is efficient. The aim is also to relate the efficiency of street lighting with the existence of light pollution.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response