A medium-temperature solar thermal power system and its efficiency optimisation

This paper firstly expounds that the reheat-regenerative Rankine power cycle is a suitable cycle for the parabolic trough collector, a popular kind of collector in the power industry. In a thermal power cycle, the higher the temperature at which heat is supplied, the higher the efficiency of the cycle. On the other hand, for a given kind of collector at the same exiting temperature, the higher the temperature of the fluid entering the collector, the lower the efficiency of the collector. With the same exiting temperature of the solar field and the same temperature differences at the hottest end of the superheater/reheater and at the pinch points in the heat exchangers (e.g., the boiler) in the cycle, the efficiencies of the system are subject to the temperature of the fluid entering the collector or the saturation temperature at the boiler. This paper also investigates the optimal thermal and exergetic efficiencies for the combined system of the power cycle and collector. To make most advantage of the collector, the exiting fluid is supposed to be at the maximum temperature the collector can harvest. Hence, the thermal and exergetic efficiencies of the system are related to the saturation temperature at the boiler here.

Management of power line easement vegetation for small mammal conservation in Australia : a case study of the broad-toothed rat (Mastacomys fuscus)

Within Australia, very little attention has been given to the potential biodiversity benefits of power line easements, if ecologically sensitive management regimes are developed. This study examined the potential power line easements may have for the conservation of small mammals, and in particular the near threatened, Broad-toothed Rat Mastacomys fuscus, in Australia. Easement vegetation was found to support a diverse small mammal community, including M. fuscus if the vegetation was allowed to develop some structural complexity. M. fuscus was one of the first species to recolonize the easement habitat, provided that the areas had regenerated to a sufficient level. Results suggests; however, that the current management technique used, where the entire easement is managed at one time via mass slashing, on short rotation times, is most likely limiting M. fuscus to low abundances, and causing isolation of the current M. fuscus populations. To ensure that power line easements supply functional, usable habitat for small mammals and other species and to minimize their potential to fragment small mammal populations, it is recommended that current management techniques be reassessed. In an effort to develop more appropriate management regimes, it was recommended that rotation times be increased between management, that mass slashing of the easement at one time be reassessed, especially in naturally low growing areas and that rotational type slashing be implemented. Other techniques such as spot spraying, may be all that is needed within some areas to control emergent saplings. This study highlights that potential biodiversity values do exist for Australian power line easements, if some changes occur to the current management practices.

Insectivore life histories: further evidence against an optimum body size for mammals

1. This study tests a model of the relationship of body mass to reproductive power (the rate of conversion of energy from the environment to an organism’s offspring). Specifically tested is the prediction that the regression of life-history variables on body size will change slope and sign about an ‘optimum’ body mass of 100 g.
2. Life-history data from the mammalian order Insectivora have been collated and analysed using a phylogenetic comparative method to test this prediction.
3. The analyses showed little evidence for significant changes in slope or sign around 100 g body mass, or other possible optimal body masses, contradicting the predictions of the model. These findings agree with those of similar analyses on life-history variables of bats.

A three-dimensional highly interconnected composite oxygen reduction reaction electrocatalyst prepared from a core-shell precursor

Getting intimate: A 3D interconnected Bi_0.5Sr _0.5FeO_3-ð (BSF)-Ag electrocatalyst is prepared from a BSF-AgNO₃ core-shell precursor in one step. The nanometer-sized Ag enhances the sintering process, enabling an optimum cathode microstructure and good cathode-to-electrolyte attachment upon firing at 850°C. A solid-oxide fuel cell based on this cathode shows a near 100% peak power density enhancement at 550°C.

Application of power functions to chromatographic data for the enhancement of signal to noise ratios and separation resolution

Chromatographic detection responses are recorded digitally. A peak is represented ideally by a Guassian distribution. Raising a Guassian distribution to the power ‘n’ increases the height of the peak to that power, but decreases the standard deviation by √n. Hence there is an increasing disparity in detection responses as the signal moves from low level noise, with a corresponding decrease in peak width. This increases the S/N ratio and increases peak to peak resolution. The ramifications of these factors are that poor resolution in complex chromatographic data can be improved, and low signal responses embedded at near noise levels can be enhanced. The application of this data treatment process is potentially very useful in 2D-HPLC where sample dilution occurs between dimension, reducing signal response, and in the application of post-reaction detection methods, where band broadening is increased by virtue of reaction coils. In this work power functions applied to chromatographic data are discussed in the context of (a) complex separation problems, (b) 2D-HPLC separations, and (c) post-column reaction detectors.

An approach for wind power integration using demand side resources

Renewable energy resources, especially wind power, are expected to provide a considerable portion of the world energy requirements in the near future. Large-scale wind power penetration impacts the electricity industry in many aspects and raises a number of technical challenges for the electricity network. A day-ahead network-constrained market clearing formulation is proposed which considers demand side resources. The proposed approach can provide flexible load profile and reduce the need for ramp up/down services by the conventional generators. This method can potentially facilitate a large penetration of wind power by shifting the wind power generation from the off-peak periods to the high-peak hours. The validity of the proposed approach has been verified using the IEEE 30 bus and 57 bus test systems.

Design and analysis of efficient rectifiers for wireless power harvesting in DBS devices

This paper presents an analysis of optimum rectifier circuits for wireless energy harvesting in deep brain stimulation (DBS) devices. Since DBS demands compact and low power consumption devices, small, high conversion efficient, and high output voltage rectifiers need to be developed. The investigation that is presented in this paper is analytical and simulated based. Analysis on a variety of circuit configurations brings more evidence to improve the performance of rectifiers. Analytical parameters influencing the output DC voltage and the efficiency of the rectifiers are described. The operating frequency of the 915 MHz industrial, scientific and medical (ISM) radio band is used in this study. The maximum conversion efficiency of the LC matched half wave rectifier, the Greinacher voltage doubler, the Delon doubler, and the 2-stage voltage multiplier is obtained as 56.34%, 74.45%, 71.48%, and 31.44%, respectively, at the 30 dBm input power level. The corresponding maximum output DC voltages are 6.27 V, 16.83 V, 13.36 V, and 9.20 V. Thus the Greinacher voltage doubler is deemed as the best configuration according to the conversion efficiency and the output voltage measurements.

A scalable and automatic mechanism for resource allocation in self-organizing cloud

Taking advantage of the huge potential of consumers’ untapped computing power, self-organizing cloud is a novel computing paradigm where the consumers are able to contribute/sell their computing resources. Meanwhile, host machines held by the consumers are connected by a peer-to-peer (P2P) overlay network on the Internet. In this new architecture, due to large and varying multitudes of resources and prices, it is inefficient and tedious for consumers to select the proper resource manually. Thus, there is a high demand for a scalable and automatic mechanism to accomplish resource allocation. In view of this challenge, this paper proposes two novel economic strategies based on mechanism design. Concretely, we apply the Modified Vickrey Auction (MVA) mechanism to the case where the resource is sufficient; and the Continuous Double Auction (CDA) mechanism is employed when the resource is insufficient. We also prove that aforementioned mechanisms have dominant strategy incentive compatibility. Finally, extensive experiment results are conducted to verify the performance of the proposed strategies in terms of procurement cost and execution efficiency.

A novel distributed algorithm for power loss minimizing in Smart Grid

Because power generation of renewable resources are unstable and demands of the customers are time-varying, the supply power and demands of the customers are always unequal. To meet the demands of the customers, power is transmitted from primary power generation to secondary power generation. It will cause high power loss. To solve this problem, a distributed algorithm is proposed in this paper. By using the algorithm, the micro-grids are able to exchange power with their neighbors so as to minimize the total power losses of the smart grid. Moreover, communication overhead (bandwidth) is reduced, comparing with centralized algorithm. Through computer simulations, we demonstrate that the proposed algorithm can lead to near-optimal result for alleviating the average power loss per micro-grid and reduce the communication overhead significantly in contrast with the centralized approach.

A time series ensemble method to predict wind power

Wind power prediction refers to an approximation of the probable production of wind turbines in the near future. We present a time series ensemble framework to predict wind power. Time series wind data is transformed using a number of complementary methods. Wind power is predicted on each transformed feature space. Predictions are aggregated using a neural network at a second stage. The proposed framework is validated on wind data obtained from ten different locations across Australia. Experimental results demonstrate that the ensemble predictor performs better than the base predictors.

Influence of rest interval duration on muscular power production in the lower-body power profile

There is a paucity of evidence-based support for the allocation of rest interval duration between incremental loads in the assessment of the load-power profile. We examined the effect of rest interval duration on muscular power production in the load-power profile and sought to determine if greater rest is required with increasing load (i.e., variable rest interval). Ten physically trained men completed 4 experimental conditions in a crossover balanced design. Participants performed jump squats across incremental loads (0-60 kg) on 4 occasions, with an allocated recovery interval of 1, 2, 3, or 4 minutes. The mean log-transformed power output at each load was used for comparison between conditions (rest intervals). Unloaded jump squats (0 kg) maximized power output at each condition. The maximal mechanical power output was 66.6 ± 6.5 W·kg (1 minute), 66.2 ± 5.2 W·kg (2 minutes), 67.1 ± 5.9 W·kg (3 minutes), and 66.2 ± 6.5 W·kg (4 minutes). Trivial or unclear differences in power output were observed between rest intervals at each incremental load. As expected, power declined per 10 kg increment in load, the magnitude of decrease was 13.9-14.5% (confidence limits [CL]: ±1.3-2.0%) and 13.4-14.6% (CL: ±2.4-3.9%) for relative peak and mean power, respectively, yet differences in power output between conditions were likely insubstantial. The prescription of rest intervals between loads that are longer than 1 minute have a likely negligible effect on muscular power production in the jump squat incremental load-power profile. Practitioners should select either a 1- to 4-minute rest interval to best accommodate the logistical constraints of their monitoring sessions.

Analytical assessment of optimum magnet pole-arc for PMSM under influence of different magnetization patterns

Permanent magnet synchronous machines (PMSMs) are popular in both industrial and domestic applications because of its high efficiency, power density, and reliability as compared with the conventional types of electrical machines. Generally, the analytical models and their field solutions are preferable to provide an accurate insight of the PMSM performances, instead of using the finite element models, because the former takes a considerably shorter computational time. PMSM design could have different properties of either slotted or slotless, or varieties of magnet placement on the rotor. By focusing on semi-closed surface-mounted PMSMs, the 2D analytical subdomain model in [1] demonstrates an accurate prediction of the magnetic fields that can facilitate the evaluation of the global quantities of PMSMs, such as cogging torque (Tcog), back-EMF, and total harmonic distortion (THDv). Previously, researchers investigated the influences of the machine performance by a single factor, e.g., the variation of Tcog during changes of magnet pole-arc (αP) [2, 3], or slot-opening [2, 3]. These investigations normally considered two types of magnetization patterns, i.e., parallel (PaM) and radial magnetization (RM). Therefore, the motivation of our work hinges on predicting the optimum value of αP in designing a surface-mounted PMSM under influence of four different magnetization patterns, using the analytical subdomain model.

Distributed generation capacity planning for distribution networks to minimize energy loss: an unbalanced multi-phase optimal power flow based approach

This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.

Maximum power point tracking methods for PV systems

Maximum power point tracking (MPPT) is an important consideration in photovoltaic (PV) systems. These systems exhibit variable nonlinear current–voltage (I–V) and power–voltage (P–V) characteristics which vary with environmental conditions. The optimum operation of a PV system occurs when the system operates at the unique maximum power point (MPP) for the given environmental conditions. Key environmental conditions include the irradiance on the cell, temperature of the cell and any shading phenomenon. Shading can occur due to objects, dust or dirt and module mismatch arising from damage or manufacturing tolerances. These shading effects introduce further nonlinearity into the I–V and P–V characteristics of the system. An extensive variety of MPPT techniques has been proposed which vary from simple estimation techniques to advanced tracking techniques. In this chapter, the criteria for assessing the performance of MPPT methods are defined followed by a complete description and discussion of both techniques designed for uniform environmental conditions and those designed for nonuniform environmental conditions.