Entanglement of mixed macroscopic superpositions: An entangling-power study

We investigate entanglement properties of a recently introduced class of macroscopic quantum superpositions in two-mode mixed states. One of the tools we use in order to infer the entanglement in this non-Gaussian class of states is the power to entangle a qubit system. Our study reveals features which are hidden in a standard approach to entanglement investigation based on the uncertainty principle of the quadrature variables. We briefly describe the experimental setup corresponding to our theoretical scenario and a suitable modification of the protocol which makes our proposal realizable within the current experimental capabilities.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.

Electrical energy storage and Smart Grid technologies to integrate the next generation of Renewable Power Systems

The growth of renewable power sources, distributed generation and the potential for alternative fuelled modes of transport such as electric vehicles has led to concerns over the ability of existing grid systems to facilitate such diverse portfolio mixes in already congested power systems. Internationally the growth in renewable energy sources is driven by government policy targets associated with the uncertainties of fossil fuel supplies, environmental issues and a move towards energy independence. Power grids were traditionally designed as vertically integrated centrally managed entities with fully dispatchable generating plant. Renewable power sources, distributed generation and alternative fuelled vehicles will place these power systems under additional stresses and strains due to their different operational characteristics. Energy storage and smart grid technologies are widely proposed as the tools to integrate these future diverse portfolio mixes within the more conventional power systems. The choice in these technologies is determined not only by their location on the grid system, but by the diversification in the power portfolio mix, the electricity market and the operational demands. This paper presents a high level technical and economic overview of the role and relevance of electrical energy storage and smart grid technologies in the next generation of renewable power systems.

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

Integrating wind power using intelligent electric water heating

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

Techniques and tools for parallelizing software

With the emergence of multicore and manycore processors, engineers must design and develop software in drastically new ways to benefit from the computational power of all cores. However, developing parallel software is much harder than sequential software because parallelism can't be abstracted away easily. Authors Hans Vandierendonck and Tom Mens provide an overview of technologies and tools to support developers in this complex and error-prone task. © 2012 IEEE.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.