Methods in wind power prediction & forecasting

Globally on-shore wind power has seen considerable growth in all grid systems. In the coming decade off-shore wind power is also expected to expand rapidly. Wind power is variable and intermittent over various time scales because it is weather dependent. Therefore wind power integration into traditional grids needs additional power system and electricity market planning and management for system balancing. This extra system balancing means that there is additional system costs associated with wind power assimilation. Wind power forecasting and prediction methods are used by system operators to plan unit commitment, scheduling and dispatch and by electricity traders and wind farm owners to maximize profit. Accurate wind power forecasting and prediction has numerous challenges. This paper presents a study of the existing and possible future methods used in wind power forecasting and prediction for both on-shore and off-shore wind farms.

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.

Coxiella buvnetii infection of an aortic graft with multiple vertebral body erosion

Q fever is caused by Coxiella burnetii and often has an insidious clinical presentation. We describe a rare case of Q fever infection of an aortic graft presenting with pyrexia and constant severe midlumbar pain due to erosion of multiple vertebral bodies. After successful treatment with graft resection and extra-anatomic vascular reconstruction, the patient continues on lifelong antibiotic therapy. We also present regional Q fever epidemiologic data together with a review of all previously documented cases of Q fever infections of vascular prostheses.

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.

The VLT-FLAMES survey of massive stars: wind properties and evolution of hot massive stars in the Large Magellanic Cloud

We have studied the optical spectra of a sample of 28 O- and early B-type stars in the Large Magellanic Cloud, 22 of which are associated with the young star forming region N11. Our observations sample the central associations of LH9 and LH10, and the surrounding regions. Stellar parameters are determined using an automated fitting method ( Mokiem et al. 2005), which combines the stellar atmosphere code fastwind ( Puls et al. 2005) with the genetic algorithm based optimisation routine PIKAIA ( Charbonneau 1995). We derive an age of 7.0 +/- 1.0 and 3.0 +/- 1.0 Myr for LH9 and LH10, respectively. The age difference and relative distance of the associations are consistent with a sequential star formation scenario in which stellar activity in LH9 triggered the formation of LH10. Our sample contains four stars of spectral type O2. From helium and hydrogen line fitting we find the hottest three of these stars to be similar to 49- 54 kK ( compared to similar to 45- 46 kK for O3 stars). Detailed determination of the helium mass fraction reveals that the masses of helium enriched dwarfs and giants derived in our spectroscopic analysis are systematically lower than those implied by non-rotating evolutionary tracks. We interpret this as evidence for efficient rotationally enhanced mixing leading to the surfacing of primary helium and to an increase of the stellar luminosity. This result is consistent with findings for SMC stars by Mokiem et al. ( 2006). For bright giants and supergiants no such mass discrepancy is found; these stars therefore appear to follow tracks of modestly or non-rotating objects. The set of programme stars was sufficiently large to establish the mass loss rates of OB stars in this Z similar to 1/2 Z(circle dot) environment sufficiently accurate to allow for a quantitative comparison with similar objects in the Galaxy and the SMC. The mass loss properties are found to be intermediate to massive stars in the Galaxy and SMC. Comparing the derived modified wind momenta D-mom as a function of luminosity with predictions for LMC metallicities by Vink et al. ( 2001) yields good agreement in the entire luminosity range that was investigated, i.e. 5.0

Determining propeller induced erosion alongside quay walls in harbours using Artificial Neural Networks

In shallow waters, such as those found close to berth structures, the wash from a manoeuvring ship’s propeller can cause erosion of the seabed. This erosion can be increased if the wash intersects a berth structure. A number of researchers have undertaken model studies and used regression analysis to develop predictive relationships for the scouring action. This paper presents an experimental investigation with Artificial Neural Networks (ANN’s), used to analyse the results. The purpose of using ANN’s was to examine the prediction accuracy of the Networks in comparison with previous regression analysis methods. ANN’s were found to provide a more accurate method of predicting propeller wash scour than the equations presented by previous investigators.

Modelling gas storage with compressed air energy storage in a system with large wind penetrations

Installed wind capacity in the European Union is expected to continue to increase due to renewable energy targets and obligations to reduce greenhouse gas emissions. Renewable energy sources such as wind power are variable sources of power. Energy storage technologies are useful to manage the issues associated with variable renewable energy sources and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in electric power systems and can be used in each of the steps of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothening the variability of large penetrations of wind power. Compress Air Energy Storage is one such technology. The aim of this paper is to examine the technical and economic feasibility of a combined gas storage and compressed air energy storage facility in the all-island Single Electricity Market of Northern Ireland and the Republic of Ireland in order to optimise power generation and wind power integration. This analysis is undertaken using the electricity market software PLEXOS ® for power systems by developing a model of a combined facility in 2020.