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.

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.

Assessing the Impact of Technology on Aircraft Systems using Technology Impact Forecasting

In today’s atmosphere of constrained defense spending and reduced research budgets, determining how to allocate resources for research and design has become a critical and challenging task. In the area of aircraft design there are many promising technologies to be explored, yet limited funds with which to explore them. In addition, issues concerning uncertainty in technology readiness as well as the quantification of the impact of a technology (or combinations of technologies), are of key importance during the design process. This paper presents a methodology that details a comprehensive and structured process in which to quantitatively explore the effects of technology for a given baseline aircraft. This process, called Technology Impact Forecasting (TIF), involves the creation of a assessment environment for use in conjunction with defined technology scenarios, and will have a significant impact on resource allocation strategies for defense acquisition. The advantages and limitations of the method are discussed. In addition, an example TIF application, that of an Uninhabited Combat Aerial Vehicle, is presented and serves to illustrate the applicability of this methodology to a military system.

Dead But Delightful:Tourism and Memory in New Orleans Cemeteries

The book chapter examines the history of New Orleans cemeteries and their popular image, especially in regard to the tourism industry.

Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons

In many environmental valuation applications standard sample sizes for choice modelling surveys are impractical to achieve. One can improve data quality using more in-depth surveys administered to fewer respondents. We report on a study using high quality rank-ordered data elicited with the best-worst approach. The resulting "exploded logit" choice model, estimated on 64 responses per person, was used to study the willingness to pay for external benefits by visitors for policies which maintain the cultural heritage of alpine grazing commons. We find evidence supporting this approach and reasonable estimates of mean WTP, which appear theoretically valid and policy informative. © The Author (2011).