Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Irwin, G. (2008Abstract: The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting.The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade -Lucus -Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

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The assessment of well-designed road-lighting systems is necessary since their performance can be critically reduced by incorrect installation. During the operational life of a system, it is also necessary to assess the effects of deterioration in the luminaire fittings, changes in road surface or surroundings and changing user needs. An automated vehicle-mounted system constitutes the most practical technical solution to carry out this task. Previous research produced image acquisition and analysis systems for measuring luminance and uniformity levels of road lighting (Glenn 2000). This paper builds on this work and describes the methods employed to assess the combined parameters of luminance, illuminance and glare.A description of the system components is given, including the CCD digital video cameras, which are mounted on the test vehicle. The cameras are pre-calibrated to estimate relationships between gray value of light images and lighting parameters (luminance and illuminance). Appropriate infra-red and neutral density filters are employed to control the wavelength and limit the light entering into the cameras.Differential GPS, 3D orientation sensors, and image flow analysis, are employed to accurately estimate the position of the vehicle. Automated image analysis methods are further developed to speed up the position and image analysis process.Multidirectional measurements of light output are achieved using multiple journeys and multiple cameras on the same road-segment, which provide data on different observation lines. Interpolation techniques are employed to estimate the complete profile and produce isolux contours. Results produced so far indicate that lighting A Zatari:

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This paper presents a novel measurement system that assesses the uniformity of a complete airport lighting installation. The system improves safety with regard to aircraft landing procedures by ensuring airport lighting is properly maintained and conforms to current standards and recommendations laid down by the International Civil Aviation Organisation.The measuring device consists of a CMOS vision sensor with associated lens system fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images during a normal approach to an aerodrome. These images are then post processed to determine the uniformity of the complete pattern.Airport lighting consists of elevated approach and inset runway luminaires. Each luminaire emits an intensity which is dependant on the angular displacement from the luminaire. For example, during a normal approach a given luminaire will emit its maximum intensity down to its minimum intensity as the aircraft approaches and finally passes over the luminaire. As such, it is possible to predict the intensity that each luminaire within the airport lighting pattern emits, at a given time, during a normal approach. Any luminaires emitting the same intensity can then be banded together for the uniformity analysis.Having derived the theoretical groups of similar luminaires within a standard approach, this information was applied to a sequence of airport lighting images that were recorded during an approach to Belfast International Airport.Since we are looking to determine the uniformity of the pattern, only the total pixel grey level representing each luminaire within each banded group needs to be extracted and tracked through the entire image sequence. Any luminaires which fail to meet the requirements (i.e. a threshold value depending on the performance of the other luminaires in that band) are monitored and reported to the assessor for attention.The extraction and tracking algorithms have been optimised for minimal human intervention. Techniques such as component analysis as well as centre of mass algorithms are used to detect and locate the luminaires. A search algorithm is used to obtain the brightness (total grey level) of each luminaire.For the sample test at Belfast International Airport several luminaires were found that do not output sufficient intensity. As a final conclusion however, the Belfast International lighting pattern is legal and conforms to standards as no two consecutive luminaires fail in the pattern.The techniques used in this paper are novel. No known research exists that couples uniformity of airport lighting with photometrics. A solid basis has been established for future work on monitoring the individual characteristics of the luminaires. This includes colour and intensity measurements. Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/23/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx Vision Sensor(s) Mosnting PItfonn E.g. Focal Length USB2.O Power & Conenes Sofficare 4_+LIIII Pesi...