Formal Engineering Education has traditionally been delivered using the low technology-high touch lecturing method, in which the lecturer and student meet face to face. Distance education in this field has been quite slow to develop primarily because of difficulty in delivery of practical based instructions and problems on integrity of assessments. Developments in information technology and the increased demand for further education by people already in employment have however changed this even in developing countries. It puts extra demand on Lecturers to guide distance learners in handling numerical computations so prevalent in Engineering. At the campuses, computer based methods are available in the high touch-high tech lecture method. High level and efficient computer software is used to help the student to simulate and solve some problems. However, such software is expensive-and therefore-not readily available to the distant learner. Spreadsheets on the other hand are almost universal on today's computers and they bridge the gap between hand calculations and high level programme computations. This paper therefore makes a case for the use of spreadsheets in Distance Engineering
TRNSYS stands for transient system simulation software. This paper describes a procedure that was used to validate a TRNSYS model for estimating electricity yields from a fixed slope photovoltaic (PV) panel. The objective was to find how close to reality predicted energy yield for a specified panel can be, at a location near one of the weather stations listed in the software's database. The software was used to predict daily total incident radiation on a horizontal plane and electrical energy yields from a 90 Wp panel when sloped at 34• facing north at a test site in Cape Town, SouthAfrica. The panel and other system components were then installed and tested to give actual electrical energy yields.The site was 5 km from a TRNSYS listed weather station. A local weather station logging 10-min data of actual total incident radiation on a horizontal plane enabled comparison with the model's estimate. Analysis of electrical energy yield gave statistical kappa values of 0.722 and 0.944 at actual to model acceptance ratio levels of 90% and 80%, respectively.Regression analysis of measured and model incident horizontal plane energy gave a coefficient of 0.782 across the year.It was thus concluded that within limits of meteorological phenomena behaviour, TRNSYS modelling reliably predicted energy yields from the PV panel installed in the neighbourhood of one of the software's listed stations.
That solar tracking improves energy yields from solar harvest systems is not debatable. Nor is the under powering of tropical Africa amidst plenty of energy resources – including solar. This paper presents a review of recent literature on tracking as applied to domestic solar harnessing devices. The purpose is to find basic requirements in design of a suitable solar tracker for the region’s rural homes. It is concluded that Single axis passive trackers possibly will stand better chances of acceptability in the region.
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