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This is the second page of REIS. Here the user is about to decide on just how much energy he/she would like to save. There are so many variations in the possible savings that can be obtained that this is left primarily up to the user. If the user can justify that by employing sophisticated control systems the energy demand of their estate will fall by a certain
percentage then by all means employ that technology. The principle barrier to this is of course "How much does it cost". The items can be classified as low cost, medium cost and high cost measures and their deployment depends heavily on the estate's Energy Efficiency Budget. |
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This is the third page of REIS. This is the Renewable Supply Page. To date the wind turbine option, the roof mounted photovoltaics and the Combined Heat and Power Options are available. With further work the Passive Solar Heating, Waste Heat Recovery and Daylight Maximisation strategies using light shelves etc. will be incorporated. As it is now Daylight Maximisation should be considered in the Demand Reduction page. Using data obtianed from manufacturers and the like the specifications for each of these renewable systems can be inserted as well as the other necessary building dimensions REIS requires. Please refer to REIS's rules page for a full description of the factors required. | ![]() |
This is the final page of REIS. The graphical output of the Supply and Demand are presented. On this page
the user has the ability to modify the demand curve to reflect the energy consumption of components within the estate. For
example lighting might account for 60% of the total electrical load so in the first red rectangle the user enters 0.6. The demand curve
shifts to mimic this change. The user then becomes a dispatcher by selecting different renewable sources and comparing their
relative demand matching effects. |
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One case study was to observe the Livingstone Tower and it was noted that:
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Some more results that we obtained using some of the buildings within the University's City Campus that are supplied from
the number one Mains Substation. The following is a list of the buildings and the data we obtained from contacts within the University.
Now what we did was to assume that 25% Demand Reduction Measures was implemented and Photovoltaics and Wind Turbines were aggressively deployed. The results obtained are very academic as many assumptions were made such as ignoring turbulent wind effects and so on. The following image is an actual output from REIS.
By all means have a go using your own data. This file will download as a zipped file. The program is written in Microsoft Excel so you will have to unzip it, enable the macros and ENJOY!!!