REIS TUTORIAL

(STRATHCLYDE UNIVERSITY)

REIS is a rules based Decision Support Package. The adjascent flow diagram shows how data is inserted, manipulated and presented as an output file. The user is responsible for data collection, site survey and all other numerical inputs requested by REIS. Once that is in...REIS will do the rest.



This first page allows the user to insert their personal details as well as the specifications of their estate. The photo can be scanned in to enhance the presentation value of the report. The factors requested on the right hand side (i.e. floor height, number of floors etc.) allow REIS to determine your available exposed wall area which will be used for different applications as you progress through the package.The bottom part of page one which allows the user access to the demand data page. From there the user inserts the total demand for which ever period and to whatever fidelity he/she chooses. REIS allows data entry of variable fidelity from half hourly to yearly. The three data entry options are EDI (Electronic Data Interchange), an ENTRACK (Entity Tracking) Data file, or manual insertion.

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.





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.








One case study was to observe the Livingstone Tower and it was noted that:
  • Livingston Tower was well laid out with offices and lecture theatres on the perimeter to maximise the daylight potential.
  • The potential energy savings are tremendous with the introduction of good control strategies. Too many lights and heaters were left on with no one in the building.
  • The active renewable energy contribution wind, pv's is "healthy". PV's have a rather dim future here in Glasgow based mainly on cost effectiveness. The wind contribution is a bit more respectable.




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.

What the output shows is that active renewables in the form of PV and Wind Power can meet 30% of November's load during the Spring to Autumn months. Obviously the demand curve will not be a straight line but for ease of explanation it was assumed to be so.

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!!!

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