14.02.2011 lecture diary

First of all sorry to anyone who happens to read this post, as it may be bit less consistent than the others due to the fact that no lecture slides about this week’s lecture were posted at the time of me writing this, so this blog post is based completely on just my own notes and on what I remember of the lecture.

The lecture started with M.M. Rahman presenting software called HOMER to us. It seemed to have a limited free version available as well, so he recommended that we’d try it out.

What I was wondering about this program was that what is so special about it? It doesn’t take the location’s geography into account (i.e. no pathing algorithm or such), it doesn’t seem to take any outages into account (i.e. no Monte Carlo, just replacement as the equipment gets old), and doesn’t even have almost any data bundled with it.

The software seems to simply create different combinations of the equipment that it is told to take into account and all the sensitivities, and then brute force calculates each solution. Based on how much data is needed for the program to run, I’d estimate that it would be viable to code a similiar if not better program in the time window it takes to get all the required data in a new project. Also, the reason why solar power wasn’t competetive in the example during the lecture most probably wasn’t because it’s just expensive in general, but because the example location was quite windy. The viability of the renewable power varies very much based on the location, which even further underlines the problems of this very basic software.

Jukka Paatero then continued the lecture with the basics of how to construct a power system, how to discount value etc.. It was mostly a repetition for anyone who attended the preliminary course, but I was left wondering whether or not the risk of equipment breakdown is taken into account in the planning phase. By that I mean that if we have 50 batteries of smaller capacity, we have usually a smaller chance for total failure than if we have 1 battery with huge capacity. Also, the more complicated the individual parts are, the higher the chance of breakdown they have, and the harder they are to repair.

Our second program of the day was a Canadian Excel-based software called RETScreen. It was closed source, but freely available software with tons of bundled data including e.g. different wind statistics and various different data sheets of batteries, turbines and other parts of the power system. This is probably a software I’d try to use as a part of planning even if I’d end up some other software as well simply because it has so much data in one place.

The biggest problem with this software was that the load model is simplified, and it can’t be changed. To me, the compulsory use of Excel is also a negative aspect as I prefer to write my programs in a language that doesn’t require heavy to run software and Windows operating system.