And the day begins. It’s 5:40am, and my inbox has 43 e-mails. I use the characteristic silence of the hours before dawn to prepare myself for the day. This time, I need to work on the the Energy Demand and Utilization class that I teach on the second half of the Fall semester. Today’s lecture will try to introduce a few tools that can help us quantify the energy demand of different processes. The hardest part about this lecture is defining clear learning outcomes that aren’t too specialized or too broad.

Here is what I plan to cover this time around:

• We will begin the class by recreating, step by step, the Tom Murphy’s argument on a recent article titled “An exercise in galactic-scale energy“. We have already covered the past and present state of our global energy demand, so by allowing the class to briefly think about our future under different growth scenarios, I will hopefully set the context for understanding: (a) the limits of a sustained growth assumption, and (b) the importance of energy accounting. I encourage you to read this article if you haven’t already.
• From there we will take a slight detour and cover the basics of calculating energy losses in buildings due to heat conduction and ventilation. I will use David McKay’s book “Sustainable Energy Without the Hot Air” as the basis for this part of the lecture. The main objective here is to familiarize the students with the heat loss formulas and with the three major ways in which the energy demand of heating and cooling can be reduced (reducing the temperature demand, reducing the “leakiness” of the building, and improving the coefficient of performance).
• Lastly, I will very briefly introduce a few relevant tools that can help in the analysis of the energy demand of a system or process. Each one of these tools can be the topic of a full course, so my intention is primarily to define how and when they can be useful. They are: life cycle analysis, engineering economics, system dynamics (specifically casual loop diagrams), linear programming and multi-criteria optimization; and regression analysis.

Let’s see how it goes.

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Last revised on 2012/04/08