alexmead's profile - activity

There is a single value metric related to energy balance called the balance point temperature (BPT). It's used with respect to heating (and only heating). BPT represents the outdoor dry bulb temperate at which the internal gains (solar, plug, etc) equal the losses through the envelope. Designs with lower BPT are better because it needs to be colder before the heater is turned on. It should be noted though, BPT is a simple metric that eliminates a lot of complexity and should be used with caution.

Is this what you're looking for?

No you wouldn't want to minimize the derivative of the cost function. Think back to introductory calculus, the derivative is a measure of how much the function is changing. You can find the minimum of a cost function by setting the derivative equal to zero (at minimums and maximum the derivative equals zero) then solve that equation for the variable of interest. For 1D this is easy, for nD (usual BPS) this is hard to visualize.

I would go ask your professor for an overview of the problem. Maybe he can offer you some extra pointers.

You could do a rough sensitivity analysis by staring with say an 8 surface approximation, then increasing to 12, then 16, etc. until the difference between successive simulations is less than some amount you are happy with accepting as an error. Not too scientific, but if you're just gonna use your judgement this may help inform it in a "smart" way.

GenOpt can be coupled to Energy Plus 8.2. In fact, GenOpt can run with any text file based I/O program, see the GenOpt Manual sections 9 and 11.

You may need to change the configuration file to have it implement the "Command" variable your operating system associates with E+ 8.2 instead of E+ 7.0. This is a simple text file modification located in the directory "cfg" which is located in the main GenOpt directory.

This type of modification, if you're not familiar with a command line, may be confusing and difficult. Once you spend some time and figure out command line operation for your operating system though you will find it quite easy. Good luck!

This question needs to be stated more clearly for your goals to be understood. Typically in a optimization problem you are trying to find a "sweet spot" within a set of model parameters which minimizes (or maximizes) the evaluation of some objective function (sometimes called a cost function).

An example optimization problem might be minimizing annual energy use in the HVAC system by varying the size of some external glazing. Intuitively we hypothesize there may be a "sweet spot" window size because heating energy use can be offset by solar gains, but windows also increase the U-value of the envelope increasing HVAC energy use. So you may set up an optimization problem with the objective function calculating annual HVAC energy use, and the parameter space being the window to wall ratio (WWR).

You wouldn't want to minimize temperature outright in an optimization, this would mean your optimal solution would have the coldest temperature be the optimal solution. Perhaps you want to minimize the time where some temperature range isn't maintained within the zone, where the objective function returns "unmet hours"?

For a clear mathematically rigorous explanation and classification of optimization problems, specifically related to building performance simulation, you should check out the GenOpt Manual, section 4.