My role is Smartcool Engineering support for the Americas. In this role I travel extensively training personnel in sales, technical operation, installation, and demonstrating different applications of the Smartcool technology. Previously, I spent 20 years as an Engineer with Pratt & Whitney and 5 years with Carrier. I've been involved with energy conservation technologies for about 10 years.
Firstly, Smartcool has nothing to do with power factor correction. I've applied PFC many times successfully and it works well within certain limitations. The Wikipedia article on it is quite good and all power and electrical engineers should be conversant on the topic.
Smartcool technology has been around since the mid-eighties and was originally developed in Australia. It is used extensively down under and in Europe, and with some markets in Asia. US introduction was in 2006 and is continuing. The technology has been independently tested and validated, but it isn't really anything new. We certainly knew about it at Carrier, but didn't pursue it because it was pretty advanced predictive software (read RISKY) and we built steel boxes.
Fundamentally it is a cycle optimizer. Thermodynamically, it takes advantage of the higher COP during periods of high suction pressure. The trick is to keep track of the cycles in order to predict the next minimum run period. The savings percentage is dependent on the amount of reserve capacity and the pattern of loading. For DX cycles, typical AC/Heat pump numbers are 15-30%. Rfrigeration numbers can be better due to the more predictable nature of the load pattern.
The Smartcool algorithm is learning and dynamic which is necessary because the thermal load is dynamic, wildly nonlinear, and changes each cycle. Additionally, each system has a unique reserve capacity that is interacting with the thermal load. We have been asked before to provide an analytical predictive model for the Smartcool performance. This has proved impractical since these are multi-variable systems. A least squares curve fitting approach only works for one specific installation. Regression analysis works pretty well, but only in comparing optimizing and non-optimizing periods on a specific installation and significantly dependent on OAT. Analytically, given the precise equations of a system and environment, it would probably be possible to numerically iterate a 365 day performance model vs. suction pressure. That sounds like a good graduate project.
Practically speaking, for DX systems we encourage our distributors to base savings calculations on 15% of the utilization rate. That is a "safe" minimum value. From there, add the RLA and FLA of the condenser times the voltage, and adjust for 3 phase (1.73) and real power as desired. Of course, we have spreadsheets for those calculations.
Thank you for the input regarding our web site. We are always looking to improve and welcome backhanded comments. In my experience, it is a mistake to ever think utilities are public service philanthropic entities. They are regulated monopolies and behave accordingly.
