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AN OPTIMAL CONTROL APPROACH FOR DETERMINATION OF THE HEAT LOSS COEFFICIENT IN AN ICS SOLAR DOMESTIC WATER HEATING SYSTEM
Title
AN OPTIMAL CONTROL APPROACH FOR DETERMINATION OF THE HEAT LOSS COEFFICIENT IN AN ICS SOLAR DOMESTIC WATER HEATING SYSTEM.
Creator
Gil, Camilo, Simaan, Marwan, University of Central Florida
Abstract / Description
Water heating in a typical home in the U.S. accounts for a significant portion (between 14% and 25%) of the total homeÂÂÂÂ's annual energy consumption. The objective of considerably reducing the homeÂÂÂÂ's energy consumption from the utilities calls for the use of onsite renewable energy...
Show moreWater heating in a typical home in the U.S. accounts for a significant portion (between 14% and 25%) of the total homeÂÂÂÂ's annual energy consumption. The objective of considerably reducing the homeÂÂÂÂ's energy consumption from the utilities calls for the use of onsite renewable energy systems. Integral Collector Storage (ICS) solar domestic water heating systems are an alternative to help meet the hot water energy demands in a household. In order to evaluate the potential benefits and contributions from the ICS system, it is important that the parameter values included in the model used to estimate the systemÂÂÂÂ's performance are as accurate as possible. The overall heat loss coefficient (Uloss) in the model plays an important role in the performance prediction methodology of the ICS. This work presents a new and improved methodology to determine Uloss as a function of time in an ICS system using a systematic optimal control theoretic approach. This methodology is based on the derivation of a new nonlinear state space model of the system, and the formulation of a quadratic performance function whose minimization yields estimates of Uloss values that can be used in computer simulations to improve the performance prediction of the ICS system, depending on the desired time of the year and hot water draw profile. Simulation results show that predictions of the systemÂÂÂÂ's performance based on these estimates of Uloss are considerably more accurate than the predictions based on current existing methods for estimating Uloss.
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Date Issued
2010
Identifier
CFE0003266, ucf:48525
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003266