Abstract
The daily performance of a CO_2 heat pump water heating system with a hot water storage tank is affected by the history of daily hot water demand and heat pump operating conditions. It is important to estimate the values of daily performance criteria accurately under daily changes in hot water demand and operating conditions for optimal operation. In previous papers, a neural network model has been proposed for this estimation, and it has turned out that the estimated values of daily performance criteria have high accuracy. In this paper, this model is applied to determination of operating conditions to attain the optimal system performance under certain hot water demand. The validity and effectiveness of this approach are ascertained by a numerical study using a simulated hot water demand.
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