Implementation of greywater heat recovery system in hospitals

Dudkiewicz, Edyta; Ludwińska, A.; Rajski, Krzysztof

doi:10.1051/e3sconf/201911600018

Cited by 6 publications

(2 citation statements)

References 9 publications

(18 reference statements)

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“…The energy efficiency of the heat recovery system, which is implemented according to Variant I, Variant II, and Variant III, can be determined using Equation (1). The energy recovery efficiency (ε) is calculated as the difference between the energy required to heat water for domestic purposes in a system without a heat exchanger and the energy demand in the DHW system [29,49].…”

Section: Heat Recovery Efficiency Analysismentioning

confidence: 99%

Analysis of the Life Cycle Cost of a Heat Recovery System from Greywater Using a Vertical “Tube-in-Tube” Heat Exchanger: Case Study of Poland

Piotrowska,

Słyś

2023

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Significant amounts of waste heat are deposited in greywater, which can be utilized, among other things, for heating domestic hot water in residential buildings. The manuscript presents an economic analysis of a greywater heat recovery system using a vertical heat exchanger of the “tube-in-tube” type in a single-family building. The analysis is based on the results of experimental research on the energy efficiency of three domestic hot water preparation systems equipped with a vertical heat exchange unit. The analyzed systems had different concepts for the flow of preheated water and cold water. The research showed that the implementation of a vertical “tube-in-tube” heat exchanger can reduce the energy consumption for domestic hot water preparation by approximately 45.7% to 60.8%, depending on the system variant. Furthermore, it was determined that the energy savings associated with reducing domestic hot water consumption can cover the investment costs related to the purchase and system of the heat exchanger within a period of 2 to 5 years of system operation, depending on the design variant and the unit price of electricity.

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Section: Heat Recovery Efficiency Analysismentioning

confidence: 99%

Analysis of the Life Cycle Cost of a Heat Recovery System from Greywater Using a Vertical “Tube-in-Tube” Heat Exchanger: Case Study of Poland

Piotrowska,

Słyś

2023

Resources

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“…Under the different conditions (i = 0%, q = 10 L/min), this was only 0.71 percentage points. Again, these are therefore not significant differences, especially as while the cold water temperature varies significantly over the year [42], the greywater temperature does not fluctuate as much [43].…”

Section: Characteristics Of the Greywater Heat Exchangermentioning

confidence: 92%

Evaluation of the Suitability of Using Artificial Neural Networks in Assessing the Effectiveness of Greywater Heat Exchangers

Starzec,

Kordana-Obuch,

Piotrowska

2024

Sustainability

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The use of greywater heat exchangers (GHEs) is an effective way to reduce energy consumption for heating domestic water. However, the available characteristics of this type of device are often insufficient and consider only a few selected parameters of water and greywater, which results in the need to look for tools enabling the determination of the effectiveness of GHEs in various operating conditions with incomplete input data. The aim of this paper was to determine the usefulness of artificial neural networks (ANNs). For this purpose, comprehensive experimental tests were carried out on the effectiveness of the horizontal heat exchanger, taking into account a wide range of water and greywater flow rates and temperatures of these media, as well as the linear bottom slope of the unit, which allowed for the creation of a database of 32,175 results. Then, the feasibility of implementing the full research plan was assessed using ANNs. The analysis showed that the impact of the media temperatures on the heat exchanger effectiveness values obtained using ANNs is limited, which makes it possible to significantly reduce the number of necessary experiments. Adopting only three temperature values of at least one medium allowed the generation of ANN models with coefficient values R2 = 0.748–0.999 and RMSE = 0.077–1.872. In the case of the tested GHE, the slope and the flow rate of the mixed water are of key importance. However, even in the case of parameters of significant importance, it is possible to reduce the research plan without compromising the final results. Assuming five different values for each of the four input parameters (a total of 625 combinations) made it possible to generate an ANN model (R2 = 0.993 and RMSE = 0.311) with high generalization ability on the full research plan covering 32,175 cases. Therefore, the conducted analysis confirmed the usefulness of ANNs in assessing the effectiveness of GHEs in various operating conditions. The approach described in this paper is important for both environmental and economic reasons, as it allows for reducing the consumption of water and energy, which are necessary to carry out such scientific research.

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