Search Results (3)

In standard district cooling (DC) plants, central chillers produce cold energy for space cooling throughout the district network. In recent times, the integration of the vapor compression system, which includes the functionalities of vapor compression chillers (VCC), and thermal energy storage (TES) tanks in the DC setup, has gained more implementation across the globe. This is due to the possibility of load shifting by using the VCC to produce chilled water for charging the TES tanks during off peak periods. Since the environmental implications of various energy intensive systems are largely determined by the amount of material and energy consumed throughout their life cycle, it is critical to conduct a sustainability assessment of these systems in terms of environmental contributions, and suggest design options to reduce these impacts. A cradle to grave life cycle assessment (LCA) model is created in response to these issues and in order to meet the project’s objectives. The life cycle impact assessment (LCIA) results of the analysis reveal that the carbon footprint per 1 RTh of the produced chilled water is estimated at 0.72 kg CO₂ eq/RTh. The operation phase of the system’s life cycle accounted for the most impact, about 98%, with other life cycle phases having negligible contributions. In substantiating the study’s investigation, the environmental performance based on several design options were discussed and compared to the case study. Among the several scenarios considered, incorporating the Sweden mix technology provided the case study with the most significant environmental savings, of about 94%. Full article

District cooling (DC) systems have recently proven to be more economically and environmentally viable as compared to conventional cooling techniques. In most DC setups, electric centrifugal chillers (ECCs) are installed to provide chilled water (CW) to charge the thermal energy storage (TES) tank or for direct CW supply to the DC network. The operation of these ECC systems consumes most of the electrical power supplied to the entire DC plant; this therefore strengthens the need to conduct a comprehensive environmental assessment in order to quantify the indirect ecological impact resulting from the energy consumed in the ECC system operation. In order to achieve this, a case study was conducted of four ECC systems with a use-life of 25 years installed in a large DC plant in Malaysia. A gate-to-gate life cycle assessment (LCA) methodology was adopted to analyze the environmental performance of the system setup. The result of the study year reveals that April and June account for the highest and lowest environmental impact, respectively. The influence of climatic temperature conditions on the monthly cooling and environmental load distribution was also observed from the results. Finally, in substantiating the study’s investigation, environmental performance based on the composition of two different electricity fuel mixes is discussed and compared. The results revealed a drastic decrease in environmental load as the ratio of non-renewable energy sources decreased in the composition of the mix, thereby reducing the contribution of the overall environmental impact of the ECC systems’ use phase. Full article

The Gordon-Ng models are tools that have been used to estimate and evaluate the performance of various types of chillers for several years. A 550 TR centrifugal chiller plant facility was available to collect data from July and September 2018. The authors propose rearranging variables of the traditional (GNU) model based on average electric consumption and through a thermodynamic analysis comparable to the original model. Furthermore, assumptions are validated. Then, by estimation of the parameters of the new model using least square fitting with field training data and comparing to the GNU model and Braun model (based on consumption), it was shown that the proposed model provides a better prediction in order to evaluate consumption of a centrifugal chiller in regular operation, by improving the coefficient of variation (CV), CV = 3.24% and R² = 92.52% for a filtered sub-data. Through an algorithm built from steady-state cycle analysis, physical parameters (S_gen, Q_leak,eq, R) were estimated to compare with the same parameters obtained by regression to check the influence of the interception term in the model. It was found that without an interception term, the estimated parameters achieve relative errors (ER) below 20%. Additional comparison between external and internal power prediction is shown, with CV = 3.57 % and mean relative error (MRE) of 2.7%, achieving better accuracy than GNU and Braun model. Full article