Condition-based monitoring of natural draught wet-cooling tower performance-related parameters

[摘要] ENGLISH ABSTRACT: The meteorological conditions at Eskom's Majuba Power Station are measured,evaluated and trended in this dissertation. The results are used to evaluate the currentnatural draught wet-cooling tower (NDWCT) design- and performance testspecifications and to compare these to the original design- and performance testspecifications. The evaluation reveals that the design parameters for the NDWCTs atMajuba Power Station, a cooling system that was originally designed optimally, couldhave been determined differently and arguably more accurately by using the wet-bulbtemperature (Tawb) as the main design variable instead of the dry-bulb temperature (Ta).A new technique to determine optimal NDWCT design and performance test conditionsis consequently proposed. In order to satisfy the atmospheric conditions required for asuccessful NDWCT performance test, it is also proposed that the tests be undertakenbetween 12:00 and 14:00 during Summer. It is found that the NDWCT inlet Tawb,measured at specific heights, does not compare well to the far-field Tawb measured at thesame heights when a Tawb accuracy of 0.1 K is required. It is proposed that a morerepresentative far-field Tawb measuring height of 10 m should be used in future NDWCTdesigns as the NDWCT design temperature reference height. The industry-standardreference height should, however, still be used during temperature profile calculations.A parametric study of the water-steam cycle and wet-cooling system at Majubaindicates that during full load conditions, the generated output (Pst) is primarilydependent on the condenser saturation pressure (pc). The latter is reliant on Tawb, thetemperature lapse rate (LRT) that is represented by the temperature profile exponent (bT),the main cooling water flow rate (mcw), atmospheric pressure (pa), and wind speed (VW).Using historical plant data relatively simple methods, enabling the quick and effectivedetermination of these relationships, are proposed. The plant-specific and atmosphericparameters required for these analyses are also tabulated.Two NDWCT effectiveness models, one mathematical (Kröger, 1998) and onestatistical artificial neural network (ANN) model are presented and evaluated. ANNs,which are not often used to evaluate NDWCT effectiveness, provide accurate NDWCTtemperature approach results within 0.5 K of measured values for varying dependentvariables. This motivates that an ANN, if set up and used correctly, can be an effectivecondition-monitoring tool and can be used to improve the accuracy of more empiricalNDWCT performance models. The one-dimensional mathematical effectiveness modelprovides accurate results under NDWCT design conditions.The dependency of Majuba's NDWCT to the rain zone mean drop diameter (dd) isevaluated by means of the one-dimensional mathematical model. A reduction in dd from0.0052 m to 0.0029 m can reduce the NDWCT re-cooled water temperature (Tcwo) sothat the rated pc is reduced by 0.15 kPa, which relates to a combined financial savingduring peak and off-peak periods of R1.576M in 2013 and R1.851M in 2016.Similar improvements can result in higher savings at other wet-cooled stations in theEskom fleet due to less optimally-designed wet-cooling systems. The proposedtechniques should be considered in future economic evaluations of wet-cooling systemimprovements at different power stations.

[发布机构] Stellenbosch University