Study On Performance Of Thermal Power Direct Air-Cooled Cendenser System Under Influences Of Environmental Factors

Recently air-cooling technology has been actively developed in north China. Environmental factors and the thermal direct air-cooled power generating units are coupled complexly, in which the performances of the thermal direct air-cooled power generating units are inluenced by the environmental wind velocity, the enviromnental wind direction, the environmental temperature and the performances of the axial flow cooling fans. In addition, the air-cooled condenser (ACC) cells in the pherimery are influenced strongly by the cluster effect of the operation of the axial flow fan cluster and the exhaust hot air recirculation of the environmental natural wind simultaneously.The thermal performance experiments of the four thermal direct air-cooled units constructed together were carried out during spring, summmer, and autumn. The further thermal performance experiments of the fan cluster portion operation on the two thermal direct air-cooled units constructed together were carried out under the summer dominant wind. The comprehensive effects of the unit experimental variables itself, and the environmental conditions, and the performances of the experimental axial flow cooling fans on the unit performances were obtained quantitatively by the grey relational analysis models, and the models for the turbine back pressure prediction based on the above thermal performance experimental data were established respectively using the artifical neural network (ANN) algorithm and the least squares support vector machine (LS-SVM) algorithm. Secondly, the rules of the effect on the downstream and upstream units against the environmental wind could be obtained based on the turbine back pressure LS-SVM prediction models when the speeds of the different portion fans on the axial flow fan cluster were reduced or increased based on the reference conditions under the summer dominant wind. The heat load from the solar radiation calculation model on the ACC was built, and the related influencing analysis was obtained.Based on the analyzing results of the grey relational models on the experimental data of the thermal performances of the thermal direct air-cooled units, it is found that the unit experimental variables itself and the environmental conditions had different influences on the performances of the thermal direct air-cooled units, and the performances of axial flow cooling fans in different places of the axial flow fan cluster had different influences on the performances of the thermal direct air-cooled units as well, with the strongest effect of the fans in the periphery of the axial flow fan cluster.For the condenser in a135MW thermal direct air-cooled unit, the monthly averaged midday solar radiation over a period of21years was obtained, and its effects on the heat load and turbine back pressure were investigated based on the constant turbine outflow and monthly average day temperature of enviroment. The monthly average heat load from the solar radiation increases in a5-month period with371.75kW in May and then decreases, which is consistent with the sunshine time. For the azimuthal angle of0°, the turbine back pressure increases over a7-month period, with the maximum increment reaching for0.2097kPa in July, and then decreases over a5-month period, which is consistent with the environmental temperature, and the heat load from the solar radiation is the0.134%of the overall heat load of the thermal direct air-cooled condenser averagely.An ANN model based on a LM-BP algorithm was developed, which could be used for predicting the turbine back pressure of a thermal direct air-cooled unit. The prediction of the ANN model usually agreed well with the actual values of the turbine back pressure. Furthermore, when it was used for predicting the turbine back pressure, the model yielded agreeable result with mean relative errors(MRE) of9.273%and root mean square error (RMSE)1.83kPa and absolute fraction of variance (R2) of0.9859. Moreover, when the enviromental experimental variables with±5%random fluctuation, such as environmental natural wind velocity and direction, ACC wind velocity and direction on windwall, were input into the ANN prediction model, the related MRE was14.57%,12.21%,11.22%and11.16%, the related RMSE was2.77,2.13,1.84and1.89kPa, the related R2was0.9641,0.9779,0.9836and0.9824, which demonstrated the robustness and reliability of the model, and the relative errors of the data fluctuation were effectively restrained.The LS-SVM models for the turbine back pressure prediction of the two thermal direct air-cooled units constructed together were established respectively under the summer dominant wind, and the rules of the influences on the turbine back pressure variations of the downstream and upstream thermal direct air-cooled units were obtained when reducing and increasing the fan speed of different portion of the axial flow fan cluster portion:(1) The turbine back pressure variations are significantly different if the fans speed of different portions are changed.(2) If the air cooling fan speeds of one unit are changed, the turbine back pressure of the other unit would be affected either.(3) It does not always play a role to reduce the turbine back pressure of the unit when the speeds of the air cooling fans are increased appropriately, and it plays a role to reduce the turbine back pressure of the unit in the downstream of the environmental natural wind and not to increase the turbine back pressure of the unit in the upstream of the environmental natural wind if the fan speeds of the portions affected by exhaust hot air recirculation obviously are reduced appropriately.