Online differential pressure reset method with adaptive adjustment algorithm for variable chilled water flow control in central air-conditioning systems

Central air-conditioning systems predominantly operate under partial load conditions.The optimization of a differential pressure setpoint in the chilled water system of a central air-conditioning system leads to a more energy-efficient operation.Determining the differential pressure adjustment value based on the terminal user's real-time demand is one of the critical issues to be addressed during the optimal control process.Furthermore,the online application of the differential pressure setpoint optimization method needs to be considered,along with the stability of the system.This paper proposes a variable differential pressure reset method with an adaptive adjustment algorithm based on the Mamdani fuzzy model.The proposed method was compared with differential pressure reset methods with reference to the chilled water differential temperature,outdoor temperature,and linear model based on the adjustment algorithm.The energy-saving potential,temperature control effect,and avoidance of the most unfavorable thermodynamic loop effects of the four methods were investigated experimentally.The results indicated that,while satisfying the terminal user's energy supply demand and ensuring the avoidance of the most unfavorable thermodynamic loop,the proposed adaptive adjustment algorithm also decreased the differential pressure setpoint value by 25.1%—59.1%and achieved energy savings of 10.6%-45.0%.By monitoring the valve position and supply air temperature of each terminal user,the proposed method exhibited suitable online adaptability and could be flexibly applied to buildings with random load changes.

From laboratory to on-site operation:Reevaluation of empirically based electric water chiller models

Chiller model is a key factor to building energy simulation and chiller performance prediction.With spread of new types of electric water chillers that have higher performance and wider operating range,new challenges have been faced by building energy simulation tools and their chiller models.This work takes a new type of electric water chiller as a case study and reevaluates eight typical empirically based models for predicting the energy performance of electric water chiller to verify whether they are suitable for the new type of chiller,using both laboratory test data from chiller manufacturer and online monitoring data from on-site operation of a central cooling plant with chillers of the same type.The prediction ability of the chiller models(including model prediction accuracy and generation ability)in laboratory test and on-site operation situations are examined.The results show that the existing models can well describe the chiller performance in the laboratory test situation but perform poorly in the on-site operation situation.As the best two models in the laboratory dataset,the overall prediction errors of DOE-2 and GN model increase more than 250%and 75%respectively in the field dataset.The big discrepancy of model prediction accuracy in the two situations is mainly due to the differences of evaporator and condenser water flow rates between the laboratory and on-site operation datasets,which indicates the limitations of the empirical chiller models and implies further research in future in order to improve the suitability and reliability of chiller model.