Dian-ce Gao

A power limiting control strategy based on adaptive utility function for fast demand response of buildings in smart grids

Power imbalance in electrical grid operation has become a most critical issue that results in a series of problems to grids and end-users. The end-users at demand side can actually take full advantage of their power reduction potentials to alleviate the power imbalance of an electrical grid. Buildings, as the major energy end-users, could play an important role on power demand response in smart grids. This article presents a fast power demand limiting control strategy in response to the sudden pricing changes or urgent requests of grids within a very short time, i.e., minutes. The basic idea is to shut down some of active chillers during demand response events for immediate power demand reduction. The article focuses on the solutions to address the operation problems caused by the conventional control logics, particularly the disordered flow distribution in chilled water system. A water flow supervisor based on an adaptive utility function is developed for updating the chilled water flow set-point of every individual zone online. The objective is to maintain even indoor air temperature change among all zones during a demand response period. A case study is conducted in a simulation platform to test and validate the novel control strategy. Test results show that the proposed control strategy can achieve fast power reduction after receiving a demand response request. Simultaneously, the proposed control strategy can effectively solve the problem of disordered water distribution and achieve the similar changing profiles of the thermal comfort among different zones under the reduced cooling supply.

Experimental study of dynamic characteristics of liquid desiccant dehumidification processes

Liquid desiccant dehumidification is an effective method of removing moisture from the air for air conditioning in built environments. The dehumidifier is a critical component where coupled heat and mass transfer between the desiccant solution and the air occurs. Understanding the dynamic characteristics of the dehumidifier is essential to develop controllers and operation strategies for the liquid desiccant hybrid air-conditioning systems. This article presents an experimental study of the dynamic heat and mass transfer characteristics of a counter-flow packed-type liquid desiccant dehumidifier. Experiments were carried out to investigate the dynamic responses of the outlet air and desiccant solution to various changing inlet conditions. In addition, the influences of typical configuration and operation parameters on the dynamic dehumidification process were analyzed. The results indicate that the settling time of the dynamic process decreases with the air and solution flow rates while increases with the packing height. The experimental results also show that the outlet air humidity ratio stabilizes sooner than the outlet air temperature during the dynamic process. The time constants of the heat and mass transfer processes were obtained, which are valuable to controller design.

A model-based adaptive method for evaluating the energy impact of low delta-T syndrome in complex HVAC systems using support vector regression

Low delta-T syndrome refers to the situation where the measured differential temperature of the overall terminal air-handling units is much lower than the normal value expected. It widely exists in the existing heating, ventilating, and air-conditioning systems and results in increased energy consumption. This paper presents a model-based method to evaluate the energy impact on the chilled water pumps due to the low delta-T syndrome in a complex chilled water system. When the low delta-T syndrome occurs, the chilled water pumps would deviate from their normal working conditions with increased power consumption. Models are developed to predict the reference benchmarks of the chilled water pump power based on the current cooling load, control rules, and preset set-points. The energy impact on the chilled water pumps can be determined by comparing the measured current pump power with the predicted benchmark. Support vector regression method is introduced for predicting the chilled water flow rate of the overall terminal units. Adaptive concept is employed to enhance the prediction accuracy of the overall pressure drop of the hydraulic water network under various working conditions. The proposed method is tested and validated in a dynamic simulation platform built based on a real complex heating, ventilating, and air-conditioning system. Results show that the proposed method can accurately evaluate the impact of the low delta-T syndrome on energy consumption of the chilled water pumps. Practical application: Low delta-T syndrome widely exists in existing HVAC systems and results in increased energy consumption. This paper presents a model-based method for practical applications in assessing the energy impact on the chilled water pumps due to the low delta-T syndrome in a complex chilled water system. When the low delta-T syndrome occurs in a system, this method can be used to predict the reference benchmark of energy use of chilled water pumps based on the measured cooling load profiles, the control rules used, and the preset set-points. The energy impact can be determined by comparing the measured actual energy consumption with the predicted benchmark. The evaluation results could help the operators to conveniently monitor the energy performance of the chilled water distribution system as well as to judge whether or not taking measures to identify and correct the related faults that result in the low delta-T syndrome.