Mingzhe Liu

Texas A&M University | TAMU · Department of Mechanical Engineering

Deep learning models are increasingly being used to predict renewable energy-related variables, such as solar radiation and outdoor temperature. However, the black-box nature of these models results in a lack of interpretability in their predictions, and the design of deep network architectures significantly impacts the final prediction outcomes. T...

Temperature control exerts a significant influence on the performance of Fifth Generation District Heating and Cooling (5GDHC) systems. Ineffective temperature control could lead to not only occupant discomfort and higher operation costs due to increased energy consumption and reduced equipment lifespan, but also a negative environmental impact thr...

The prediction of renewable energy plays a critical role in optimizing the operation, fault diagnosis, and other essential tasks within its energy system. Given the scarcity of labeled data and the proliferation of newly established renewable energy systems, the concept of deep transfer learning can enhance the performance of deep learning predicti...

Deep learning models are increasingly applied in the field of solar radiation prediction. However, the substantial demand for labeled data limits their rapid application in newly established systems. Traditional transfer learning employs pre-training and fine-tuning methods to reduce the use of data in the target system. However, it still necessita...

Recent research has highlighted the effectiveness of advanced building controls in reducing the energy consumption of heating, ventilation, and air conditioning (HVAC) systems. Among advanced building control strategies, deep reinforcement learning control (DRL) shows the potential to achieve energy savings for HVAC systems and has emerged as a pro...

This study aims to explore the differences in the energy performance among ultra-low temperature district heating and cooling (ULTDHC) networks with different substation configurations. Three substation configurations, including free cooling (using heat exchangers only for substation cooling), active cooling (using chillers only for substation cool...

HEADING In the U.S., electricity accounted for 41% of household end-use energy consumption in 2019. The demand side management of residential buildings, including heating, ventilation, and air conditioning (HVAC), home appliances such as refrigerators, washers/dryers, and lights, and behind-the-meter (BTM) distributed energy resources (DERs) such a...

Buildings account for 70% of U.S. electricity consumption, of which the major electricity consumer is space heating and cooling. Therefore, grid-interactive efficient buildings (GEBs) have potential to provide the electricity grid with significant demand flexibility necessary for further adoption of the intermittent renewable electricity generation...

This paper presents the a set of multi-domain load models that allow simulating the dynamics of coalesced electrical power and the thermo-fluid system by exploiting the Modelica language based on the Modelica OpenIPSL power system library. This allows for phasor domain representation of the electrical grid, such as that used in de facto power syste...

The development of a distributed heat pump system that utilizes several renewable energy sources to meet building heating and cooling demands was reported in this paper. We refer to this system as the multiple‐source and multiple‐use heat pump (MMHP) system. A unique sky source heat pump, ground heat exchangers, and various heat pumps are connected...

The energy input for building operations is mainly composed of fossil fuel-based energy carriers, and therefore accounts for a large proportion of global greenhouse gas emissions. Thus, significant effort such as application of heat pumps has been focused on boosting renewable energies in building to decrease the energy demand and its related emiss...

The energy consumption of pumps for hot and chilled water circulation cannot be ignored because it can be 10-20 % of the consumption of heating, ventilating, and air conditioning (HVAC) systems. This value generally accounts for a significant proportion of the total building energy consumption. In most HVAC systems, water is usually delivered by se...

We herein report the development of a distributed heat pump system that can utilize a variety of renewable energy sources to meet different building heating and cooling demands (i.e., a multiple source and multiple use heat pump system, MMHP). In this system, a water circulating loop is used to connect ground heat exchangers, a unique sky-source he...

In energy distribution systems, thermal energy is usually transferred by a heat carrier fluid via pumps. Improper design and unreasonable control of pumping systems result in inefficient operation which accounts for a significant part of electricity consumption in the industry. The need to save energy has been sharpened the focus on improving energ...

We herein report the development of a distributed heat pump system that can utilize a variety of renewable energy sources to meet different building heating and cooling demands (i.e., a multiple source and multiple use heat pump system, MMHP). In this system, a water circulating loop is used to connect ground heat exchangers, a unique sky-source he...

In this study, an artificial neural network (ANN) was used to model the thermal performance of a novel direct-expansion solar-assisted sky-source heat pump (SSHP) during winter. The input parameters of the ANN take into account the weather conditions, water loop characteristics, and the compressor characteristics of the SSHP. The following four out...

This study investigates the heating operation performance of a multiple-source multiple-use heat pump system, consisting of a sky source heat pump, a ground heat exchanger and floor heating heat pump in an experimental facility named RE (Renewable Energy) House. The novelty of this system is that the ground thermal state is maintained by the combin...