Storage Air Conditioning System Research Articles

Optimization of Na2SO4•10H2O composites for cold storage by D-optimal mixture design

This study delved into the creation of a composite phase-change material (PCM), named SBNSC, for potential application in cold storage air-conditioning systems (8–16°C). The composite PCM was formulated using sodium sulfate decahydrate (Na2SO4·10H2O) as the primary PCM, borax as a nucleating agent, ammonium chloride (NH4Cl) as a temperature control additive, sodium hexametaphosphate as a crystal modifier and carboxymethylcellulose as a thickening agent. The D-optimal mixture design was employed to optimize the composition, and this resulted in the identification of an optimal formulation characterized by the most desirable properties. The thermal properties were evaluated using differential scanning calorimetry and revealed a phase-change temperature of 15.40°C. X-ray diffraction analysis confirmed the crystalline nature of the composite PCM. After 100 cooling and heating cycles, the crystallization temperature was 9.50°C, the melting temperature was 15.50°C and the supercooling degree was 0.70°C. The enthalpy values showed an 11.22% decrease, indicating reliable thermal performance. The study concluded that the optimal formulation (SBNSC) exhibits commendable thermophysical properties, demonstrating its potential for effective application in phase-change cold storage air-conditioning systems.

Research on Phase Change Cold Storage Materials and Innovative Applications in Air Conditioning Systems

Phase change cold storage materials are functional materials that rely on the latent heat of phase change to absorb and store cold energy. They have significant advantages in slight temperature differences, cold storage, and heat exchange. Based on the research status of phase change cold storage materials and their application in air conditioning systems in recent years, this paper provides an overview of the materials and their enhanced research progress. It summarizes the types of phase change cold storage air conditioning systems, optimization schemes, and system applications. This paper also identifies the current issues in phase change cold storage air conditioning and discusses the development trends in cold storage materials and air conditioning systems. It anticipates that future advancements will focus on composite phase change cold storage materials and low-energy consumption intelligent phase change cold storage air conditioning systems in steam compression using spherical capsules and concave–convex plate PCM.

Examination of Operational Methods for a Low-Temperature Aquifer Thermal Storage Air Conditioning System Based on Operational Performance and Considerations of Thermal Storage and Pumping Volume Balance

Aquifer Thermal Energy Storage (ATES) systems are garnering attention as high-efficiency air conditioning technologies that contribute to the realization of a carbon-neutral society. This study focuses on an ATES system constructed in Japan, characterized by its complex geological conditions and thin aquifer layers. Detailed actual performance data measured over four years are presented, and performance analysis results show that a COP of 5 was achieved for the overall building cooling and heating system. In addition, the study provides a detailed analysis of the imbalance in heat quantity, remaining heat storage, and other factors based on actual data, identifying operational issues and summarizing specific improvement measures. Finally, as a proposal for a sustainable operational method to balance the cumulative heat storage and pumping volume of cold and hot water, specific operational procedures are summarized, including setting the return water temperature for the next season based on the dimensionless average pumping temperature of the previous season, and a flowchart is presented. There is no prior research that shows such specific operational procedures, and this can be considered an important achievement of this study.

Case study of variable speed photovoltaic direct-driven ice-storage air conditioning system in Wuhu

In order to meet the contradiction between the growing demand for refrigeration and energy scarcity, this paper proposes a novel photovoltaic ice storage air conditioning system. The system is directly driven by a photovoltaic array. The performance of the system was studied through experiments, and a mathematical model was constructed for comparative verification. The experimental results show that the daytime cooling COP of the system is 1.18, the photovoltaic conversion efficiency is 6.29 %, and the nighttime cooling time is 9 h, which basically meets the cooling needs. Through simulation, the performance of the system was optimized, and the results showed that an increase in the initial water volume and temperature of the ice storage tank would increase the cooling COP; the spacing between evaporator pipes increased from 45 mm to 60 mm, resulting in a 7.11% increase in COP; the optimal spacing between evaporator fins is 9 mm, which improves performance by 9.11 %.

Design optimization method of heating and cooling full cycle storage air conditioning in integrated energy system

Heating and cooling storage air conditioning is an important part of the integrated energy system, which can play an important role in the flexible conversion of thermoelectric coupling systems. Because storage air conditioning involves the dynamic characteristics of power supply on the source side and cold and heat demand on the load side, system capacity allocation is a problem of technical and economic optimization. This paper breaks through the traditional design method based on the hourly load distribution law of typical design days and proposes a performance-oriented design method for the bidirectional full-cycle dimension storage air conditioning system based on the system’s annual operation performance, which can take into account the hourly dynamic load distribution law of every day in the full heating season and the full cooling season coupled with the bidirectional demand of cold and heat loads. A more scientific and reasonable capacity configuration scheme for the storage air conditioning system is obtained. The design is presented with a concrete case.

Reinforcement learning-based demand response strategy for thermal energy storage air-conditioning system considering room temperature and humidity setpoints

Heating, ventilation, and air-conditioning systems significantly influence demand response (DR) actions. In the literature, many studies have investigated the reduction of sensible loads through DR events by increasing temperature setpoints while satisfying indoor comfort levels. However, less consideration has been given to latent loads. Therefore, proximal policy optimization reinforcement learning (RL) algorithms are adopted to simultaneously control indoor temperature and humidity (T&H) setpoints to reduce sensible and latent loads. An EnergyPlus-Python joint simulation platform was created for the temperature-humidity independent control system. DR strategies based on RL, active thermal energy storage, and time-of-use electricity prices are formulated to find the optimal indoor T&H setpoints, considering environmental constraints, comfort levels, and energy consumption. The results showed that in the optimal experimental strategies implemented based on negative feedback regulation, savings of 29.15 % on electricity consumption were achieved during DR periods and 46.11 % savings on the daily operating costs. Moreover, a simulation strategy based on feed-forward regulation was developed and found to reduce electricity consumption by 6.92 % during DR periods. Compared with a fixed T&H setpoint, the developed strategy meets the preferences of different groups of people for thermal comfort and increases the system's flexibility.

Research on energy-saving conventional submarine air-conditioning system based on heat and humidity load calculation

The built-in air-conditioning and ventilation system of modern conventional submarines still adopts duct ventilation, which has high working noise, high energy consumption, poor dehumidification effect, and is mainly inter-cooled. For the air quality, hot and humid environment and comfort requirements in the submarine cabin. This project proposes an energy-saving cold storage air-conditioning system suitable for submarines. It adopts the air control method of temperature and humidity independent processing, and combines solution dehumidification and cold storage technology to independently control the temperature and humidity of the cabin, so as to achieve the purpose of efficient dehumidification and energy saving. The system makes full use of the limited space inside the submarine, reduces the energy consumption of refrigeration, improves the underwater endurance and concealment, and provides a healthy and comfortable air environment for the crew of the submarine, which has important strategic value.

A demand response method for an active thermal energy storage air-conditioning system using improved transactive control: On-site experiments

Transactive control (TC) and active thermal energy storage (ATES) strategies can effectively achieve a supply–demand balance across energy sources in the power grid. However, past research mainly focused on one of these demand response (DR) strategies, and integrated DR strategies that combine TC and ATES are unavailable. Therefore, to fully utilize both TC and ATES strategies in the DR of air-conditioning systems and thus enhance power grid stability, a comprehensive DR strategy that combines an improved version of TC with ATES (ITC + ATES) was developed for energy storage air-conditioning systems. The ITC + ATES strategy utilizes the automatic feedback regulation effect of the real-time electricity price on the grid side to the air-conditioning users. Then, the system bids the cooling or heating demand on the user side in the power market, thus adjusting the dynamic temperature set-point in real time. The ATES system's automatic energy storage and release process is then regulated accordingly. Thus, this strategy not only allows the air-conditioning system to participate in the power DR, but ensures that the electricity consumption of the air-conditioning system conforms to the power market law and realizes the optimal social value of the power commodity. On-site test experiments of space cooling and heating conditions were conducted on a full-scale intelligent centralized air-conditioning experimental platform with an ATES system to test the effect of this strategy. Comparing the ITC + ATES strategy with the conventional control strategy, ATES strategy, and ITC strategy reveals that the ITC + ATES strategy is most effective in ensuring the thermal comfort of occupants, particularly during the DR period. Moreover, the maximum total electricity consumption reduction rate, the maximum total operating cost reduction rate, the maximum electricity consumption reduction rate during the DR period, and the maximum total operating cost reduction rate during the DR period of the ITC + ATES strategy were 33.20%, 49.69%, 76.14%, and 76.16%, respectively. These results suggest that the ITC + ATES strategy is an efficient and integrated DR approach.

Study on the Dynamic Generation of Subcooled Water Using a Compact Heat Exchanger

The dynamic generation of ice slurry from subcooled water is one of the most promising ways to make ice; this process is utilized widely in ice storage air-conditioning systems. However, the random occurrence of ice blockage during the generation of subcooled water using conventional heat exchangers prevents the increase in subcooling, thereby reducing the efficiency of the release of the subcooled water and converting it into ice slurry. A more efficient approach to reducing the fluid passage time is to employ a compact heat exchanger with a highly efficient heat transfer performance, a heat transfer length of only 21.5 mm, and a hydraulic diameter of 0.32 mm. A compact heat exchanger was used to build a dynamic generation setup for subcooled water, and 40 wt% of non-freezing liquid and tap water was used as the working fluid for heat exchange to generate subcooled water. The results show that the compact heat exchanger can achieve a greater subcooling degree (3.8 K) and longer duration (108 min). This study further explored the potential for dynamic ice making from deep, subcooled water and improved the overall structure of the compact heat exchanger used. The experimental setup is recommended based on the analysis of the results.

Flow Characteristics and Heat-Transfer Enhancement of Air Agitation in Ice Storage Air Conditioning Systems

A large number of bubbles generated by the air agitation device in an external melting ice storage system can cause the disturbance of the ice–water mixture, which can enhance the heat transfer and contribute to the reduction in energy consumption. The structural design and optimization of the air agitation device in an external melting ice storage system is the key issue for energy savings. In this study, the influence of different orifice spacings and diameters on the distribution of the gas–liquid flow field, gas holdup, heat-transfer coefficient, and power consumption in the ice storage tank was investigated by numerical simulation. The simulated results showed that the heat-transfer coefficient of the ice–water mixture with air bubbles should be 3–5 times higher than the natural convection when the air superficial velocity is 0.03 m/s. The gas holdup was mainly affected by the orifice spacing, and the maximum varied from 5.0% to 8.2%. When the orifice spacing was less than 150 mm, the gas holdup changed a little in the horizontal direction, and the uniformity became worse when the orifice spacing was larger than 180 mm. An orifice diameter larger than 3 mm can improve the heat transfer and cause less air-compressing energy consumption, which decreased by approximately 1.62%.

Experimental study of R290 replacement R134a in cold storage air conditioning system

R290 refrigerant offers good environmental protection and thermodynamic characteristics. The feasibility of R290 replacing R134a was summarized through theoretical analysis and experimental tests in this paper. A coiled ice storage experimental test platform was built, and the performance of R290 and R134a cool storage air conditioning systems was analyzed. The experimental analysis confirmed that the R290 system has a higher volumetric refrigerating capacity, and the system COP (coefficient of performance) is comparable to the R134a system. At the same evaporation temperature, the pressure ratio and exhaust temperature of the R290 system are lower than those of the R134a system. In addition, the charge amount of the refrigerant can have an impact on cold storage performance. It was found that the optimal charge range of R134a is 1300–1400 g, and that of R290 ranges from 500 to 600 g. The optimal charge amount for R290 is only 43–46% of R134a. A lower charge amount is beneficial to reduce the explosion risk of the R290 cool storage air conditioner. Under the optimal charge, the R290 system has a fast cooling rate and shorter cooling storage time, and the average specific refrigerating effect is increased by approximately 52% compared with R134a.

Experimental study on the preparation and cool storage performance of a phase change micro-capsule cold storage material

In this paper, a cold storage air conditioning system based on a phase change micro-capsule material was constructed. The appropriate micro-encapsulated phase change materials were selected according to the temperature of the generator and evaporator. In addition, phase change materials were encapsulated and mixed with water with good thermal conductivity to form phase change micro-capsule suspensions, which takes into account the latent heat, fluidity and thermal conductivity of the phase change. Three kinds of micro-capsule phase change material suspensions with good stability and mass fractions of 5%, 10% and 15% were prepared. The main thermophysical parameters of the suspensions were obtained by analysis. In addition, the cold storage characteristics of the phase change micro-capsule suspensions in the cold storage tank of the composite system were experimentally studied. The results showed that the best composition ratio of base liquid was 99.1% deionized water, 0.2% SDS, 0.2% xanthan gum, and 0.5% NaCl. At the same cold storage time, compared with the evaporation temperature of −5 °C, when the evaporation temperature was −10 °C, the cooling capacity of the system decreased significantly. The cold storage capacity of phase change cold storage was approximately 1.5 times higher than that of ice cold storage, and the overall performance of phase change cold storage was better than that of ice cold storage. The developed phase change micro-capsule suspension has been considered to have some effect on phase change cold storage.

Reinforcement learning of room temperature set-point of thermal storage air-conditioning system with demand response

Demand response (DR) is an effective means to reduce peak loads and enhance grid stability. Heating, ventilation, and air-conditioning (HVAC) systems have potential energy transfer characteristics and can be used as a typical flexible load for building DR. The HVAC thermostat settings are the key parameters that directly affect the elasticity of building DR and reflect the willingness of users to participate in DR. For air-conditioning DR control, the conventional method to determine thermostat settings is model-dependent, while reinforcement learning (RL) is a model-free, adaptive continuous control algorithm. Taking the proximal policy optimization RL algorithms, a neural network is used to construct a strategic framework to obtain discrete control actions, that is, thermostat settings, and a new objective function truncation method is adopted to limit the update step size and enhance the robustness of the algorithm. Thus, a TRNSYS and MATLAB joint simulation platform for the thermal storage air-conditioning system was built. This study formulated a DR strategy based on time-of-use electricity prices, which considers factors, such as environment, thermal comfort, and energy consumption; and the proposed RL algorithm is used to learn the thermostat settings in DR time. The results show that the proposed RL algorithm could realize the temperature set-point control, which saved 9.17% of the operating cost compared with a non-thermal storage air-conditioning system with a constant set-point.

Analysis and Research on Ice Storage and Water Storage Air Conditioning System of an Electric Power Building

The air conditioning system of ice storage and water storage has been applied in many practical projects. This paper introduces the air conditioning system form of Fuyang Electric Power Dispatching Building. The design condition of cold and heat sources and its transmission and distribution system is also introduced. In addition, this paper also collects and analyses the data of the chillers in actual operation. The results show that the system runs steadily and accords with the design conditions.

Predictive model of cooling load for ice storage air-conditioning system by using GBDT

Cooling load prediction can provide reliable data support for the development of low energy consumption building. It is difficult for traditional models to achieve stable prediction accuracy under different load mode when the amount of data is limited. To resolve this problem, gradient boosting decision tree (GBDT) model based on selection of input variables was proposed to predict the cooling load of commercial buildings. First, the input variables that affect prediction cooling load were determined through correlation analysis on the original data set. Then, the Pearson analysis was done on the original data to get the optimal combination of input variables. Next, the ensemble learning technology was used to build GBDT model. In order to improve the prediction accuracy of the model, the grid search method was applied to determine the hyperparameter combination of GBDT. Experimental results showed that in the high-load mode, the mean absolute error (MAE) of the GBDT model was reduced by about 24% compared with the SVM, and was reduced by about 37% compared with the DNN model. Under the general load mode, MAE was reduced by about 30% and 53% respectively. Compared with the other models, the prediction accuracy of GBDT model has been significantly improved under different load mode. The proposed cooling load prediction model can provide reliable data support for the predictive control of buildings.

Experimental and numerical investigation on a novel photovoltaic direct-driven ice storage air-conditioning system

In this paper, a photovoltaic direct-driven ice storage air-conditioning (PDISAC) system is proposed and performance of the system is experimentally and theoretically investigated. The proposed system is a battery or inverter less photovoltaic direct-driven system where the DC compressor is directly connected to the PV array. Through the test, it has been found that the proposed system was able to lower the test room temperature below 298.15 K, while the reference room temperature was 306.15 K. Moreover, the experimental refrigeration efficiency and solar-energy utilization efficiency were reported 1.028 and 7.1% respectively. Then, a mathematical model for the progress of ice making and cold storage is presented and verified by the experimental results. Besides, the factors such as the ambient temperature, the initial water temperature and volume in the ice storage tank, and the thickness of the ice layer surrounding the coil have been studied. The simulation results indicate that the initial heat transfer rate at the condensation side drops by 10.8% and refrigeration efficiency drops by 32.7% with the ambient temperature increasing from 298.15 K to 308.15 K. The increment of initial water temperature and initial water volume will lead to an increase in refrigerating capacity and refrigeration efficiency.

Receding‐horizon based optimal dispatch of virtual power plant considering stochastic dynamic of photovoltaic generation

AbstractThe merits of a virtual power plant in integrating photovoltaic generation and flexible loads, such as a chilled water thermal storage air conditioning system and an electric vehicle, are well recognized. However, the optimal operation of a virtual power plant is challenged by the complexities of solar irradiance and the large size of a chilled water thermal storage air conditioning system and an electric vehicle. This paper proposes a new approach to the optimal dispatch problem of a virtual power plant. The stochastic dynamic of solar irradiance is modelled by a stochastic differential equation set. The binary decision for a chilled water thermal storage air conditioning system and an electric vehicle are characterized by a mixed logical dynamical model. The resulting optimal dispatch problem is solved by the receding horizon approach. The appeal of the proposed approach is in its capability to consider the stochastically dynamical impact of solar irradiance. Besides, the proposed approach can solve the optimization problem over a relatively small period of time, and thus has the potential for online applications. Finally, the feasibility and effectiveness of the proposed approach is demonstrated by numerical simulations.

A demand-side integrated flexible load regulation optimization strategy for clean energy consumption

In order to absorb large-scale clean energy for power grid, the use of energy storage technology is paid more and more attention. However, most of the current researches are focused on a single kind of energy storage forms, and few are involved in the joint use of multiple energy storage devices. This paper aims at the insufficient application of a single energy storage device and the conflict between multiple energy storage technologies. A demand-side integrated flexible load regulation optimization method is proposed. For the heat storage electric boiler system and the ice storage air conditioning system, the combined algorithm is used to optimize their operation. It is clear that the combined algorithm based on genetic algorithm combined with cold, hot and electrical system has a more significant effect of absorbing clean energy than the single energy storage system. And, the example result proves the correctness and feasibility of the proposed comprehensive demand side response strategy.

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

Analysis on the Operation of Ice Storage Air Conditioning System in Practical Engineering

Cold storage technology is one of the effective means to alleviate the imbalance of power load during peak and valley period. Based on a practical project, the operation of the ice storage air conditioning system was monitored for 26 days. Temperature, pressure, ice storage and other parameters were recorded. Through the analysis of the operation data and air temperature, it is found that the operation of the ice storage system is stable and consistent with the design condition. But there are still some shortcomings in the operating strategy. This paper provides some suggestions for the design and operation of air conditioning system in future projects.