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In this paper, a heat recovery ground source heat pump (HR-GSHP) system, in which the primary pipes of the GSHP for air conditioning and the GSHP for hot water are connected to ground heat exchangers (GHEs) and each GSHP is operated simultaneously or within a short period of time, was installed in a dormitory building on a trial basis. Then, the optimal operation method to minimize the energy consumption of the system was investigated. The operating period of the GSHP for HW was changed and simulations were conducted to determine the operating period with the lowest energy consumption, which was 8 months from April to November. Furthermore, the HR-GSHP system was operated for 8 years from 2012 to 2019, and actual measurements were carried out to verify the system performance and the energy saving effect in optimal operation. In actual operation, it was confirmed that the minimum temperature was about 10 °C or higher even when the GSHP for HW was operated year-round. Therefore, the GSHP for HW was operated year-round after the third year of operation. It was confirmed that the operation of the GSHP for HW in summer, especially in August and September when the cooling load is large, can improve the system's efficiency by the effect of recovering cooling exhaust heat. In the eighth year of operation, when the GSHP for HW was operated most during the summer season, the system was able to reduce power consumption for air conditioning and hot water supply by approximately 17%. [ABSTRACT FROM AUTHOR]

Shallow geothermal heat has the characteristics of wide distribution and huge reserves. However, for northern rural buildings, the heating load in winter is much greater than the cooling load in summer, and thermal imbalance of the soil is prone to occur. This paper takes rural residences in southern Hebei as an example and designs a solar-assisted shallow geothermal energy system. Compared with the original shallow ground-source heat pump system, the indoor and outdoor temperature differences of the target building were first analyzed. Second, the changes in the soil temperature field and the differences in the supply and return water temperature were monitored. Finally, the initial investment and operating costs of the assisted system are analyzed. The results show that the average ground temperature field increases significantly in winter. Through the alternate operation of solar energy and ground-source heat pumps, heat extraction from the ground is reduced, and the imbalance cycle of heat extraction in winter and heat removal in summer is shortened. It alleviates the imbalance of the cold and heat loads for soil throughout the year. The inlet and outlet water temperature and heat exchange efficiency of the buried pipes have been significantly improved. The energy efficiency ratio of the system using the assisted system has increased from 3.40 in 2020 to 4.17, an increase of 0.77. The optimal ratio of the solar- assisted shallow geothermal energy system is a 12.80 m2 solar heat-collection area and one buried hole. The winter heating operating cost of the solar-assisted shallow geothermal energy system is 18.86 CNY/m2. It can save 37% of the annual operating costs of heating, cooling, and hot water compared to a single ground-source heat pump system and 40%–45% compared to traditional heating and cooling modes. [ABSTRACT FROM AUTHOR]

Among the most significant solutions suggested for estimating energy consumption and cooling load, one can refer to enhancing energy efficiency in non-residential and residential buildings. A structure's characteristics must be considered when estimating how much heating and cooling is required. To design and develop energy-efficient buildings, it can be helpful to research the characteristics of connected structures, such as the kinds of cooling and heating systems needed to ensure sui interior air quality. As an important part of energy consumption and demand of buildings, the assessment of cooling load conditions from the envelope of large buildings has not been comprehensively understood yet. In the present paper, a new conceptual system has been developed to anticipate cooling load in the sector of residential buildings. Also, the paper briefly describes the major models of the developed system to maintain continuity and concentrate on the prediction model of the cooling load. To predict cooling load, authors have modelled two methods of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in conjunction with teaching-learning-based optimization (TLBO). This article aims to illustrate how artificial intelligence (AI) approaches play an essential role in addressing the mentioned necessity and help estimate the optimal design parameters for various stations. The value of the multiple determination coefficient is also determined. The values of the training R² (coefficient of multiple determination) are 0.96446 and 0.97585 for TLBO-MLP and TLBO-ANFIS in the training stage and 0.95855 and 0.9721 in the testing stage, respectively, with an unknown dataset which is acceptable. The training RMSE values for TLBO-MLP and TLBO-ANFIS are 0.0685 and 0.11176 for training and 0.07074 and 0.12035 for testing, respectively, for the unknown dataset, which is acceptable. The lowest RMSE value and the higher R² value indicate the favourable accuracy of the TLBO-MLP technique. According to the high value of R² (97%) and the low value of RMSE, TLBO-MLP can predict residential buildings' cooling load. [ABSTRACT FROM AUTHOR]

Precooling gaseous hydrogen fuel to a cold temperature before refueling a heavy-duty (HD) hydrogen fuel cell electric vehicle (HFCEV) is essential to avoid overheating the vehicle tank, as well as achieving a high state of charge (SOC). Because a large volume of hydrogen is dispensed during each fill, the need for a shorter fill time amplifies the need to precool each load for refueling a HFCEV. Thus, the design and operation of a precooling unit (PCU), as well as the associated capital and operating costs, plays a pivotal role in any plans for heavy-duty hydrogen refueling stations. In this paper, we present a thermodynamic and technoeconomic analysis of a PCU in a gaseous hydrogen refueling station (HRS) for HD HFCEVs. By employing Argonne National Laboratory's hydrogen station cost optimization and performance evaluation (H2SCOPE) model, the refueling of 50 kg of hydrogen on-board type IV tank at ambient temperatures of 15–45 °C and varying fill rates is simulated. The required degree of precooling temperature to obtain either 100% or the maximum possible SOC is obtained from the simulation. Additionally, the simulation results demonstrate that the average flow rate of hydrogen is approximately 40% lower than the maximum flow rate during a typical fill; which motivates further evaluation of the instantaneous hydrogen mass flow rate profile and suggests the scope of improving precooling unit design. Accordingly, a hybrid strategy of precooling hydrogen has been proposed to address the cooling load by sizing the refrigeration unit for the average flow rate of hydrogen, while supplementing the above average peak hydrogen flow cooling load through thermal buffering. The combined technique enables the downsizing of the original PCU capacity by 25–40% and demonstrates a potential cost reduction of the PCU by approximately 30%, which translates to an installed cost reduction of ∼$125,000 per dispenser. • Hydrogen fill rate during refueling has a strong influence on the precooling load. • Bell-shaped profile of the fill rate advises a scope of improving precooling. • Hybrid strategy of on-demand cooling aided with partial thermal buffer is proposed. • The hybrid precooling approach downsizes the refrigerator capacity by 25–40%. • A potential reduction in the capital cost of precooling unit is 30%. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor scheduling flexibility and insufficient carbon emission reduction capacity of the current integrated energy system, this paper proposes an optimization scheduling model of integrated energy demand response that combines source-load synergy with reward and punishment stepped carbon trading mechanism. Firstly, the integrated energy system operation architecture including electricity-heat-cooling energy was constructed to harmonize the energy generation side and consumption side and effectively improve the multi-energy complementary capability of the system. Secondly, the reward and punishment stepped carbon trading mechanism is established by combining the initial carbon quota allocation method and the actual carbon emission calculation theory, so that environmental friendliness and economic sustainability are effectively improved. Finally, to minimize the system operating cost, an integrated demand response optimal dispatch model that considers the characteristics of electric, thermal and cooling loads is constructed to determine the optimal dispatch scheme for the integrated energy system. The results of the calculation example indicate that the proposed integrated demand response model has the function of peak reduction and valley correction, energy conservation and carbon reduction, and provides a feasible solution for the integrated energy system optimal scheduling. [ABSTRACT FROM AUTHOR]

Generally, the central air conditioners are centralized in a refrigeration room in public buildings. The proportion of energy consumption of the refrigeration room is about 40% of entire building. This paper aims to propose an energy plus and self-designed simulator to reduce the energy consumption of a large electronic factory in Zhuhai City, Guangdong province, China. In this paper, the real data collected from the electronic factory in February and the group control method used in the refrigeration room based on the kernel ridge regression algorithm. The correctness of the kernel ridge regression algorithm was verified with the experimental results. Compared to traditional PID control method, the kernel ridge regression algorithm could dynamically adjust those parameters, such as temperature and frequency to match the high efficiency zone of each device. The overall average COP of the system is increased from 4.17 to 7.04. The electricity of the refrigeration room could save 64 MWh with the cooling load forecast error being below 7% in February. The power consumption is expected to reduce by 8.2% and 562.3 MWh in 2022. [ABSTRACT FROM AUTHOR]

Many researchers are devoted to improving the prediction accuracy of daily load profiles, so as to optimize day-ahead operation strategies to achieve the most efficient operation of district heating and cooling (DHC) systems; however, studies on load prediction and operation strategy optimization are generally isolated, which leaves the following question: what day-head load prediction performance should be paid attention to in the operation optimization of DHC systems? In order to explain this issue, and taking an actual DHC system as a case study, this paper proposes an evaluation method for the prediction of daily cooling load profiles by considering the impact of inaccurate prediction on the operation of a DHC system. The evaluation results show the following: (1) When prediction models for daily load profiles are developed, the prediction accuracy of the daily mean load should be emphasized, and there is no need to painstakingly increase the accuracy of load profile shapes. (2) CV and RMSE are the most suitable deviation measures (compared to others, e.g., MAPE, MAE, etc.) for the evaluation of load prediction models. A prediction model with 27.8% deviation (CV) only causes a 3.74% deviation in operation costs; thus, the prediction performance is enough to meet the engineering requirements for the DHC system in this paper. [ABSTRACT FROM AUTHOR]

This paper studies the combined heating and cooling thermal performance of a CO2 heat pump system considering the subcooling effect. For such a system without cold thermal energy storage (CTES), the gas cooler outlet temperature normally needs to be controlled to match the cooling load required. However, the integration of CTES would enable the system to be operated under its optimal conditions depending on the ambient temperatures, i.e. a considerable amount of cooling capacity can be generated and stored for later use. A configuration of a CO2 heat pump integrated with CTES is described in this paper. A thermodynamic cycle and a simulation model considering the subcooling effect have been developed. The mathematical model for the pinch point analysis has been newly validated against published experimental data with acceptable agreements. In the case study, the impacts of the subcooling temperature on the optimal combined performance under four ambient temperatures (5 °C, 15 °C, 25 °C, and 32 °C) have been studied. The highest optimal combined COP of 5.38 can be achieved when the ambient temperature is 5 °C. The detailed profiles of CO2 temperatures, heating and cooling loads, and the COPs when the CTES is in operation have been revealed for the first time. It is found when the ambient temperature is higher than the water inlet temperature (plus the pinch point temperature), the optimal cooling COPs can even have a surge without the subcooling effect, due to a lower sCO2 temperature leaving the heat exchanger compared to the ambient temperature. Additionally, performance analysis for the CO2 heat pump system with or without CTES is compared, and it is concluded that all optimal heating, cooling, and combined COPs integrated with CTES surpass those without CTES. [ABSTRACT FROM AUTHOR]

This paper presents a detailed study of the energy savings that can be achieved through residential appliances by implementing conservation voltage reduction (CVR). The computed energy savings are derived from the ZIP coefficients of a load model (static) under varying voltage conditions that represent the power consumed by each appliance tested. Multiple studies have shown energy savings at the substation level but not at the level of a specific residence and appliance; hence, the latter is the focus of this analysis. The appliances are determined based on the type of heating and cooling loads, and the daily duration of use for each appliance, which contributes to the total monthly consumption that is billed for a household are included in this study. Energy savings in Malaysia has been a focus of many current studies, and this study is the first attempt to achieve energy savings through the implementation of CVR. No published work has compared individual appliances that truly benefits from CVR, and this is addressed in this study. The main contribution of this study is that it provides very detailed and measured data that are used to analyze and generate energy savings for very specific residential appliances intended to meet every 1% voltage drop. The load model is developed for the common household appliances in Malaysia, and then a voltage reduction study is applied to the appliances as well as the Malaysian distribution networks. Here, we also provide insight for performing voltage reduction at an electric vehicle (EV) charging station in Malaysia. The results of this study should serve as a foundation for all practicing utilities engineers to address the issue of CVR in Malaysia. The CVR factors for residential, commercial, and industrial networks in Malaysia are also published in this paper. [ABSTRACT FROM AUTHOR]

This paper investigated the effect of individual differences and the type of heating system on the perceived thermal comfort condition, neutral temperature, and thermal sensitivity in cold outdoor air conditions. Three types of individual factors, such as gender, temperament, and thermal past experience, were studied and compared in this paper. According to the results, temperament and thermal past experience directly influenced the occupants' thermal preference and indirectly influenced the thermal sensation by affecting their clothing level. However, the effect size of such variations was negligible. The type of heating system had the most significant impact on the neutral temperature, with a mean difference of 2.8°C. Individual factors did not have a direct impact on the neutral temperature. However, thermal sensitivity was influenced by an individual's temperament. Occupants with a cold temperament were more sensitive to the variation in the running mean outdoor temperature (Trm) than those with a warm temperament. When the results were compared with the predictions by the adaptive thermal heat balance (ATHB) and the predicted mean vote (PMV) models, it indicated that if the control condition over the heating system became limited, there would be no (i.e., very low) behavioral, physiological, and psychological adaptation. However, by creating an opportunity to control the heating system, thermal adaptation could be reached at a lower temperature under cold outdoor air conditions. Comfort is subjective and influenced by environmental factors and personal differences. For example, individuals might feel different and hotter or cooler at the same ambient temperatures. In addition, individuals could adapt to the environment and afford their comfort with lower costs than the heat predicted mean vote (PMV) and the cooling load calculation showed. The results of this paper could help to understand why people have different thermal perceptions under the same environment and might lead to the identification of the important nonenvironmental factors that impact the perceived feeling of health, well-being, and educational performance. Therefore, influencing decision-making during the design and maintenance of educational buildings. The results indicated that individual differences influenced the level of clothing and occupant preference. These differences influenced the variation in occupants' thermal sensitivity to indoor and outdoor air temperatures. However, they had a negligible influence on the neutral temperature. The heating systems had the most impact on the neutral temperature. The opportunity to control heating systems could lead to the thermal comfort condition being achieved at a lower temperature in cold outdoor air temperatures, which could reduce energy consumption. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of using a phase change material (PCM)-based latent heat storage (LHS) integrated with an air-conditioning system. The study has filled the knowledge gap regarding the dependence of melting rate and operational time of the AC system on PCM volume. Additionally, the study has examined the influences of important parameters such as inlet velocity and Stefan number on melting rates, outlet temperature, and COP. The results have revealed that higher inlet air velocity and Stefan number have led to shorter melting duration. Specifically, an increase in velocity from 1.6 to 2.14 m/sec has reduced the time required for complete melting by 19.16% at a fixed Ste value and D value of 2. Further increasing the velocity to 2.67 m/sec has reduced the time by 31.59%. However, increasing the volume of the PCM has resulted in a longer melting duration, with the total melting time increasing from 3.35 to 7.11 h. Better COP values have been obtained for low-velocity cases. For all cases examined, the COP of the AC system with PCM has been superior to the COP without the PCM at any given time. Increasing inlet velocity and Ste raised the outlet temperature of the HEX, while PCM volume had little impact. The results have also indicated that lower inlet velocity is suitable for longer working periods and lower AC cooling loads, whereas higher inlet velocity is appropriate for shorter working periods and higher AC cooling loads. [ABSTRACT FROM AUTHOR]

A major portion of the worldwide emissions arise from mobile air-conditioning systems with hydrofluorocarbon refrigerant as working substance and which is one of major cause for the greenhouse effect. R134a refrigerant having GWP of 1400 has been extensively used in car air conditioning. To reduce greenhouse gas emissions, the current R134a refrigerant must be phase out as per Kigali Amendment. The present study deals with cooling load calculation of car model by heat balance method as per ASHRAE standard using local climate condition. Further, thermodynamic analysis of R1234yf as an alternate refrigerant to R134a has been carried out for automobile air conditioning system. The required properties of refrigerants are extracted from Engineering Equation Software. The thermodynamic analysis is carried out to study the effect of operating parameters viz. condensing temperature, evaporating temperature, degree of superheating and degree of subcooling on COP, EDR, exergy efficiency and entropy generation. The previous literature reports mainly focus on separate study of either cooling load calculation or energy analysis or exergy analysis of R1234yf and R134a for automobile air conditioning system, while this paper presents the comprehensive study of new low GWP R1234yf as an alternate refrigerant to R134a in automobile air conditioning system with cooling load calculation including the concept of energy, entropy and exergy analysis. The percentage difference in COP between R134a and R1234yf system varies from 2.44 % to 4.78 % while percentage difference in EDR varies from 6.79 % to 2.87 % when evaporating temperature varied from -10 °C to 10 °C. With 12 °C of superheating at compressor inlet, the COP of R134a is 3.9 whereas COP of R1234yf is 3.75, which makes 3.85 % lower than that of R134a. The R1234yf has 4.78 % lower value of exergy efficiency as compared to that of R134a at evaporating temperature of -10 °C and it is found that maximum exergy destruction takes place in compressor. [ABSTRACT FROM AUTHOR]

A finite-time thermodynamic (FTT) model of three-heat-reservoir thermal Brownian refrigerator is established in this paper. This model can be equivalent to the coupling of a thermal Brownian engine and a thermal Brownian refrigerator with heat transfer effects. Expressions for cooling load and coefficient of performance (COP) are derived by combining FTT and non-equilibrium thermodynamics (NET). The system performance is studied and compared with those of previous models. For fixed internal parameters, the thermal conductance distributions among three heat exchangers are optimized for maximal cooling load. For fixed inventory allocations, the internal parameters are also optimized for maximal cooling load. Finally, the double-maximum cooling load is obtained by optimizing internal parameters and external thermal conductance distributions simultaneously, and the optimal operating temperatures are also derived. Results show that half of total thermal conductance should be placed in condenser to reject heat to ambient under maximal cooling load regime. The heat transfer determines system performance by controlling the working temperatures and the coupling of two external loads. The system works in reversible state when COP reaches its maximum value. The new performance limits can predict that of three-heat-reservoir thermal Brownian refrigerator more accurately, and also include those of NET model. [ABSTRACT FROM AUTHOR]

The climate data used for dynamic energy simulation of buildings located in urban regions are usually collected in meteorological stations situated in rural areas, which do not accurately represent the urban microclimate (e.g., urban heat island effect), and this might affect the simulation accuracy. This paper aims at quantitatively evaluating the effects of heat island on a high-rise building's energy performance based on the microclimate simulation tool ENVI-met and the building energy simulation tool COMFIE. However, the computation of microclimate models is time consuming; it is not possible to simulate every day of a year in a reasonable time. This paper proposes a method that generates hourly "site-specific climate data" to avoid long microclimate simulation times. A coupling method of ENVI-met and COMFIE was developed for more precise building energy simulation, accounting for the heat island effect. It was applied to a high-rise building in Wuhan, China. The results showed that the yearly average urban heat island effect intensity at the height of 3 m was estimated to be 0.55 °C and decreased with height. Compared to the simulation considering the outdoor temperature variation with the height and orientation, using the original climate data collected in rural areas led to an overestimation of the heating load by around 5.8% and an underestimation of the cooling load by around 8.7%. Compared to the weather file at the height of 3 m near the north facade neglecting the temperature variation along the height, the heating load was overestimated by 8.2% and the cooling load was underestimated by 10.8%. The methods proposed in this paper can be used for the more precise application of urban building energy simulation. [ABSTRACT FROM AUTHOR]

This paper evaluated the cement-based materials incorporated with novel solid–gel phase change materials (PCMs) for improving the energy efficiency of building envelopes. This novel PCM is form-stable, which will not leak as solid–liquid PCMs do and not need encapsulation, and it features high energy-storage capacity. Experimental results showed that the thermal properties of cement-based materials were improved as the increase of PCM content. A 30% replacement of sand by volume with PCM can increase the latent heat of the mixture from around 0 to 7 J/g and decrease the thermal conductivity of PCM mortar based on the generalized self-consistent (GSC) model by about 20%. However, the workability and mechanical properties were compromised. The simulation results indicated that 30% PCM-incorporated walls can contribute to 5% energy saving for cooling in a whole year and 12% reduction in peak cooling load compared with the reference without PCM. The proposed PCM composite offers a promising avenue to achieve energy-efficient building envelopes. [ABSTRACT FROM AUTHOR]

With the increase in energy demand and carbon emission requirements, energy management and CO2 emission reduction on the user side are significant for integrated energy system (IES) scheduling. This paper constructs a two-stage optimal dispatching model combining active/passive demand response (DR) and reward and punishment ladder-type carbon trading. In the first stage, the electricity/gas load was optimized by adding a logistics function to the active DR model. A passive DR model is built based on the optimized electric load and the heat/cooling–electricity ratio of the cogeneration unit to optimize the heat/cooling load. In the second stage, a multi-objective IES model based on the optimized load and reward and punishment ladder carbon trading was solved by the golden eagle multi-objective optimization (MOGEO). Analyzing the scheduling results from different scenarios, the active/passive DR model can reduce the load peak-to-valley difference and improve user satisfaction and grid revenue. At the same time, the combination of reward and punishment ladder carbon trading makes the system gain more carbon revenue, reduces system operating costs and carbon emissions, and improves energy utilization. [ABSTRACT FROM AUTHOR]

This paper presents experimental and thermodynamic investigations of the performance of commercial refrigeration systems with capacities varying from 6 to 26 tons of refrigeration. The analysis considers a critical comparison between the conventional and widely used single-phase approach with the actual multi-phase methodology. The tests were performed under practical conditions with state-of-the-art experimental setups using variable cooling loads. The tests were performed in a climate chamber with advanced ambient temperature and humidity control equipment, where temperature can be raised up to 65 °C, and humidity can vary from 10 to 90%. This enabled us to simulate a wide range of operating modes to validate the performances of the proposed two-phase refrigeration system with theoretical results obtained from single-phase modeling. It was also found that the refrigeration system with a larger cooling capacity exhibited an operational performance close to two-phase theoretical results more than the small refrigeration system capacity. The experimental results were found to comply with the theoretical results with an error of approximately 10% for the two-phase approach compared to an error of approximately 20% for the single-phase approach. [ABSTRACT FROM AUTHOR]

There is currently no way for subway air-conditioning systems to adjust to changes in passenger capacity in terms of air-supply volume and air-supply temperature. In this paper, a study of the setting of the air-supply volume and controlling the temperature in subway trains was conducted. Based on the fact that the air-supply volume in a subway train needs to meet the requirements of cooling load and humidity load, as well as fresh-air volume, the minimum critical air-supply volume curve was determined on the basis of theoretical calculations under different passenger capacities. Under different passenger capacity and air-supply-volume conditions, the PMV (predicted mean vote) distribution of the subway train was simulated and calculated, and the results indicated that increasing the air-supply volume would not be sufficient to achieve PMV = 0. Therefore, in accordance with the theoretical formulation of the PMV, multiple linear regression was used to fit the temperature-control curve for various passenger capacities. A simulation calculation of the subway train was used to assess the uniformity of the flow field and the temperature field within the subway train in accordance with EN14750. It is evident from the results that under the control curve of the air-supply volume and temperature under different passenger capacities, the uniformity of the flow field and the temperature field can meet the standard requirements. By using the air-supply volume and temperature-control curve proposed in this paper, it is possible to adjust the air-supply volume in real-time, control the temperature of the air-conditioning system of the subway train, improve the passenger comfort of the train, and reduce the energy consumption of the air-conditioning system. [ABSTRACT FROM AUTHOR]

In this paper, a cascade refrigeration system equipped with a single-screw compressor (SSC-CRS) is proposed and built in order to achieve the goal of high load cooling capacity under ultra-low temperature conditions. Firstly, the isentropic efficiency curve of the single-screw compressor (SSC) is fitted through experimental method in response to the characteristics of low suction temperature and large pressure ratio of the compressor. In addition, the analysis of SSC-CRS with 28 refrigerant pairs are made to compare the coefficient of refrigeration (COP) and power consumption. On the basis of the cascade system, the paper compares the improvement of performance between two circuits with SSC: vapor injection cascade refrigeration system (SSC-ICRS) and ejector vapor injection cascade refrigeration system (SSC-EICRS). The results indicate the COP improvement rate of SSC-ICRS system is 17.39 %–41.98 % and the COP improvement rate of SSC-EICRS system is 49.46 %–68.37 % compared with SSC-CRS. • The isentropic efficiency curve of the single-screw compressor is fitted through experimental method. • The analysis of SSC-CRS with 28 refrigerant pairs are made to compare the coefficient of refrigeration and power consumption. • The COP improvement rate of SSC-EICRS system is 49.46 %–68.37 % compared with SSC-CRS. [ABSTRACT FROM AUTHOR]

In this paper, an experimental investigation of the performance improvement of a heat pump equipped with a two-phase ejector, called an "ejector–expansion heat pump (EEHP)", is proposed. The system performance of the EEHP is compared with that of a vapor-compression heat pump (VCHP). The improvement potential is determined and discussed. The heat pump test system based on a water-to-water heat pump that can experiment with both the EEHP and the VCHP is constructed. A two-phase ejector with a cooling load of up to 2500 W is installed for the experiment. The results show that the EEHP always produces a higher heating rate and COPHP than the VCHP under the specified working conditions. The heating COPHP is increased by 5.7–11.6% depending on the working conditions. It is also found that, under the same heat sink and heat source temperature, the EEHP can produce a lower compressor discharge temperature and a lower compressor pressure ratio than the VCHP. This is evidence that the two-phase ejector can provide the compressor with better working characteristics, which yields a longer compressor lifetime. It is demonstrated that the expansion pressure ratio is key to the performance of the EEHP. A larger expansion pressure ratio yields greater improvement potential when compared with the VCHP. [ABSTRACT FROM AUTHOR]

A Trombe wall with thermal catalytic blinds (TC-Blind/TW) for indoor heating/cooling, air purification and shading was proposed. In this paper, we has fully explored the advancement and feasibility of the system from thermal catalytic material preparation and performance testing, system construction and system steady state experiment testing, system heat-mass transfer model establishment and verification, and finally to the analysis of system operation strategy. The main conclusions are as follows: Firstly, thermal catalytic material MnO x -CeO 2 behaved excellent heating and purification performance, the formaldehyde degradation followed L-H model. Secondly, the thermal efficiency and formaldehyde single-through conversion of system during the daytime were between 35%-55% and 32%–42%, respectively. Thirdly, the established heat-mass transfer model had the high accuracy, with the maximum RSMD of 0.8%. Finally, the blinds turning angle has a great influence on the system performance, then the optimal annual operation angles in four cities were suggested. Take Beijing as an example, the annual generated clean air was 11355.6 m3/m2, the reduced heating and cooling loads were 341.2 and 318.3 MJ/m2, respectively. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for predicting a warehouse's reduced load while offering flexibility. Physics-based energy simulations are first performed to model flexibility events, which involve adjusting cooling setpoints with controlled temperature increases to reduce the cooling load. The warehouse building encompasses office and storage spaces, and three cooling scenarios are implemented, i.e., exclusive storage area cooling, exclusive office area cooling, and cooling in both spaces, to expand the study's potential applications. Next, the simulation data are utilized for training machine learning (ML)-based pipelines, predicting five subsequent hourly energy consumption values an hour before the setpoint adjustments, providing time to plan participation in demand response programs or prepare for charging electric vehicles. For each scenario, the performance of an Artificial Neural Network (ANN) and a tree-based ML algorithm are compared. Moreover, an expanding window scheme is utilized, gradually incorporating new data and emulating online learning. The results indicate the superior performance of the tree-based algorithm, with an average error of less than 3.5% across all cases and a maximum hourly error of 7%. The achieved accuracy confirms the method's reliability even in dynamic scenarios where the integrated load of storage space and offices needs to be predicted. [ABSTRACT FROM AUTHOR]

The response potential of demand-side resources is becoming increasingly significant in integrated energy system (IES) operations. In addition, to ensure the effective participation of system devices, their actual responsiveness at different timescales should be considered. Based on these considerations, this paper proposes an IES multi-timescale operation optimization strategy that incorporates multiple forms of integrated demand response (IDR) and considers the response characteristics of the equipment. First, the multi-timescale characteristics of IDR are analyzed. Moreover, a multi-timescale operation model of IES that comprises day-ahead, intraday, and real-time stages is further established. In the day-ahead dispatch, a low-carbon economic scheduling model is developed by considering the shifting demand response (DR) and the cost of carbon emissions. In the intraday scheduling, noting that cooling and heat energy transmission possess slow dynamic characteristics, a rolling optimization model for cooling/heating coupled equipment considering load shedding and substituting DR is established. In real-time scheduling, the output of electric/gas coupled equipment is adjusted. Finally, an industrial park-type IES in northern China was selected as an example for a case study. The results show that (1) the IDR multi-timescale response strategy can exploit different types of demand-side flexibility resources. After implementing the shifting DR, the peak-to-valley difference of the electric load curve was reduced by 20%, and the total system cost was reduced by 2.3%. After implementing load shedding, the maximum load differences per unit period of the electric, heat, and cooling load curves decreased by 18.7%, 40.0%, and 68.9%, respectively. (2) By refining the timescale of IES optimization, the proposed model can effectively ensure the energy supply and demand balance of the system under different load scenarios and reduce the system operation cost. After applying the model to simulation in three typical days (transition season, summer, and winter), the penalty costs of lost loads reduce by ¥3650, ¥3807, and ¥3599, respectively, and the total system costs decrease by 17.4%, 16.1%, and 16.2%, respectively. [ABSTRACT FROM AUTHOR]

Determination of thermal insulation performance (i.e. optimum insulation thickness, energy saving and payback period) is a tedious and time-consuming task that requires a thorough knowledge in thermal insulation engineering and economics. The main goal of this paper is to make the determination of insulation performance simple and timesaving by introducing thermal insulation performance curves (TIPCs) from which the insulation performance can easily be found for any climate condition and all economic factors related to energy and insulation. These curves were generated based on a life-cycle cost analysis (LCCA) method. The curves can be easily read based on a single factor, called the f-factor, which comprises the number of degree-day, coefficient of performance, present worth factor, energy cost, and insulation cost. With the gain of heating and cooling degree days (i.e. HDD and CDD), TIPCs can be used for both heating and cooling loads. TIPCs cover commonly used insulation materials for building walls with thermal conductivities range from 0.020 to 0.055 W/m K. TIPCs were validated against published data. [ABSTRACT FROM AUTHOR]

The current paper proposes a double-flash geothermal system with a dual-pressure organic Rankine cycle binary system. To improve the system's performance, the inlet geofluid is preheated via an indirect mode of a solar system, and an Ejector Refrigeration Cycle system is installed to the geofluid's brine line to produce cooling capacity. Comprehensive investigations are performed to select the Dual-pressure Organic Rankine Cycle s working fluid among various pure substances and zeotropic mixtures that refer to choosing the R245ca/R142b. The system presents 12.12 MW net power at the base mode with a 1.87 MW cooling load and 4.88 years payback period. Some main parameters' change effect on the system is studied. The low-pressure steam turbine's exit pressure influences the cooling load and energetic efficiency. The high-pressure turbine's input pressure affects the total exergy destruction and net power higher than the other. The optimum state of the system is obtained through two energy-economic and exergy-economic assessments. The energy-economic assessment provides a higher cooling load of about 5.7 MW and a lower net power of about 10.8 MW with 4.59 years payback period. The exergy-economic assessment represents 12.22 MW net power and a cooling load of about 1.97 MW with 4.77 years payback period. • A novel solar and geothermal dual-source power and cooling system is proposed. • Different pure and zeotropic working fluids are employed to select the best one. • Applying energy, exergy, and economic analyses and multi-objective optimization. • R245ca/R142b is selected as the best working fluid in the DORC subsystem. • 12.12 MW net power and 26.45% exergetic efficiencies are obtained. [ABSTRACT FROM AUTHOR]

Transformer efficiency is a key concern for both transformer operators and regulators, particularly with regards to new transformers. Cooling is a critical factor in preventing overheating and controlling the ageing of transformer insulation. This paper aims to analyse how different cooling setups can influence efficiency. Transformer losses depend on the winding temperature, which is affected by load, ambient temperature, and cooling power. In this study, we will take all of these factors into consideration to examine their impact on transformer losses. Using a 520 MVA transformer as an example, we will calculate the loss levels under different realistic ambient temperature and load profiles. We will also apply different cooling system settings to determine the optimization possibilities. Our calculations will consider different turn-on temperatures of the fans and cooling stages and will use steady state calculations over a period of 12 months. Additionally, a novel approach to control cooling by using the loading of the transformer is present, as are the possibilities of using variable speed fans. Finally, we will estimate the influence of cooling settings on transformer ageing by examining their impact on temperature. [ABSTRACT FROM AUTHOR]

Phase change materials (PCMs) are recognized as a promising passive energy retrofit technology for existing buildings, as they are applied to the internal and external surfaces of the building with less impact on the original structure. However, the effectiveness of PCMs varies from region to region. Taking the Central Plains of China as an example, this paper investigated the effect of phase change temperature and material thickness variation on the energy efficiency of PCM when it was arranged on 14 placements including furniture through EnergyPlus (E+). And further explored the applicability of coupling PCMs with natural ventilation (NV). The results showed that: for the Central Plains of China, PCMs arranged on the internal surface of building roofs were optimal, and the reduction rate of uncomfortable degree hours could reach 38%, 26%, 24% and 40% after integrating PCMs into the roof, floor, external wall and furniture. The uncomfortable degree hour reduction rate per unit mass of PCM was 0.052%/kg for the roof, and the value of furniture was very close to the external wall and floor, which achieved 0.033%/kg. In addition, the coupling of PCM with NV improved the energy efficiency of PCM by more than twice. [ABSTRACT FROM AUTHOR]

In this paper, the coupling of a high temperature heat pump with a combined cooling, heat, and power system is investigated. The plant converts the input energy source (natural gas) into electricity and useful thermal energy by means of a cogenerator. Part of the thermal energy feeds an absorption chiller that produces the cooling energy to satisfy the cooling load of an existing industrial building located in northern Italy. The heat pump enhances the low temperature heat from the condenser and absorber of the absorption chiller to high temperature heat to integrate the hot water produced by the cogenerator. The energy performance of the entire plant is analyzed by means of steady-state simulations at both fixed conditions and on an annual operation to meet the heating, cooling, and electric needs of the building varying different parameters and compared to traditional systems for energy production. As the main results, the integrated system provides flexibility and achieves valuable energy performances, in the range of a few tens of percent with respect to benchmark energy production systems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings. Design/methodology/approach: A feature selection scheme and stacking ensemble model to fulfill cooling load prediction task was proposed. Firstly, the abnormal data were identified by the data density estimation algorithm. Secondly, the crucial input features were clarified from three aspects (i.e. historical load information, time information and meteorological information). Thirdly, the stacking ensemble model combined long short-term memory network and light gradient boosting machine was utilized to predict the cooling load. Finally, the proposed framework performances by predicting cooling load of office buildings were verified with indicators. Findings: The identified input features can improve the prediction performance. The prediction accuracy of the proposed model is preferable to the existing ones. The stacking ensemble model is robust to weather forecasting errors. Originality/value: The stacking ensemble model was used to fulfill cooling load prediction task which can overcome the shortcomings of deep learning models. The input features of the model, which are less focused on in most studies, are taken as an important step in this paper. [ABSTRACT FROM AUTHOR]