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In this paper, the Ant-based Radial Basis Function Network (ARBFN) is proposed to determine the optimal daily dispatch of ice-storage air-conditioning systems. ARBFN is a novel algorithm that is integrated into the Ant Colony Optimization and Radial Basis Function Network. ARBFN is used to construct the function of the cost and operation for each chiller and ice-storage tank and is used to simulate the polynomial function of the cooling load and the cost of power consumption. The best learning rate in the training process is adjusted in ARBFN to improve the accuracy of constructing models for chillers and ice-storage tanks. The electricity savings are thus 4.130% on a summer day and 7.381% on a non-summer day. The results have shown that ARBFN can more accurately calculate the actual power consumption and cooling capability of each chiller and ice-storage tank. Lastly, ACO is used to calculate the daily dispatch of the ice-storage air-conditioning system. The results demonstrated the optimization of energy savings and efficiency for the operation of the ice-storage air-conditioning system. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper assesses the dynamic thermal inertia performance of unfired clay bricks with dry-grass fiber additives. The used raw material was retrieved from Ifrane in Morocco. The used clay was illite with a 59.60% silicon proportion. Multiple percentages (0%, 1%, 7%, and 15%) were analyzed in this study. The dynamic thermal inertia simulation was carried out in TRNSYS software to investigate the specimens' time lag, decrement factor, and heating and cooling loads. For this purpose, a reference house with three different wall thicknesses (0.20, 0.25, and 0.30 m) was evaluated. Collected findings reflected great time lag improvements. With the incorporation of 15% additive, 13.11 h was recorded. This reflected a thermal gain of 49.12% with the use of 0.30-m-thick walls. Decrement factor analysis also recorded interesting improvements. Thermal cooling and heating loads also recorded prominent energy savings of 95% and 60%, respectively. Finally, adopting thicker building walls recorded great thermal gains in the range of 60%. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? A hybrid desiccant M-cycle cooling system with an HDH unit is proposed for simultaneous cooling and water production. Three typical operational modes are analysed and compared in terms of cooling and water production. What is the implication of the main finding? The recirculation mode exhibited a superior cooling performance than the other two modes. The water production rates and system COP were similar among the three modes. In this paper, the cooling and freshwater generation performance of a novel hybrid configuration of a solid desiccant-based M-cycle cooling system (SDM) combined with a humidification–dehumidification (HDH) desalination unit is analysed and compared in three operational modes: ventilation, recirculation, and half recirculation. The HDH unit in this system recycles the moist waste air sourced from the M-cycle cooler and rotary desiccant wheel of the SDM system to enhance water production. A mathematical model was established and solved using TRNSYS and EES software. The results of this study indicate that the recirculation mode exhibited superior cooling performance compared to the other two modes, producing up to 7.91 kW of cooling load and maintaining a supply air temperature below 20.85 °C and humidity of 12.72 g/kg under various ambient conditions. All the operational modes showed similar water production rates of around 52.74 kg/h, 52.43 kg/h, and 52.14 kg/h for the recirculation, half-recirculation and ventilation modes, respectively, across a range of operating temperatures. The recirculation mode also exhibited a higher COP compared to the other modes, as the environmental temperature and relative humidity were above 35 °C and 50%. However, it should be noted that the implementation of the recirculation mode resulted in a higher water consumption rate, with a maximum value of 5.52 kg/h when the inlet air reached 45 °C, which partially offset the benefits of this mode. [ABSTRACT FROM AUTHOR]

The closed evaporative cooling tower (CECT) is widely used in the field of industrial cooling. At present, most CECTs still mainly adopt the horizontal-tube falling-film cooling method. In this paper, a novel vertical CECT using 3D deformation tubes is developed. To investigate the vertical surface falling-film evaporative cooling effect of this novel cooling equipment, a traditional horizontal CECT was modified to produce a prototype of vertical non-packing CECT. The cooling performance of the novel vertical CECT has been investigated and compared to the previous traditional horizontal CECT by experimental method. The results show that the convective heat transfer coefficient of the water film outside the tube was increased by 5.87~12.95% and the overall cooling performance was increased by 7.31% on average. This indicates that the cooling load can be increased by changing the traditional horizontal-tube falling-film evaporative cooling method to the vertical falling-film evaporative cooling method. Moreover, the heat flux of the novel vertical CECT decreases by about 7% when the wet bulb temperature increases by 1 °C under the test range of wet bulb temperature, which indicates that the ambient wet bulb temperature has an obvious influence on the cooling load. The research results can provide reference for the optimization design of the CECT. [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 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]

This paper provides a method for predicting the energy efficiency of buildings using artificial intelligence tools. The scopes is twofold: prediction of the levels of the heating load and cooling load of buildings. A feature of this research is the performance of intellectual analysis in conditions of a limited amount of data when solving the stated tasks. An improved method of augmentation and prediction (input-doubling method) is proposed by processing data within each cluster of the studied dataset. The selection of the latter occurs due to the use of the fast and easy-to-implement k-means method. Next, a prediction is made using the input-doubling method within each separate cluster. The simulation of the method was performed on a real-world dataset of 768 observations. The proposed approach was found to have a high prediction accuracy in the absence of overfitting and high generalization properties of the improved method. Comparison with existing methods showed an increase in accuracy by 40-46% (MSE) compared to SVR with rbf kernel, which is the basis for the improved method, and by 5-12% (MSE) compared to the closest existing hierarchical predictor. [ABSTRACT FROM AUTHOR]

During the pre-design stage of buildings, reliable long-term prediction of thermal loads is significant for cooling/heating system configuration and efficient operation. This paper proposes a surrogate modeling method to predict all-year hourly cooling/heating loads in high resolution for retail, hotel, and office buildings. 16 384 surrogate models are simulated in EnergyPlus to generate the load database, which contains 7 crucial building features as inputs and hourly loads as outputs. K-nearest-neighbors (KNN) is chosen as the data-driven algorithm to approximate the surrogates for load prediction. With test samples from the database, performances of five different spatial metrics for KNN are evaluated and optimized. Results show that the Manhattan distance is the optimal metric with the highest efficient hour rates of 93.57% and 97.14% for cooling and heating loads in office buildings. The method is verified by predicting the thermal loads of a given district in Shanghai, China. The mean absolute percentage errors (MAPE) are 5.26% and 6.88% for cooling/heating loads, respectively, and 5.63% for the annual thermal loads. The proposed surrogate modeling method meets the precision requirement of engineering in the building pre-design stage and achieves the fast prediction of all-year hourly thermal loads at the district level. As a data-driven approximation, it does not require as much detailed building information as the commonly used physics-based methods. And by pre-simulation of sufficient prototypical models, the method overcomes the gaps of data missing in current data-driven methods. [ABSTRACT FROM AUTHOR]

An important aspect in improving the energy efficiency of buildings is the effective use of building heating and cooling load prediction models. A lot of studies have been undertaken in recent years to anticipate cooling and heating loads. Choosing the most effective input parameters as well as developing a high-accuracy forecasting model are the most difficult and important aspects of prediction. The goal of this research is to create an intelligent data-driven load forecast model for residential construction heating and cooling load intensities. In this paper, the shuffled shepherd red deer optimization linked self-systematized intelligent fuzzy reasoning-based neural network (SSRD-SsIF-NN) is introduced as a novel intelligent data-driven load prediction method. To test the suggested approaches, a simulated dataset based on the climate of Dhahran, Saudi Arabia will be employed, with building system parameters as input factors and heating and cooling loads as output results for each system. The simulation of this research is executed using MATLAB software. Finally, the theoretical and experimental results demonstrate the efficacy of the presented techniques. In terms of Mean Square Error (MSE), Root Mean Square Error (RMSE), Regression (R) values, Mean Absolute Error (MAE), coefficient of determination (R2), and other metrics, their prediction performance is compared to that of other conventional methods. It shows that the proposed method has achieved the finest performance of load prediction compared with the conventional methods. [ABSTRACT FROM AUTHOR]

In this paper, an economic investigation is performed to identify the economic feasibility of a solar-powered adsorption cooling system. In the first step, the system is mathematically formulated, and the solar fraction of the system is calculated. After that, the system is economically optimized for a cooling load related to a single-family house using particle swarm optimization. In order to identify the most efficient application of the system, the cost per 1 kW of cooling capacity is calculated over different cooling loads. The results demonstrated that the system under study is more suitable for small-scale applications. In addition, sensitivity to electricity price analysis demonstrates that the main bottleneck of cost-efficient system design is the initial price of the solar collector. Therefore, in the next step, the former sensitivity analysis to electricity price is jointly performed over different initial prices of the solar collector at two different cooling loads. Finally, by considering the cost of CO2 capture and the amount of avoided CO2 by utilizing solar energy, the environmental benefit of the system under investigation is calculated. The results show that the optimum solution is 13% more cost-efficient compared to the base design. In addition, taking the CO2 capture parameters into account, the environmentally friendly case has 21% more annual cost compared to the optimal solution one. However, this extra cost can be justified through CO2 capture cost. [ABSTRACT FROM AUTHOR]

Building energy consumption prediction has become an important research problem within the context of sustainable homes and smart cities. Data-driven approaches have been regarded as the most suitable for integration into smart houses. With the wide deployment of IoT sensors, the data generated from these sensors can be used for modeling and forecasting energy consumption patterns. Existing studies lag in prediction accuracy and various attributes of buildings are not very well studied. This study follows a data-driven approach in this regard. The novelty of the paper lies in the fact that an ensemble model is proposed, which provides higher performance regarding cooling and heating load prediction. Moreover, the influence of different features on heating and cooling load is investigated. Experiments are performed by considering different features such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. Results indicate that relative compactness, surface area, and wall area play a significant role in selecting the appropriate cooling and heating load for a building. The proposed model achieves 0.999 R 2 for heating load prediction and 0.997 R 2 for cooling load prediction, which is superior to existing state-of-the-art models. The precise prediction of heating and cooling load, can help engineers design energy-efficient buildings, especially in the context of future smart homes. [ABSTRACT FROM AUTHOR]

According to the established model of a single resonance energy selective electron refrigerator with heat leakage in the previous literature, this paper performs multi-objective optimization with finite-time thermodynamic theory and NSGA-II algorithm. Cooling load ( R ¯ ), coefficient of performance (ε), ecological function ( E C O ¯ ), and figure of merit ( χ ¯ ) of the ESER are taken as objective functions. Energy boundary (E ′ / k B) and resonance width (Δ E / k B) are regarded as optimization variables and their optimal intervals are obtained. The optimal solutions of quadru-, tri-, bi-, and single-objective optimizations are obtained by selecting the minimum deviation indices with three approaches of TOPSIS, LINMAP, and Shannon Entropy; the smaller the value of deviation index, the better the result. The results show that values of E ′ / k B and Δ E / k B are closely related to the values of the four optimization objectives; selecting the appropriate values of the system can design the system for optimal performance. The deviation indices are 0.0812 with LINMAP and TOPSIS approaches for four-objective optimization ( E C O ¯ − R ¯ − ε − χ ¯ ), while the deviation indices are 0.1085, 0.8455, 0.1865, and 0.1780 for four single-objective optimizations of maximum E C O ¯ , R ¯ , ε , and χ ¯ , respectively. Compared with single-objective optimization, four-objective optimization can better take different optimization objectives into account by choosing appropriate decision-making approaches. The optimal values of E ′ / k B and Δ E / k B range mainly from 12 to 13, and 1.5 to 2.5, respectively, for the four-objective optimization. [ABSTRACT FROM AUTHOR]

The foundation of energy-efficient architectural design is modeling heating and cooling loads (HLs and CLs), which defines the heating and cooling apparatus constraints necessary to maintain a suitable interior air environment. It is possible that analytical models for energy-efficient buildings might offer an accurate evaluation of the influence that various building designs would have. The implementation of these instruments, however, might be a process that requires a significant amount of manual labor, a significant amount of time, and is reliant on user experiences. In light of this, the authors of this paper present two unique methods for estimating the CL of residential structures in the form of complex mathematical concepts. These methodologies include an evolutionary web algorithm (EWA), biogeography-based optimization (BBO), and a hybridization of an adaptive neuro-fuzzy interface system (ANFIS), namely BBO-ANFIS and EWA-ANFIS. The findings initiated from each of the suggested models are evaluated with the help of various performance metrics. Moreover, it is possible to determine which model is the most effective by comparing their coefficient of determination ( R 2   ) and its root mean square error (RMSE) to each other. In mapping non-linear connections between input and output variables, the observed findings showed that the models used have a great capability. In addition, the results showed that BBO-ANFIS was the superior forecasting model out of the two provided models, with the lowest value of RMSE and the greatest value of R 2   (RMSE = 0.10731 and 0.11282 and R 2   = 0.97776 and 0.97552 for training and testing phases, respectively). The EWA-ANFIS also demonstrated RMSE and R 2   values of 0.18682 and 0.17681 and 0.93096 and 0.93874 for the training and testing phases, respectively. Finally, this study has proven that ANN is a powerful tool and will be useful for predicting the CL in residential buildings. [ABSTRACT FROM AUTHOR]

Aiming at the issues of unreasonable cooperation schemes and inappropriate setting of parameters of the refrigeration system with multi-chiller plants, this paper presents a cooperative optimization method to improve the energy performance of the system composed of water-cooled chillers and air-cooled heat pumps. The cooperative optimization process includes scheme optimization and parameter optimization. To content the dynamic cooling load, the working sequence of air-cooled heat pumps and water-cooled chillers with variable frequency chilled water pumps is first optimized. Based on the optimal scheme, a back-propagation neural network (BPNN) coupled with particle swarm optimization (PSO) is implemented to explore the preferred operating parameters of multiple chiller plants corresponding to the best coefficient of performance (COP). Compared with the performance of the initial operation module, the energy consumption of the water pump and fan decreases by over 50%, and the COP of the refrigeration system is improved by 16% (COP = 3.85) through the scheme operation. After parameter optimization, the total energy consumption is reduced by 21.7%, and COP is increased by 26.5% (COP = 4.20). Therefore, the proposed cooperative optimization method can provide useful operation guidance for the refrigeration system with multi-chiller plants. [ABSTRACT FROM AUTHOR]

The novelty of this work is a new type of stack, namely, the parallel wave stack (PWS). In this paper, we study the performance of an air-based standing wave thermoacoustic refrigerator using the PWS. We use small heat pipes with a heat transfer rate of approximately 30 W as heat exchangers for the system. We investigate the effect of the ratio of stack length (Ls) to the distance between stack center and reflector (Xs) on the performance of the refrigerator parallel wave stacks with a blockage ratio (BR) of 67 %, 71 %, and 74 %, and with Ls/Xs ratios of 0.74, 0.96, and 1.20. We tested and compared these under a cooling load (Qc) of 0.5 W to 2 W and a frequency of 150 Hz. The results show that a BR of 71% with an Ls/Xs ratio of 0.96 provides a minimum cold-side temperature (Tc), and a maximum temperature difference (ΔTm), a maximum coefficient of performance, and a maximum relative coefficient of performance. This new type of stack can provide a higher performance. The structure of the stack is also stronger than others. This stack is an alternative and can be used in a thermoacoustic refrigerator. The results obtained from the present study will be very useful for improving the performance of the thermoacoustic refrigerator in the future. [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 recent years, diverse energy has been integrated into the power system, which constitutes a regional integrated energy system (IES). However, the coupling and complementation of multiple energy sources make load forecasting more difficult. For the time‐sequence and non‐linear characteristics of electric load and the complementarity of different energy in IES, this paper proposed an attention‐based convolutional neural network (CNN) combined with long short‐term memory (LSTM) and bidirectional long short‐term memory (BiLSTM) model for short‐term load forecasting in IES. The historical load, temperature, cooling load, and gas consumption of the past 5 days are used as the input features. CNN integrated with attention block is utilized to extract effective features of the load impact factors. Then the load of the next hour is forecasted by the LSTM combined with BiLSTM layers. Finally, the model is verified by the data from an integrated energy park in North China. The results show that the proposed method has better forecasting performance than CNN‐BiLSTM, CNN‐LSTM, BiLSTM, LSTM, backpropagation neural network (BPNN), random forest regression (RFR), and support vector machine regression (SVR). [ABSTRACT FROM AUTHOR]

The rapid increase in cooling demand for air-conditioning worldwide brings the need for more efficient cooling solutions based on renewable energy. Seawater air-conditioning (SWAC) can provide base-load cooling services in coastal areas utilizing deep cold seawater. This technology is suggested for inter-tropical regions where demand for cooling is high throughout the year, and it has been implemented in islands with short distances from the coast and the deep sea. This paper proposes adjustments to the conventional design of SWAC plants to reduce implementation risks and costs. The approach is named high velocity SWAC and consists of increasing the excavation depth of the seawater pump station up to 20 m below the sea level, compared to 2 to 5 m in conventional SWAC projects. This allows a twofold increase in the speed of inlet pipeline seawater and cooling load of the plant. The cooling load can be expanded twofold with only 55% capital cost and 83% project costs, compared with the costs of a new system. In addition, this article shows that high velocity SWAC plants with thermal energy storage will have an important role supporting the dissemination of intermittent renewable sources of energy in regions where SWAC is a viable cooling alternative. [ABSTRACT FROM AUTHOR]

User behaviour can significantly affect indoor thermal comfort conditions, as well as energy consumption, especially in existing buildings with high thermal masses where natural cross ventilation is the main strategy to reduce cooling loads. The aims of this paper were: (i) to compare how behavioural changes evaluated by means of rule-based and stochastic models lead to changes in indoor thermal comfort levels, and (ii) to define the patterns of indoor thermal comfort in historic residential buildings in future scenarios. To this end, a historic building located in Molfetta (Southern Italy) was analysed using a dynamic energy simulation engine in five weather scenarios (Typical Meteorological Year, current extreme weather file 2018, predicted weather files for 2020, 2050, and 2080 generated by morphing method), and stochastic and rule-based models for window openings were adopted and compared. The results showed that the stochastic model was more accurate than the rule-based one, resulting in a reduction of discomfort conditions during the summer period between 30% and 50% in all climate scenarios. However, although the differences between predicted discomfort levels using rule-based and stochastic models tended to increase, discomfort levels still appeared to be not acceptable in the 2050 and 2080 scenarios due to the rising temperature driven by climate change. [ABSTRACT FROM AUTHOR]

The purpose of this research is to design an energy-efficient off-grid vending machine that has a refrigeration system powered by an environmentally friendly refrigerant. The paper presents details from the equipment's design phase in terms of the resistance structure, photovoltaic panels area dimensioning, but also in terms of the necessary cooling load to be provided by the refrigeration system. The refrigerant chosen was R290 following a comparative analysis, which showed that it has an efficiency 6.6% higher than R134a. During the monitoring periods, the outdoors temperature varied between −4–28 °C, the relative humidity between 22–100% and yet only a slight indoor temperature variation of ±1.5 °C compared to the set value was recorded. The battery module managed to store enough energy from the photovoltaic panels to keep the vending machine functional through three consecutive days with adverse environmental conditions, as evidenced by the low variation of indoor temperature [ABSTRACT FROM AUTHOR]

Cooling buildings represent a major environmental issue, especially during summers. Although thermal insulation can decrease cooling loads, the presence of thermal bridges, infiltrations, windows, and other openings pose a continuous challenge. In the Middle East and North Africa (MENA) region, for instance, most windows are made of aluminum, a thermal conductor. This paper uses two methods to evaluate the alternative solution of enveloping buildings, including windows, with a secondary layer. The first method involved small-scale models; two test rooms were built, with one (the reference room) being based on regular municipal thermal guidelines and the other (the enveloped room) including an extra, secondary surrounding layer. The second test staged a similar scenario via software simulation. Both sets of results showed a significant reduction in electricity consumption in the enveloped room, which became more notable as the weather grew hotter. At the high end of the temperature scale, the power consumption of the enveloped room was 47%–54% lower than that of the reference room. However, such a secondary building envelope would increase the width of the wall structure and present the downside of adding to construction costs. While adopting this system in Dubai may save the city an estimated 16.6% in electrical energy, based on current prices, a house would likely need between 10 and 15 years to recuperate the associated capital investment. [ABSTRACT FROM AUTHOR]

Based on the features of large heating power per unit volume and small cooling surface area, the thermal management is one of the key technologies and plays a significant role for the pulsed inductor. A mathematical model that describes the heat transfer and thermal accumulation processes with the operating condition of periodic pulse loading for the pulsed inductor has been developed and validated in this paper, and the model results show a fine accuracy as compared with the test data. In addition, a computer code has been implemented to simulate the thermal accumulation and performance of natural cooling with different operating conditions (as the various of pulse voltage, pulse spacing, and pulse duration). The results show that the pulse voltage, pulse spacing, and pulse duration are the focus factors to the thermal accumulation for the pulsed inductor, and the effect of the natural cooling by surface area of the inductor is poor under the periodic pulse loading. [ABSTRACT FROM PUBLISHER]

Nowadays, since energy management of buildings contributes to the operation cost, many efforts are made to optimize the energy consumption of buildings. In addition, the most consumed energy in the buildings is assigned to the indoor heating and cooling comforts. In this regard, this paper proposes a heating and cooling load forecasting methodology, which by taking this methodology into the account energy consumption of the buildings can be optimized. Multilayer perceptron (MLP) and support vector regression (SVR) for the heating and cooling load forecasting of residential buildings are employed. MLP and SVR are the applications of artificial neural networks and machine learning, respectively. These methods commonly are used for modeling and regression and produce a linear mapping between input and output variables. Proposed methods are taught using training data pertaining to the characteristics of each sample in the dataset. To apply the proposed methods, a simulated dataset will be used, in which the technical parameters of the building are used as input variables and heating and cooling loads are selected as output variables for each network. Finally, the simulation and numerical results illustrates the effectiveness of the proposed methodologies. [ABSTRACT FROM AUTHOR]

Office buildings require a significant amount of energy for heating and cooling purposes. A possible strategy for reducing this energy in order to reduce carbon dioxide emissions and operational costs is to specify high-performance facades. However, their benefits remain unclear for UK conditions with mild winters and cool summers. This paper reports on an investigation on the energy demand of offices in London, UK, incorporating facades with U-values between 1·2 and 2·6 W/(m2 K) and g-values between 0·3 and 0·5 using the dynamic simulation tool Tas. Other variables considered included climate change (using the Chartered Institution of Building Services Engineers' future weather data files), low internal gains, long working hours and office orientation. It was found that, apart from the case when internal gains are low, cooling is overwhelmingly necessary and energy usage increases with decreasing U-value and decreases with decreasing g-value. Low-U-value facades act to reduce conduction heat losses, thereby increasing energy use. Conversely, low-g-value facades act to reduce solar heat gains, thereby reducing the energy required for cooling. The results are used to highlight deficiencies in The Building Regulations 2010 and where more advice would be of benefit. The paper also discusses the merits of a number of strategies for reducing energy use in office buildings. [ABSTRACT FROM AUTHOR]

The Earth to air heat exchanger (EAHE) is an effective passive cooling and heating system for buildings. This paper studied numerically the potential for reduction in energy consumption for cooling and heating loads for a residence equipped with an EAHE system in the climate of Nasiriya city, which is located in southern Iraq and at 31.7°N and 45.8°E, latitude and longitude, respectively. Also, this paper presents a study about the thermal performance of three types of EAHE systems, system 1, consisting of one layer of EAHE and buried at an available area of house garden with 3‐m depth, system 2, at the same site of system 1, but with two layers of EAHE at two depths, 3 and 4 m, and finally, system 3, buried along the area of the house at a depth of 3 m. First, the built numerical model was validated against experimental results, and the results of the comparison showed good agreement. The electricity consumption for cooling and heating of the house is calculated with and without the EAHE system. The results showed that with using EAHE, there is a considerable saving in energy and saving in the cost of electricity consumption, which reached 376 329 IQD ($301.11) over 1 year for system 2. [ABSTRACT FROM AUTHOR]

Copyright of Maintenance & Reliability / Eksploatacja i Niezawodność is the property of Polish Scientific & Technical Society Consumables, Polish Maintenance Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Recovering waste heat from urban infrastructures is becoming increasingly important as the UK strives to decarbonise heat, which remains one of the main challenges in the transition towards net zero. The Bunhill Waste Heat Recovery (WHR) System represents a first of its kind scheme that will recover waste energy from a ventilation shaft of the London Underground (LU) transport network. The system is based upon the installation of a heat recovery heat exchanger that consists of cooling coils and a reversible fan. The coils are connected to a heat pump that supplies low-carbon thermal energy to the Bunhill Heat Network in Central London. One particularly important aspect of the Bunhill WHR system is its ability to operate in a way that not only provides heating to the local heat network, but can also simultaneously supply cooled air to the LU tunnels depending on the operation of the reversible fan. The current paper estimates the potential cooling benefit that could be achieved with the WHR system based upon the development of a mathematical model. The model is able to predict the condition of the coil surface according to air inlet parameters, and this is used to calculate the latent and sensible cooling loads, which are applied to simulate how the system affects the local tunnel environment, with peak temperature reductions of up to 7.2 K being estimated for adjacent stations in 2030. The results from the investigation are presented together with recommendations for further development and future deployment of heat recovery from metro systems, as this technology could be applied across London and elsewhere to deliver significant carbon and cost savings while improving the thermal environment of railway tunnels. Practical Application: This work investigates the cooling potential behind a practical project that involves recovering waste heat from the LU network. As electrification leads to an increased deployment of heat pump and district heating systems, waste heat could become a valuable resource for maximising energy efficiency, even more so when additional cooling benefits can be achieved. This paper aims to explore the impacts of cooling on railway tunnels, emphasising how secondary benefits, which are many times overlooked, could be critical to making waste heat recovery economically feasible, maximising its potential as a key technology for decarbonising heat. [ABSTRACT FROM AUTHOR]

Summary: Integration of information technology with multi‐carrier energy systems has paved the way for smart energy hubs (SEHs). Such energy hubs require stochastic modeling of intermittent renewable energy resources (RERs) and fluctuating demands to realize their optimal operation. Many excellent works are available related to their optimization but none of the existing works presents a comprehensive model which not only incorporates the stochastic nature of RERs and demands but also taps demand response potential in the presence of system storages. To fill this gap, this paper proposes a comprehensive model for an SEH which incorporates the stochastic nature of electrical, heating, and cooling demands in the presence of RERs, batteries, and thermal storages. In addition, optimal shifting of electrical, heating, and cooling loads are performed to further reduce the operational cost of SEH considering a price‐based demand response program (DRP). The cost minimization objective is formulated as a mixed‐integer linear programming (MILP) optimization problem. Five different cases are analyzed considering the inclusion and exclusion of storage and RERs with different percentages of shiftable loads for DRP. The proposed complex model is solved using CPLEX in GAMS environment. With RERs, cost reductions of 5.25% and 18.96% are observed in the operational cost of SEH without tapping demand response (DR) potential. When 10% and 20% loads are deemed to be shiftable for DR, operational costs reduce to 20.15% and 21.43% respectively with RERs and energy storages. Results of the study can support energy managers in the optimal operation of multi‐carrier energy systems. [ABSTRACT FROM AUTHOR]

In this paper, various eco-friendly refrigerant mixtures R430A, R436A, R436B, R435A, and R510A used in vapour compression refrigeration systems are considered for this study. All of them have zero ODP and very low GWP. On the basis of exergy features, the efficiency of various working fluids in vapour compression refrigeration cycles was compared. The exergy efficiency of mixtures is evaluated for various evaporating temperatures ranging from -40°C to -5°C at a constant condensation temperature of 45°C. The variation of exergy is also analyzed for various condensation temperatures ranging from 25°C to 60°C at a constant evaporating temperature of -10°C. The exergy losses in various components are computed and presented in Grassmann diagrams for a cooling load of 1 kW. The results indicate that all the investigated alternative refrigerant mixtures have higher exergy efficiency than R134A. The maximum exergy performance is 39.72% observed for the mixture R435A at an evaporation temperature of -30°C, and this value is 9.89% higher than that of R134a.The results also show that the highest and lowest exergy losses have occurred in the compressor and evaporator. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the implication of present and future bioclimatic potential of passive heating and cooling design strategies for climate change scenarios of five locations covering all climate zones of India. Weather data for future climate change were developed for A2 (medium-high) scenario of the Intergovernmental Panel on Climate Change (IPCC) for four time slices, namely TMY (Typical Meteorological Year), 2020, 2050 and 2080. A case study residential building was used for calibration and validation of the bioclimatic potential using EnergyPlus simulation. Results show a strong correlation between the annual bioclimatic summer and winter discomfort hours and the corresponding annual cooling and heating energy load for the changing climate scenarios. Results also show an overall increase in annual cooling energy load, over and above the base case, ranging from 18% to 89% among the five cities in 2020; 32% to 132% in 2050 and 58% to 184% in 2080 if residential buildings continue to be operated in the same manner as it is done today without passive strategies. The use of passive strategies may reduce the annual cooling load by about 50%– 60% in residential buildings in future. [ABSTRACT FROM AUTHOR]

Hybrid renewable energy systems are subject to extensive research around the world and different designs have found their way to the market and have been commercialized. These systems usually employ multiple components, both renewable and conventional, combined in a way to increase the system's overall efficiency and resilience and to lower GHG emissions. In this paper, a hybrid renewable energy system was designed for residential use and its annual energy performance was investigated and optimized. The multi-module hybrid system consists of a Ground-Air Heat Exchanger (GAHX), Photovoltaic Thermal (PVT) panels and Air to Water Heat Pump (AWHP). The developed system's annual performance was simulated in the TRaNsient SYStem (TRNSYS) environment and optimized using the General Algebraic Modelling System (GAMS) platform. Multi-objective non-linear optimization algorithms were developed and applied to define optimal system design and performance parameters while reducing cost and GHG emissions. The results revealed that the designed system was able to satisfy building thermal heating/cooling loads throughout the year. The ground source heat exchanger contributed 21.3% and 26.3% of the energy during heating and cooling seasons, respectively. The initial design was optimized in terms of key performance parameters and module sizes. The annual simulation analysis showed that the system was able to self-generate and meet nearly 29.4% of the total HVAC electricity needs, with the rest being supplied by the grid. The annual system module performance efficiencies were 13.4% for the PVT electric and 5.5% for the PVT thermal, with an AWHP COP of 4.0. [ABSTRACT FROM AUTHOR]

Reducing cooling loads in hot countries requires thermal insulation, and cooling methods be improved. Evaporative cooling, although problematic, is one solution that can be explored since it is significantly more efficient than regular compressor air conditioners, and the net result of using one is cooling. Furthermore, while compressor air conditioner efficiency decreases with rising temperatures in summer, evaporative ones, up to a point, are the exact opposite. A novel hybrid cooling system capable of combining both showed an 80% decrease in cooling load. The system's efficacy was assessed in this paper by thermally simulating designs that are suitable for the hot Middle East region. Two locations with different environments and building guidelines that are representative of the variations in the area were selected. The first was the hot, dry Baghdad environment; the other was Dubai's coastal, more humid city. Two different houses were designed to suit the municipal rules of each and accommodate the hybrid cooling system. As expected, the simulation results showed that savings in the dry Baghdad climate were high at 78% compared to a non-insulated alternative. In Dubai, unsurprisingly, they were less at 52% on the more humid coast. Further simulations revealed that this latter figure in the humid coast could also be achieved using good thermal insulation. [ABSTRACT FROM AUTHOR]

The mismatching between the predicted and the operational performance of buildings designed to be nearly zero-energy underlines the importance to study the post-occupancy behavior, to understand if the building-HVAC system is capable to meet the variable conditions even due to the progressive climate change. The paper proposes a discussion about the operational performance of an existing nearly zero-energy building in the Mediterranean climate, during the heating and cooling seasons. The monitoring shows that the required electrical power is always lower than the nominal one, also because the external conditions are not extreme as the design ones. In the colder days, the difference in the required power is −21%. In summer, there is a delay of two hours between the external maximum temperature and the maximum required power. However, the monitored power is usually higher than the nominal one, with a maximum value of +11%. Considering all proposed combinations for the design calculation, it is demonstrated that the real performance cannot be predicted during the design, because indoor and external conditions influence the dynamic behavior of the building-HVAC system. [ABSTRACT FROM AUTHOR]

In traditional air-conditioning system, low-temperature chilled water is used to cool air. Generally, the temperature difference between air to be operated and the chilled water is high, and majority of air can be operated using water at higher temperatures. Therefore, this paper proposes the concept of grade of load and the method of dividing cooling/heating load into different grades. A traditional air cooling/heating load and energy consumption of fresh air handling unit (FAHU) in Beijing, were compared with cooling/heating loads with different grades and energy consumption of FAHU with different grade energies. The results indicate that cooling and heating loads, handled by the lowest and highest water temperatures of 9.5°C and 37.5°C, account for 27% and 25% of cooling and heating loads in design conditions, respectively. The cumulative cooling/heating load handled by water temperature with highest grade, only accounts for 47%/35% of the total cumulative cooling/heating load. As compared to traditional air handling process, the energy-saving rate of FAHU using different grade energies is 16.4% in summer and 25.6% in winter. This study shows that handling air with different grade energies has significant energy-saving potential for air-conditioning system. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop guidelines for the placing of new coolers in cooling systems subject to retrofit. The effects of the accumulation of scale on the flow system are considered. A methodology to assess the interconnected effect of local fluid velocity and fouling deposition is developed. The local average fluid velocity depends on the water flow rate distribution across the piping network. The methodology has four main calculation components: a) the determination of the flow rate distribution across the piping network, b) the prediction of fouling deposition, c) determination of the hydraulic changes and the effect on fouling brought about by the placing of new exchangers into an existing structure, and d) the calculation of the total cooling load and pressure drop of the system. The set of disturbances introduced to the system through fouling and the incorporation of new coolers, create network responses that eventually influence the cooling capacity and the pressure drop. In this work, these interactions are analysed using two case studies. The results indicate that, from the thermal point of view, the incorporation of new heat exchangers is recommended in series. The limit is the point where the increase of the total pressure drop causes a reduction in the overall volumetric flow rate. New coolers added in parallel create a reduction of pressure drop and an increase in the overall water flow rate; however, this increase is not enough to counteract the reduction of fluid velocity and heat capacity removal. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to describe and categorize calculation methods for conducting a complete air conditioning study. More specifically, this paper is a general review of cooling loads calculation methods, psychrometric calculations for installing a central air conditioning unit, ways of fan coil units connection and air duct calculation methods. Design/methodology/approach – This paper was based on two pillars: a dissertation for an industrial facility and technical information found after methodical research. Findings – After a brief reference of the calculation methods and the air conditioning systems installed in this industrial facility, this paper concludes with the most appropriate calculation methods for this industrial facility. Research limitations/implications – This study describes some calculation methods. Thus, future research could be addressed toward the analysis of more methods. Practical implications – This paper includes implications for choosing the most appropriate calculation method according to the air conditioning system installed. Originality/value – The originality of this paper lies in the fact that, except for the theoretical part, there are some examples taken from a case study, thus it can be used as a future guide for selecting methods and systems of industrial air conditioning. [ABSTRACT FROM AUTHOR]

The objective of this paper is to analyze the performance of the rooftop photovoltaic (PV) system, taking into account its shading impact on the rooftop surface and the eventual cooling load of the building. This paper tests three approaches of the rooftop PV system: zero tilt angle flat PV configuration; PV configuration with a monthly adjusted tilt angle; and PV configuration with a dual-axis sun tracking system. Each of the PV configurations is optimized to do the following: minimize the self-shading among the adjacent arrays; maximize the rooftop surface shading to curtail the cooling load; maximize the net energy yield; and minimize the net levelized cost of energy (LCOE) of the PV system. The existing building model is developed in SketchUp Pro. The model is simulated in an EnergyPlus environment to calculate the building's cooling energy consumption with different shading scenarios in various PV configurations. Various rooftop PV configurations are designed and simulated in a System Advisor Model (SAM) to analyze the effect of self-shading of the adjacent PV arrays on the PV performance. The optimal distance between the arrays (for maximum net energy yield and minimum net LCOE) is found to be 1.5 m. The net LCOE of the optimal scenario is 5.247 ¢/kW h and 4.112 ¢/kW h for monthly tilt and dual-axis tracking arrangements, respectively. The economic surplus of the optimized system is 0.422 ¢/kW h and 0.258 ¢/kW h for the monthly tilt and dual-axis tracking arrangements, respectively, as compared to the ground-mounted system. [ABSTRACT FROM AUTHOR]