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With recent energy and environmental crises, the energy consumption prediction of air conditioning (AC) is essential. Notably, existing general prediction systems use the air temperature, real-time AC usage, time, occupancy, and AC historical energy consumption as inputs and employ feedforward neural networks. However, such systems face certain challenges. First, the input system may be difficult to reflect the real-time interaction among the building environment, occupants, and energy system; Second, the algorithms need to be upgraded to further improve accuracy, speed up convergence, and avoid overfitting. his paper introduces a novel parameter (group occupant behavior probability, GOBP) in the input system; and uses swarm intelligence algorithms with chaotic mapping and adaptive weight adjustment as optimization with LSTM and BP as the basic algorithms. The verification results obtained from five different buildings indicate the following: (1) The novel prediction system improved prediction performance with 20.08%–78.37 % of MAPE and 3.99%–53.28 % of CV-RMSE, however, it will increase 148.70s–1065.11s of calculation time. (2) For accuracy, using GOBP will improve the 0.30%–51.87 % and 0.18%–64.77 % by using swarm intelligence optimization algorithms. (3) This paper discusses the priority of selecting suitable inputs, algorithms, and optimization to combine a whole prediction system. • The definition of a simplified model using the group occupant behavior probability is proposed. • The chaotic mapping and adaptive weight adjustment are used for optimizing the swarm intelligent algorithms. • A reconstituted AC energy consumption prediction system is proposed with novel inputs and improved algorithms. • The reconstructed prediction system demonstrates improved prediction accuracy and data acquisition difficulty\. • The best combination of inputs and algorithms is discussed based on 60 groups of comparative experiments. [ABSTRACT FROM AUTHOR]

As the national digitization process accelerates, the number and energy consumption of data centers are increasing year by year. Want to reduce the PUE of the data center. It is correct to start from the perspective of optimizing the energy consumption of air conditioning system operation. In this paper, a predictive optimization control method that is different from previous real-time optimization control is proposed. Predict, optimize, control and adjust the operating parameters of the air conditioning water system in the data center. At the same time, it solves the energy saving problem of the air conditioning system and the lag problem of previous adjustments. Predictive optimization control has broad prospects in research on operation optimization of data center air conditioning water systems. • Reducing air conditioning water system energy consumption in data centers can lower PUE. • Predictive optimization can solve the lag problem of water systems. • After global prediction optimization, energy consumption was saved by 12.9%. [ABSTRACT FROM AUTHOR]

Natural cooling energy and high-efficient radiant cooling techniques are essential to mitigate energy resources shortage crisis, breakthrough on traditional convective air-conditioning systems in isolation between indoor and outdoor environment with high indoor air quality. In this paper, a polyethylene aerogel (PEA) and phase change material (PCM) integrated novel Trombe wall was proposed, involving natural cooling energy harvesting, cooling energy storage, indoor ventilation and radiant cooling. A two-dimensional unsteady numerical model based on surface-to surface (S2S) radiation model and effective specific heat capacity method was developed in the commercial software Ansys Fluent to evaluate the cooling performance and dynamic heat-transfer mechanism of the novel Trombe wall. Subsequently, climate-responsive operation strategies on ventilation modes were proposed to maximize natural cooling energy utilization and fresh air supply. Parametrical and comparative studies were conducted on optimal structural design and robust operation. Our results showed that, with the novel design and advanced operation strategies, passive cooling capacity of 0.64 kWh/m2·day can be provided, together with fresh air supply of 2705.2 kg/day (1.4 m2 Trombe wall), corresponding to air change rate per hour (ACH) of 1.15. In terms of active cooling system, the integration of PEA and PCM can effectively prevent moisture condensation and shift peak cooling load. Hence, radiant cooling capacity of 0.99 kWh/m2·day and radiant cooling ratio of 47 % can be achieved by the novel Trombe wall, with electricity consumption only at valley period. Moreover, economic saving of 55.0 CNY/day and decarbonization potential of 23.8 kg CO 2,e /day can be achieved when the novel Trombe wall is integrated into a typical office building in subtropical climate Guangzhou. This study provides a novel structural design and optimal operation strategies on a Trombe wall, together with guidelines on techno-economic-environmental performance improvement, promoting effective natural cooling energy utilization and energy-flexible/efficient radiant cooling for decarbonization of buildings in cooling-dominant regions. • A novel Trombe wall for natural cooling energy harvesting and radiant cooling. • An unsteady numerical model for thermodynamic analysis. • Passive cooling capacity of 0.64 kWh/m2.day and fresh air supply of 2705.2 kg/day. • Radiant cooling capacity of 0.99 kWh/m2·day and radiant cooling ratio of 47 %. • Daily CO 2 reduction of 23.8 kg and economic saving of 55.0 CNY in a typical office building. [ABSTRACT FROM AUTHOR]

In this paper, PSO-OMRC model is proposed for heating ventilation and air conditioning (HVAC) system. The PSO-OMRC predicts SPT in HVAC for energy saving and thermal comfort of persons in room. PSO-OMRC used data collected from temperature, humidity, PIR, and thermal camera sensors in HVAC installed rooms for SPT prediction. In existing HVAC systems, SPT is constant and consumes more energy. Moreover, SPT prediction using traditional machine learning algorithms considers various parameters such as room temperature, humidity and person count in room. Existing algorithms considers the above parameters for energy saving in HVAC and thermal comfort for persons, whereas other parameters such as room walls and ceiling temperature, human body temperature need to be considered for SPT prediction and for energy saving in HVAC. The PSO-OMRC model predicts the SPT based on number of occupants and microclimatic conditions such as environment temperature, humidity, room wall temperature and ceiling temperature. From experimental results, the utilization of the thermal image occupant model provides significant energy savings in the PSO-OMRC model. In nano coated room, PSO-OMRC model is evaluated with the implementation of a thermal image occupant model to improve energy savings, resulting in approximately 25.2% of energy savings while maintaining the level of thermal comfort. • Microclimatic and occupant data-based setpoint temperature prediction in HVAC. • Gaussian Process Regression algorithm is used to predict setpoint temperature. • The proposed PSO-OMRC model provides thermal comfort for occupants. • Nano coated room has considerable energy savings with PSO-OMRC model in HVAC. [ABSTRACT FROM AUTHOR]

Abstract Liquefied natural gas (LNG) is widely used in many countries around the world primarily as a mode of transport for natural gas. However, massive amount of energy (around 830 kJ/kg of LNG) is wasted during the regasification process in the LNG regasification terminals. Therefore, the technologies to utilize the LNG cold energy have received significant attention over recent decades. In this paper, we review various studies on the current LNG cold energy utilization systems, including power generation, air separation, desalination, cryogenic carbon dioxide capture, and NGL recovery. Utilizing LNG cold energy on such systems can improve the energetic and exergetic efficiencies significantly. Furthermore, several potential applications to utilize LNG cold energy in the future are proposed and discussed to broaden the perspectives of the researchers in the community. Among these potential applications, recovering LNG cold energy on cold chain for food transportation, data center cooling and hydrate based desalination are very promising. Finally, the limitations and challenges to be addressed for LNG cold energy utilization are discussed in detail. Graphical abstract Image 10764500 Highlights • Abundant amount of cold energy can be recovered during LNG regasification. • A comprehensive review on the state-of-the-art LNG cold energy utilization systems is provided. • LNG cold energy can be utilized for power generation, air separation, air conditioning and desalination. • Technologies to utilize LNG cold energy are analyzed and compared. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a mathematical model to enable a more in-depth understanding of the combined heat and mass transfer processes of a counter-flow indirect evaporative cooler operating in semi-arid regions. A series of simulation was conducted to compare the performances between a single-purge and four-purge configurations. Furthermore, the effect of several parameters on the performance of the single-purge configuration was investigated under the baseline condition. The developed model was validated against experimental data from literature to within 2% discrepancy. Key results revealed that the single-purge configuration produced higher cooling capacity (around 20% higher), as well as higher dew-point effectiveness under the same operating conditions. A parametric study was also made on the single-purge configuration. The results revealed that lower product air temperature and higher dew-point effectiveness were achieved with longer channel length and larger purge ratio. However, the maximum cooling capacity approached its maximum with longer channel length and 35% purge ratio. [ABSTRACT FROM AUTHOR]

Abstract In tropical climates, the energy consumed by ventilation and air conditioning can exceed 50% of the total consumption of a building. Demand for cooling is rising steadily, driven mainly by growing incomes in developing economies, and is expected to also increase with climate change. Tropical, coastal areas with narrow continental shelves are good sites for the implementation of Seawater Air Conditioning (SWAC), a renewable and low CO 2 emission cooling process. This paper presents the existing SWAC projects around the world and gives details on the technology. Data on ocean temperature profiles, ocean bathymetry and world surface temperature are processed with the intent of estimating the world potential of SWAC. The results present the required distance from coast to reach seawater with a temperature of 5 °C or less. This is combined with the potential demand for air conditioning, taking into account surface air temperature and a set SWAC design for cooling from 30 to 20 °C. The pipeline length, seawater depth and capacity factor are then used to estimate the costs of SWAC projects around the world. It is concluded that the locations with the highest potential for SWAC are intertropical islands and some continental locations. Highlights • This renewable source is ideal for tropical coastal areas with narrow continental shelves. • The energy in a m3/s of SWAC can be equivalent to 49 ha of solar PV or 42 MW of wind turbines. • A novel SWAC potential model is developed to identify the most promising sites worldwide. • Capacity factor, pipeline length, depth extraction and cost estimates are presented in detail. • The cheapest SWAC project costs $0.0185/KWh t and is located in Nauru, Pacific Ocean. [ABSTRACT FROM AUTHOR]

This paper proposes the design, construction, and test of a prototype R141b ejector refrigeration system. It was used as an air conditioner for a hot climate country (Thailand). The prototype machine was designed to work as a water chiller to provide thermal comfort condition for the tested room with the cooling capacity up to 4500 W. It was driven by hot water with temperatures of 90–98 °C. The condenser was cooled by water, which was provided by a cooling tower, with temperatures of 28–32 °C. CFD simulation was also employed to design the ejector. The tested results indicated that the prototype R141b ejector refrigerator working as an air conditioner was satisfactory in operating conditions consistent with a hot climate (Thailand's environment). The temperature of the air conditioned space was around 23 to 25 °C with the cooling load of 4500 W. The coefficient of performance (COP) was between 0.42 and 0.47. [ABSTRACT FROM AUTHOR]

The paper presents numerical analysis of heat recovery exchanger, which operates as an indirect evaporative air cooler in summer conditions and as a typical heat recovery unit during winter season. The numerical simulation is performed with the original mathematical model which is able to simulate the operation during summer and winter season. The model was validated against existing experimental data (operation as indirect evaporative air cooler) and against experimental data collected by authors at Wroclaw University of Technology (operation as heat recovery exchanger). Obtained results allowed for analysis of heat and mass transfer process occurring in considered exchanger during round-year operation. The characteristic heat and mass transfer zones for evaporative air cooler and heat recovery exchanger were established. Results also allowed for analysis of most important problems connected with achieving highest efficiency of the exchanger and achieving safe operating conditions during winter season (preventing the exchanger from freezing). Safe operating conditions (parameters of the ambient air in winter which would guarantee that no frost would be formed on the plates) were established. The analysis of the effectiveness of the novel exchanger with selected factors (i.e. obtained cooling capacity, thermal efficiency and relative effectiveness) was also presented in the paper. [ABSTRACT FROM AUTHOR]

Under the influence of building load stochasticity and thermal inertia of central air conditioning system, the lag of control strategy makes it difficult for the cooling source system to meet the cooling demand of users in real time, which affects the operational energy efficiency ratio of the cooling source system. In this regard, this paper proposes a chiller dynamic optimization method based on Markov chain model predictive control algorithm, which studies the optimization of parallel operation characteristics of multiple chillers on the basis of correcting the occurrence of small probability events and avoiding frequent chiller starts and stops, reveals the prediction law of hourly load distribution of the future air conditioning system, explores the balance point between the prediction time of building load and the calculation time of chiller control strategy, provides a theoretical basis and reference for determining the time limit of the optimal calculation and the output of the optimal control strategy. The study provides a theoretical basis and reference for determining the time limit of the optimal calculation and the output of the optimal control strategy. It is found that the optimal control strategy not only has good optimization effect, but also the confidence is significantly increased by 56.7%. • Markov chain predictions of building loads are time-bound. • Consider the impact of the randomness of the load time distribution. • The model takes into account the occurrence of small probability events. [ABSTRACT FROM AUTHOR]

The liquid desiccant air-conditioning system (LDAS) is a novel air-conditioner with good energy saving potential. Regenerator is the key component of the liquid desiccant air-conditioning system, which is the main energy-consumed part. Electrodialysis regenerator is a new liquid desiccant regeneration method which can meet the dehumidification requirements even when the environment air is hot and wet. In this paper, in order to reduce the waste of electrode solution and the operational cost of normal electrodialysis regenerator, a novel multi-function liquid desiccant regeneration system was developed and investigated. Moreover, an experimental system was constructed to achieve the accurate current efficiency of the new system. The results show that in order to improve the current efficiency of the multi-function desiccant regeneration system, the operational current and the concentration difference between solutions in regenerate chambers and dilute chambers should be both decreased. The ideal performance coefficient of liquid desiccant air-conditioning system can exceed 7 when the conductivity of liquid desiccant is higher than 300 mS/cm. In the practical application of the multi-function liquid desiccant regeneration system, the operational current will be designed to fulfill the hydrogen and halogen gas production of the system. [ABSTRACT FROM AUTHOR]

It is expected that energy saving may be attained by connecting heat source equipment and air conditioning equipment in multiple buildings with piping network and operating heat source equipment flexibly in consideration of heat demands required by air conditioning equipment. In this paper, an optimization method is proposed to operate such heat supply systems with piping network rationally. Mass flow rates and temperatures of water are adopted as basic variables to express heat flow rates as well as pressure and heat losses in piping segments. The discreteness for the selection of piping segments for water flow are also taken into account. To avoid treating the nonlinearity directly, mass flow rates are discretized, and the optimization problem is finally formulated as a mixed-integer linear programming one, and its suboptimal solution is derived efficiently by a two-stage approach. A case study is conducted for a heat supply system for space cooling and heating of an exhibition center with multiple buildings. Through the study, the validity and effectiveness of the proposed optimization method is shown in terms of solution optimality and computation time. In addition, it is shown how the primary energy consumption can be reduced using piping network. [ABSTRACT FROM AUTHOR]

The large ownership of direct-expansion (DX) air-conditioning (A/C) systems in small and medium-sized buildings brings with it the need to reduce their energy consumption without damaging the thermal comfort of the occupants. Model predictive control (MPC) is an effective method to optimally control the operation of air-conditioners. However, most existing MPC methods require the investment of additional equipment and labor-intensive work, which greatly increases the cost of MPC and hinders its practical application. To solve the problem, this paper presents an economical and practical MPC algorithm for DX A/C systems, capable of achieving a balance between thermal comfort and energy saving. The proposed algorithm was experimentally validated on both an experimental DX A/C system and a market available split-type air-conditioner. Experimental results on the experimental DX A/C system show that temperature and humidity set-points selected at α = 1 saved 23.3% of energy consumption compared to those selected at α = 0, while keeping indoor thermal comfort within acceptable range. And results on the split-type air-conditioner demonstrate energy savings of up to more than 32% compared to the baseline and proved that the algorithm can be practically applied on market available D/X air-conditioners. • A practical application-oriented model predictive control algorithm is developed for DX A/C systems. • A cooling capacity prediction ANN model of the DX A/C system is used to predict the cooling load. • An ANN model for predicting the operational status of the DX A/C system is developed without increasing the training data. • A cost function is used to balance indoor thermal comfort levels and energy consumption. • The algorithm has been validated in both an experimental DX A/C system and a market available split-type air-conditioner. [ABSTRACT FROM AUTHOR]

Decreasing fuel consumption in compressed air energy storage (CAES) system is a general trend for conserving energy and protecting the environment. Waste heat recovery is an interesting technology to compact energy storage system. However, CAES system has a low thermal efficiency when using low grade waste heat as heat source directly. In this paper, an integrated energy system consisting of a CAES system and a precooling system (PC-CAES) is proposed to decrease the energy consumption of compression train in the charging process, and enhance the round trip efficiency (RTE) of the system. Air conditioner is utilized as pre-cooler to precool the inlet air of compressor and five refrigerants are investigated. The thermodynamic analysis is performed by using steady-state mathematical model and thermodynamic laws. The calculation results show that the RTE of the proposed PC-CAES system is improved by more than 3% than that of the conventional CAES system and more economical than CAES with additional compression stages. Meanwhile, a parametric analysis is also carried out to evaluate the effects of several key parameters on the system performance of two CAES systems. [ABSTRACT FROM AUTHOR]

Abstract: Building legislation along with environmental and comfort concerns are increasingly driving designers of building services and air conditioning equipment towards more energy efficient solutions. Heat pipe technology is emerging as a viable, efficient and environmentally-sound technology for applications in efficient air handling unit designs. In this paper, an experimental investigation on the thermal performance of an air-to-air heat exchanger, which utilises heat pipe technology, will be presented. The heat exchanger consisted of 7 loop heat pipes with finned evaporator and condenser sections. The heat exchanger was fully instrumented to test for the effect of the variation of heat load and the air velocity, through the heat exchanger, on the overall thermal resistance of the loops. The values of the effectiveness of the heat pipe heat exchanger are shown to vary with the air velocity as expected but the results also allow the prediction of effectiveness variation with the heat load and operating temperature (previously assumed to be constant). The results allow an interpretation of the overall thermal performance of each loop heat pipe as a function of the load and air velocity. The paper concludes with a theoretical analysis of the energy savings that would be expected when utilising the technology in a representative application. [ABSTRACT FROM AUTHOR]

Abstract: The demand for electricity in the Maldives continues to increase by more than 11% in recent years. This is mainly due to the growing number of high-rise air-conditioned buildings and the increasing use of electrical appliances in the residential and commercial sector. This paper investigates potential cost savings and emission reductions achieved by installing different insulation materials of optimum thickness in building''s walls. The paper also investigates the effect when air gaps are introduced in the wall. The optimum insulation thickness is based on the cost benefits of each insulation material over its lifetime. This study found that by introducing optimal thickness of different insulation materials and by having air gaps of 2 cm, 4 cm and 6 cm, energy consumption and emissions can be reduced by 65–77%, in comparison to a wall without insulation or air gaps. And, hence have considerable cost savings. [Copyright &y& Elsevier]

Abstract: The paper brings new evidence on the impact of separate mechanical ventilation system on the annual energy and exergy performance of several design alternatives of residential heating systems, when they are designed for a house in Montreal. Mathematical models of residential heating, ventilation and domestic hot water (HVAC–DHW) systems, which are needed for this purpose, are developed and furthermore implemented in the Engineering Equation Solver (EES) environment. The Coefficient of Performance and the exergy efficiency are estimated as well as the entropy generation and exergy destruction of the overall system. The equivalent greenhouse gas emissions due to the on-site and off-site use of primary energy sources are also estimated. The addition of a mechanical ventilation system with heat recovery to any HVAC–DHW system discussed in the paper increases the energy efficiency; however, it decreases the exergy efficiency, which indicates a potential long-term damaging impact on the natural environment. Therefore, the use of a separate mechanical ventilation system in a house should be considered with caution, and recommended only when other means for controlling the indoor air quality cannot be applied. [Copyright &y& Elsevier]

Abstract: Efficient energy management in hybrid vehicles is the key for reducing fuel consumption and emissions. To capitalize on the benefits of using PHEVs (Plug-in Hybrid Electric Vehicles), an intelligent energy management system is developed and evaluated in this paper. Models of vehicle engine, air conditioning, powertrain, and hybrid electric drive system are first developed. The effect of road parameters such as bend direction and road slope angle as well as environmental factors such as wind (direction and speed) and thermal conditions are also modeled. Due to the nonlinear and complex nature of the interactions between PHEV–Environment–Driver components, a soft computing based intelligent management system is developed using three fuzzy logic controllers. The crucial fuzzy engine controller within the intelligent energy management system is made adaptive by using a hybrid multi-layer adaptive neuro-fuzzy inference system with genetic algorithm optimization. For adaptive learning, a number of datasets were created for different road conditions and a hybrid learning algorithm based on the least squared error estimate using the gradient descent method was proposed. The proposed adaptive intelligent energy management system can learn while it is running and makes proper adjustments during its operation. It is shown that the proposed intelligent energy management system is improving the performance of other existing systems. [Copyright &y& Elsevier]

The purpose of this paper is to address the problems experienced by customers in the utilisation of electrical energy for air conditioners (ACs). According to the proposed schema in this paper, the customer will be able to evaluate the impacts of a probable electricity price spike and the outside temperature (Tout) to calculate the total expected electricity cost for an AC (TEC). The aim of this paper is to show how consumers can estimate the TEC for any temperature. In this research, a model considering two types of price spikes (PS) is developed, namely: short-duration and long-duration spikes. To evaluate and examine this model, spike durations of half hour, one hour, and one and half hour were simulated to determine TEC. This proposed schema also examines how the control system applies a pre-cooling method if there is a substantial risk of PS. The results present possible savings on the electrical energy consumption when the consumer applies this method to anticipate spike events. This model is tested considering the demand and market price curves of electricity in South Sulawesi, which were published by the Indonesian State Electricity Company (called PLN=Perusahaan Listrik Negara) and the value of Tout in the Makassar area. • The air conditioner is a key driver of the growing energy consumption and electricity demands. • Consumer can estimate the total expected cost for any temperature. • A pre-cooling method was applied if there is a substantial risk of price spike. • Possible saving by consumer if applied this method to anticipate spike events. [ABSTRACT FROM AUTHOR]

Abstract: Many control solutions are currently available for controlling energy system operations. Newly developed solutions for established systems are assumed to demonstrate improvement over previous solutions especially in cost savings. We have found this to be true in the area of HVAC (heating, ventilation, and air conditioning) systems. This paper provides a useful methodology for quantitative comparison of control solutions with respect to operational costs, achieved quality of control, and external conditions that could also play important roles. [Copyright &y& Elsevier]

Abstract: The Information and Communication Technology industry has gone in the recent years through a dramatic expansion, driven by many new online (local and remote) applications and services. Such growth has obviously triggered an equally remarkable growth in energy consumption by data centers, which require huge amounts of power not only for IT devices, but also for power distribution units and for air-conditioning systems needed to cool the IT equipment. This paper is dedicated to the economic and energy performance assessment of a cogeneration system based on a natural gas membrane steam reformer producing a pure hydrogen flow for electric power generation in a polymer electrolyte membrane fuel cell. Heat is recovered from both the reforming unit and the fuel cell in order to supply the needs of an office building located near the data center. In this case, the cooling energy needs of the data center are covered by means of a vapor-compression chiller equipped with a free-cooling unit. Since the fuel cell’s output is direct current rather than alternate current, the possibility of further improving data centers’ energy efficiency adopting DC-powered data center equipment is also discussed. [Copyright &y& Elsevier]

Abstract: Terminal load distribution and pipe network structure are the key factors that affect the energy-saving potential of central air-conditioning chilled water systems, nonlinear thermodynamic performance of an air-conditioning system with large inertia will mainly exert influence on the stability and reliability of energy-saving operation control. Unreasonable variable flow control strategy can neither achieve an ideal energy-saving effect nor meet the air-conditioning comfortableness requirements. With a direct-return chilled water system as study object, this paper built a hydraulic calculation model of pipe network topology, bypass loop hydraulic calculation model, AHU thermodynamic model, and water pump variable frequency operation model. Operating frequency of a water pump for different flow ratio, pump power, temperature difference of pipe network supply and return water, pressure difference of pipe network supply and return water, bypass control valve characteristics, system adjustability coefficient, and pipe network resistance characteristics of a chilled water system are studied under the condition of given supply water temperature, and pipe network’s AHU node thermal and humid load. And energy consumption characteristics of constant temperature difference control and variable temperature difference control are also analyzed with comparison. The results can provide theoretical guidance for the stable and reliable energy-saving operation of a chilled water system. [Copyright &y& Elsevier]

Abstract: This paper provides a comparative study of the performance of cross-flow and counter-flow M-cycle heat exchangers for dew point cooling. It is recognised that evaporative cooling systems offer a low energy alternative to conventional air conditioning units. Recently emerged dew point cooling, as the renovated evaporative cooling configuration, is claimed to have much higher cooling output over the conventional evaporative modes owing to use of the M-cycle heat exchangers. Cross-flow and counter-flow heat exchangers, as the available structures for M-cycle dew point cooling processing, were theoretically and experimentally investigated to identify the difference in cooling effectiveness of both under the parallel structural/operational conditions, optimise the geometrical sizes of the exchangers and suggest their favourite operational conditions. Through development of a dedicated computer model and case-by-case experimental testing and validation, a parametric study of the cooling performance of the counter-flow and cross-flow heat exchangers was carried out. The results showed the counter-flow exchanger offered greater (around 20% higher) cooling capacity, as well as greater (15%–23% higher) dew-point and wet-bulb effectiveness when equal in physical size and under the same operating conditions. The cross-flow system, however, had a greater (10% higher) Energy Efficiency (COP). As the increased cooling effectiveness will lead to reduced air volume flow rate, smaller system size and lower cost, whilst the size and cost are the inherent barriers for use of dew point cooling as the alternation of the conventional cooling systems, the counter-flow system is considered to offer practical advantages over the cross-flow system that would aid the uptake of this low energy cooling alternative. In line with increased global demand for energy in cooling of building, largely by economic booming of emerging developing nations and recognised global warming, the research results will be of significant importance in terms of promoting deployment of the low energy dew point cooling system, helping reduction of energy use in cooling of buildings and cut of the associated carbon emission. [Copyright &y& Elsevier]

Abstract: A data-driven approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system in an office building is presented. A neural network (NN) algorithm is used to build a predictive model since it outperformed five other algorithms investigated in this paper. The NN-derived predictive model is then optimized with a strength multi-objective particle-swarm optimization (S-MOPSO) algorithm. The relationship between energy consumption and thermal comfort measured with temperature and humidity is discussed. The control settings derived from optimization of the model minimize energy consumption while maintaining thermal comfort at an acceptable level. The solutions derived by the S-MOPSO algorithm point to a large number of control alternatives for an HVAC system, representing a range of trade-offs between thermal comfort and energy consumption. [Copyright &y& Elsevier]

Abstract: Biogas engine-driven heat pump air conditioner is a new-style system which includes biogas engine-driven heat pump, primary heat exchanger, second heat exchanger, sprayed room and fans, pumps, etc. In summertime, the air can be reheated by the waste heat water from the biogas engine in the system, while the air can be reheated and humidified by the waste heat water in winter. Reducing or displacing electrical heating requirements can achieve the great opportunity for significant energy savings. This paper, therefore, aims to improve the energy performance of the AC system by using the waste heat from the biogas engine. The mathematic model was used to research the BHPAC. Explicitly, we investigated the influence of various factors including the outdoor air temperature and humidity in summer and winter. Results show that the biogas engine-driven heat pump air conditioner can save more energy than the electrical power heat pump. In summer, the minimum for percentage of primary energy saving for BHPAC is over 25%. With the outdoor air dry-bulb temperature and the relative humidity rises, the saving energy percentage rises. In winter, the minimum for percentage of primary energy saving for BHPAC is 37%. The more the outdoor air relative humidity of the outdoor air decreases, the more the BHPAC saves energy. It is proved that the system which is a highly actively fully utilizing energy technology has good partial load characteristic and good effects of energy saving. [ABSTRACT FROM AUTHOR]

Abstract: Cooling load calculations are essential in sizing air conditioning system equipment. In designing energy, efficient and renewable energy sourced cooling systems for buildings, it is important to have the exact values of cooling loads and seasonal cooling demands of buildings. In this paper new assessment method for more precise determining of cooling loads and seasonal cooling demands of residential buildings are developed, which are necessary for right solutions of cooling efficiency problems. Comparing to the method of ASHRAE, example and other methods it provides more correct results. Application of suggested method provides better accuracy in assessment of cooling loads especially for seasonal aspects, as they take into account the impact of more factors. [ABSTRACT FROM AUTHOR]

Abstract: Integration of the heat pipe with an ejector will result in a compact and high performance system. The concept of the heat pipe/ejector refrigeration cycle is discussed, in this paper. The needed driving capillary forces are firmly established. The basic characteristics of the system, such as entrainment ratio, coefficient of performance, exergy efficiency and thermal efficiency of the system are evaluated. Also, the zero-dimensional constant pressure mixing theory is applied to ejector. In this study, water is used as the working fluid. Whenever the mixed flow is supersonic, a normal shockwave is assumed to occur upstream of diffuser inlet. The simulation results indicate that, the coefficient of performance can reach about 0.30 at T e =10°C, T c =30°C and T g =100°C. Also, the second law efficiency of the heat pipe/ejector refrigeration cycle increases with increasing evaporator temperature and decreasing condenser temperature. It is seen that, the maximum heat pipe cooling capacity obtains for large heat pipe diameters, near the small heat pipe lengths. It has proven that, this refrigeration system can be widely used in many areas, especially in renewable energy utilization such as solar energy. [Copyright &y& Elsevier]

Abstract: This paper gives a concise review of new designs and developments of illumination, heating and air-conditioning systems and technologies for energy-efficient buildings. Important breakthroughs in these areas include high-efficiency and/or reduced cost solar system components, LED lamps, smart windows, computer-controlled illumination systems, compact combined heat-power generation systems, and so on. To take advantage of these new technologies, hybrid or cascade energy systems have been proposed and/or investigated. A survey of innovative architectural and building envelope designs that have the potential to considerably reduce the illumination and heating and cooling costs for office buildings and residential houses is also included in the review. In addition, new designs and ideas that can be easily implemented to improve the energy efficiency and/or reduce greenhouse gas emissions and environmental impacts of new or existing buildings are proposed and discussed. [Copyright &y& Elsevier]

Abstract: This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme/model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005 〈www.archenergy.com〉]. Energy savings up to 30.4% were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied. [Copyright &y& Elsevier]

With the announced plans to ban diesel in major European cities from 2025, battery-powered electric buses (BEB) are attracting attention to replace diesel fleets, given their zero tailpipe emissions. However, their large-scale deployment faces several challenges, namely the limited driving range (DR) and the need for adequate charging infrastructure. The limited DR is due to the lower battery specific energy compared to oil-based fuels. Also, the use of electric auxiliaries, especially, air conditioning, reduces the DR further. The DR problem could be resolved either by increasing the battery capacity, which increases the bus cost or by rightsizing the battery alongside an adequate charging strategy to avoid schedule disruption. Therefore, this paper presents a comprehensive energy modeling of a BEB using Dymola, encompassing the different energy systems encountered in BEB. The proposed model serves as a platform to evaluate the bus energy needs during its service to properly size the battery. A powertrain model is presented to emulate the propulsion load. Then, a cabin model alongside a heating ventilating and air conditioning system are developed emulating the thermal load. Finally, auxiliaries necessary for the bus operation are modeled. The energy consumption of each system is assessed under several operating conditions. Image 1 • Study proposes a modeling methodology to assess battery electric buses energy consumption. • Assesses the impact of different driving and weather conditions and passengers load on the energy consumption. • Model serves as a platform to evaluate battery electric buses energy needs to properly size the battery. • Cabin thermal needs and auxiliaries reduce driving range by more than 50% under extreme weather and driving conditions. [ABSTRACT FROM AUTHOR]

Many technical solutions have been developed to reduce buildings' energy consumption, but limited efforts have been made to adequately address the role or action of building occupants in this process. Our earlier investigations have shown that occupants play a significant role in buildings' energy consumption: It was shown that savings of up to 20% could be achieved by modifying occupant behavior thorough direct feedback and recommendations. Studying the role of occupants in building energy consumption requires an understanding of the interrelationships between climatic conditions; building characteristics; and building services and operation. This paper describes the development of a systematic procedure to provide building occupants with direct feedback and recommendations to help them take appropriate action to reduce building energy consumption. The procedure is geared toward developing a Reference Building (RB) (an energy-efficient building) for a specific given building. The RB is then compared against its given building to inform the occupants of the given building how they are using end-use loads and how they can improve them. The RB is generated using a data-mining approach, which involves clustering analysis and neural networks. The framework is based on clustering similar buildings by effects unrelated to occupant behavior. The buildings are then grouped based on their energy consumption, and those with lower consumption are combined to generate the RB. Performance evaluation is determined by comparison of a given building with an RB. This comparison provides feedback that can lead occupants to take appropriate measures (e.g., turning off unnecessary lights or heating, ventilation, and air conditioning (HVAC), etc.) to improve building energy performance. More accurate, scalable, and realistic results are achiveable through current methodology which is shown through comparison with existing literature. • A model is developed to create a reference building to evaluate the energy saving opportunities. • Developed data mining framework is applied and validated on a set of 76 buildings. • The methodology provides the occupants with insights regarding their energy savings. • The framework is generic and can be applied to a wide range of buildings. [ABSTRACT FROM AUTHOR]