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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]

• A two-step framework for grey-box modeling of building thermal dynamics. • Parameter identification under fluctuating data from direct expansion system. • Determined optimal complexity and data frequency in case study. • New evaluation metric that considers accumulated energy value for load prediction. Thermal dynamics model plays a crucial role of advanced control in the intelligent building. Grey box method is widely used in the modeling of building thermal dynamics based on the operation data of air-conditioner. The performance of direct-expansion (DX) system fluctuated severely during its operation, which leads to the difficulties in identification and evaluation of the building thermal model. In this paper, a two-step identification framework for second-order thermal resistance-capacity network of building based on DX system data is proposed. A case study is conducted on an office building equipped with variable refrigerant flow system in Foshan, China. The results show that the proposed framework can identify the parameters rationally. The model achieves high accuracy for both indoor temperature (Mean absolute errors of 0.74°C) and cooling load prediction (Mean absolute errors of 4453.86W) in a short time interval of 10 minutes. Additionally, the best complexity of the grey-box model for case building and the data acquisition interval is determined. Finally, an improved set of evaluation metrics for thermal load evaluation is proposed and discussed. [ABSTRACT FROM AUTHOR]

In this paper, numerical simulations of Diffusion Absorption Refrigeration – DAR cycle were conducted in order to study the performance of two configurations in steady state mode and use ammonia, water, hydrogen as working fluids. The two configurations were numerically simulated using models developed with the commercial flow sheet Aspen HYSYS V10 software. The first configuration where the main simple DAR cycle components were simulated and validated the experimental results. The second configuration where the modified DAR cycle was simulated which has an auxiliary heat exchanger added to the main simple DAR cycle as a modification. It was found that for the same input assumptions and heat applied, the modified DAR cycle shows higher cooling load. Therefore, higher COP than the simple DAR cycle. The optimal operation of the modified cycle is 36 W applied to the generator to achieve a COP of 0.235 instead of 0.209 for simple DAR cycle. The Simulation results show that by using the modified cycle, the COP improves by 12.4%. [ABSTRACT FROM AUTHOR]

• Performance of the ejector refrigerator was studied under different ejector profiles. • Significant performance improvement was achieved when using the CRMC–ejector. • The T chill produced by CRMC–ejector was much lower than CONV–ejector. • The CRMC–ejector produced better performance under various working conditions. • The system COP can be increased by 27–63% via the CRMC–ejector. This paper proposes the performance improvement of the ejector refrigerator based water chiller (ejector-based chiller) by means of using different mixing chamber profiles. Two different ejector mixing chamber profiles are constructed which are based on the conventional method (CONV–ejector) and the constant rate of momentum change method (CRMC–ejector). With the different design methods, the ejectors have different flow areas along the ejector's axis; however, they have identical ejector throat diameters of 9 mm. Both ejectors are equipped with two primary nozzles, and hence, they have the same ejector area ratio of 6.3 and 7.9, respectively. The refrigerator is powered by hot water at a temperature of 94–98 °C while the condenser is cooled by cooling water at 29–31 °C. The chilled water temperature (T chill) under various cooling loads and COP is assessed. It is found that the CRMC–ejector produces a much lower chilled water temperature than the CONV–ejector at identical cooling load. The system COP can be increased by 27–63% via the CRMC–ejector. With the change in T hot , both ejectors produce identical T chill ; however, the CRMC–ejector still produces much lower T chill at an identical cooling load. A larger primary nozzle throat yields a higher T chill. [ABSTRACT FROM AUTHOR]

Cooling load characteristics play a key role to the building, especially in self-sustained building. It is determined mainly by the building envelope thermal performance. This research investigates the effect of the building envelope on cooling load in low latitude and hot-humid area. In this paper, based on cooling load simulations, the effect of reducing the cooling load of building envelope and the life cycle cost was analyzed. In addition, the energy-saving system was established. For the life cycle cost analysis, the cost of each strategy was obtained through a survey in local stores. This paper determining the effect of external walls, windows, roof, shading on the building cooling load, and pointed out the optimum insulation thickness of roof and all orientation exterior wall. And the optimum window structure and exterior shading length was give. [ABSTRACT FROM AUTHOR]

Across diverse geographies, mini-grids have been employed to provide energy access to off-grid and rural communities. In India, amid the government push to expand grid infrastructure, concerns have been raised about the viability of mini-grid business models that are largely run by private companies. While the role of mini-grids in previously un-electrified areas has been studied extensively, there exists limited empirical evidence regarding their uptake in grid-connected regions. In this paper, we analyze adoption and use of mini-grids among rural communities living in grid-electrified villages. The findings are based on the primary data of 2648 households and 544 non-farm enterprises from 54 villages in the states of Uttar Pradesh and Bihar in India. Our results suggest that despite the presence of central-grid infrastructure, users adopt mini-grid in regions which lack reliable power supply. The mini-grid uptake was found to be relatively higher among non-farm enterprises, which, unlike households, have not received adequate policy attention and support. However, mini-grids were being used only for meeting basic lighting and cooling loads in most cases, primarily due to affordability concerns. Based on our findings, we argue that grid-interactive mini-grids could be used to serve rural enterprises as they value reliable power supply. Yet, the current low levels of electricity demand among non-farm rural enterprises suggest that growth in electricity demand and in turn enterprise productivity would require complementary services and infrastructure. • Insights from a survey of 54 villages having both central grid and solar mini-grid. • Mini-grid use among non-farm enterprises is significant, but low among rural households. • Lack of reliable grid-power supply in surveyed villages is a key driver of mini-grid use. • Rural enterprises currently have low electricity demand. • Mini-grid connections primarily used to meet basic lighting and cooling energy demand. [ABSTRACT FROM AUTHOR]

Thermal insulation has become essential, firstly to ensure the thermal comfort of the occupants and secondly to save energy and that's why we find more and more varieties of insulators (organic, inorganic and synthetic) in the Moroccan market, depending on the need when to make the right choice. This paper presents the theoretical part of a thermal and an energetic study of the envelop of a house located in the city of Marrakesh (Morocco), by using four types of insulators, that are mostly used in Moroccan markets, for different thicknesses to determine the most suitable insulator for Marrakech climate and its optimal thickness. The insulators studied are: Expanded Polystyrene, glass wool, rock wool and wood fiber. The numerical simulations were realized using the software of thermal dynamic simulation TRNSYS. The results show that for a thickness of 8 cm of the wood fiber insulator saves about 7% for heating and 14% for cooling loads. For temperatures, in January temperatures are higher by 0.26 °C, and in July are lower by 0.49 °C. [ABSTRACT FROM AUTHOR]

• Developed an improved attention-based approach for robust cooling load prediction. • Generated hourly cooling loads under diverse occupancy schedules. • Highlighted the impact of temporal characteristics on prediction performances. • Introduced a time representation learning and attention mechanism to improve accuracy. • Combining XGB to enhance prediction accuracy, robustness, and transparency. Space cooling in buildings is responsible for massive energy consumption and carbon emissions. Accurate cooling load prediction can facilitate the implementation of energy-efficiency cooling control strategies in practice. In this paper, an improved attention-based deep learning approach is proposed for robust ultra-short-term cooling load prediction. First, a novel time representation learning is introduced to extract the periodicity and non-periodicity of cooling loads efficiently. Then, long short-term memory with an attention mechanism extracts properly the time steps by identifying the relevant hidden states and learns high-level temporal dependency. The approach additionally incorporates extreme gradient boosting through the error reciprocal method, enhancing the elimination of prediction errors and improving robustness. The study takes Guangzhou as an example and generates cooling loads using diverse occupancy schedules of five building types based on the Chinese National Standard and Typical Meteorological Year data. The approach is evaluated on datasets comprising the cooling loads, meteorological data, and contextual information. Through results analysis, the approach outperforms other models in terms of prediction accuracy and robustness across all building types. Additionally, model interpretation is provided regarding feature importance and attention matrixes, which enhances the understanding and transparency of the final prediction from the proposed approach. [ABSTRACT FROM AUTHOR]

Indoor occupants have a close connection with the energy consumption of heating, ventilation and air-conditioning (HVAC) in airport terminals which are characterized by passenger flow. In this paper, an on-site survey was performed to investigate movements of passengers and service counters on the departure floor of a Chinese hub airport terminal. The survey results were used as inputs for agent based simulation to figure out the characteristic of passenger flow. Only 3.6% of the occupant density data in simulation exceed their respective design value, which demonstrates that the design occupant density in each area can reveal the actual situation in this airport. However, the uneven occupant distributions both in time and space make the maximum occupancy rates to be only 54.8%–64.4% on the departure floor. Consequently, the maximum actual demand of cooling load for mechanical outdoor air (25 W/m2) is obviously lower than the design value (47 W/m2), which demonstrates a large energy saving potential of HVAC systems in airports by adjusting amount of mechanical outdoor air with variation of actual occupancy rates. • On-site surveys of passenger flow were performed in a hub airport terminal. • Survey results were used as inputs for agent based simulation of passenger flow. • Only 3.6% of the occupant densities in simulation exceed their respective design value. • Uneven occupant distributions result in low occupancy rates of 54.8%–64.4%. • Adjusting mechanical outdoor air with occupancy rates has a large energy saving potential. [ABSTRACT FROM AUTHOR]

Highlights • Train-induced airflow in subway is studied by network simulation and field tests. • Energy performance is analyzed in three different ECSs. • Influence of climate and passenger number on energy consumption is examined. Abstract Environment control systems (ECSs) provides a comfortable environment for the passengers in subway stations, which are classified as platform bailout door (PBD), platform screen door (PSD) and PBD-PSD-combined systems. In this paper, the airflow characteristics and the energy consumption of these ECSs in typical subway stations were studied. Airflow was analyzed by a network simulation method, and the simulation results were verified by field tests. In addition, based on the cooling load calculation and the proposed operation strategy, the equipment opening time and the energy consumption of the three ECSs were analyzed in different climate zones with different operation phases. The results reveal that the PBD-PSD-combined system achieves the best energy performance among the three ECSs; however, the energy saving percentage varies in different situations. Compared to the sub-optimal ECS, the energy saving percentage of the combined system differs from 1% to 8%, while it is only 1% in hot climate zones with high passenger flow. [ABSTRACT FROM AUTHOR]

• Modeling a multi-energy retailer in the framework of multi-carrier energy systems. • Developing a multi-energy retailer based on gas/cooling/heating/power carriers. • Presenting an IGDT method to cope with uncertainties in the optimization model. • Integrating flexible options, e.g. hybrid energy storage in the optimization model. • Proposing integrated DR to control multiple energy demands simultaneously. Multi-energy systems (MESs) were introduced to enhance the flexibility and efficiency of conventional energy distribution systems. In this new trend, it is possible to supply different energy carriers simultaneously by the multi-energy retailer (MER), under which, without the need to transfer all of them to different locations, the loads are fed centrally, and the customers can purchase all the carriers they need from the desired MER. Motivated by these descriptions, this paper focuses on the optimal scheduling of MER in the integrated energy system, including natural gas, electricity, cooling, and heating, under the information gap decision theory (IGDT) framework. The MER's goal is to maximize profits by considering the uncertainty of the day-ahead power market. The proposed IGDT approach without a probabilistic distribution function analyzes the risk-aversion strategy associated with electricity price uncertainty. In this paper, integrated demand response (IDR) for natural gas, electrical, heating, and cooling loads are developed simultaneously as a flexible demand-side management resource. The proposed model contains multiple technologies owned by MER, including hybrid energy storage technology, combined heat and power, chiller, boiler units, and renewable resources. Numerical results from different cases illustrate the effectiveness of IDR installation in terms of profitability. Besides, the MER can serve multiple demands more efficiently. Under the IGDT approach, the purchasing power cost is reduced up to 24.23%. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet communication business, the issues related to the space, efficiency and energy consumption of data center are increasingly attracting more attentions. Because the modular air conditioning system has the advantages of quick construction, easy replication, rapid deployment, flexible scalability, high cooling efficiently, it has become a way to solve the bottleneck problem of traditional data center. In this paper, a data center being equipped with modular air conditioning system in Tianjin is taken as an example to analyze the energy and electricity saving and the characteristics of deployment by steps. The practice of this example shows the feasibility and prospects of applying modular air conditioning system in data center. [ABSTRACT FROM AUTHOR]

The paper presents a relational study of correlating cooling energy use with local weather station and apartment price data in Seoul. The overall analysis at a macro-level shows monthly variations in the correlation coefficients of cooling energy use and local weather station data during summer months. A further analysis at a micro-level shows temporal and spatial variations in the correlation. As the August correlation appears the strongest across all city districts, up to r=0.972, a simple bivariate regression (SBR) model is derived to predict peak cooling energy use for each district. Given the latest climate change projections for Seoul, we use the SBR models to estimate increases of cooling energy use for each city district in August 2050s. The largest predicted increase rate (IR) is 96.1% in one city district (from 124.5% in 2012–220.6% in 2047). The smallest IR is 6.0% in another city district (from 51.5% to 57.5%). In 2047, the city district with the highest predicted IR is up to 292.8%, while the lowest is up to 57.5%. We discuss the implications of the projected future peak cooling energy demands for sustainable resilience as well as citizen's health and wellbeing. [ABSTRACT FROM AUTHOR]

• New comprehensive framework for a CCHP-based MG operation. • New CCP approach for guaranteeing confidence level of the whole system. • Proposing a comparative structure for participating in power and heat markets. • Utilizing multi-carrier storage, hybrid chiller, besides new mathematical for CHP. Microgrids (MGs) have a special role in developing several consumers' energy infrastructure and supply in more economical, safer, and sustainable ways. The interaction and mutual relationship between each energy carrier on the reliable performance of other carriers and the high growth of tri-generation technologies in the MG face the optimal performance of such networks with many challenges. Combined cooling, heating, and power (CCHP)-based MGs are a new generation of MGs that simultaneously provide electrical, thermal, and cooling loads. However, the interaction between these carriers is very influential in CCHP-based MG's operation, which is rarely analyzed. Hence, this paper focuses on the operation of CCHP-based MG coupled with hybrid chiller, multi-energy storage, solar and wind power, etc., under the chance-constrained programming (CCP) approach by considering the mutual relationship between carriers. While modeling consumption and wind and solar energies fluctuations, the proposed approach analyzes the violation of the balance constraint for each carrier and subject it to guarantee the corresponding confidence level. Therefore, the degree of dependence of the system on each carrier and the mutual relationship between carriers are analyzed in this work. This paper also presents a new incentive framework for participating in the electricity and heating markets for the system. The proposed model is implemented on the test system, and the results are discussed for different cases for several confidence levels. The results illustrate the importance of the electricity carrier confidence level on the safe performance of the whole system compared to other carriers. Only by increasing the operation cost of the electricity sector by 4.3%, the system's reliable performance is guaranteed with a probability of 98%. [ABSTRACT FROM AUTHOR]

Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry have been developed from either forward or inverse modeling approaches. However, these models usually require extensive computer resources and lengthy computation. This paper discusses the use of the multi-layer perceptron (MLP) model, one of the artificial neural network (ANN) models widely adopted in engineering applications, to estimate the cooling load of a building. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing prestigious commercial building in Hong Kong that houses a mega complex and operates 24h a day. The paper also discusses the practical difficulties encountered in acquiring building-related data. In contrast to other studies that use ANN models to predict building cooling load, this paper includes the building occupancy rate as one of the input parameters used to determine building cooling load. The results demonstrate that the building occupancy rate plays a critical role in building cooling load prediction and significantly improves predictive accuracy. [Copyright &y& Elsevier]

The next generation radar suite will include a radar that has sensitivity far greater than shipboard radars in use today. Most likely the radar will be a multi-faced, solid state, phased array system with each array consisting of thousands of individual radiating elements powered by transmit/receive (T/R) modules. It will likely need to be large, and the demands it makes on ship services will be unprecedented. Its electrical power demands could be larger than the total ship's load for present-day ships. Array size could significantly impact topside design. This paper examines top-level radar system design choices and illustrates the trends in the ship impact of those choices. Radar design options considered are aperture size and shape, coolant operating temperature, number of array faces, and power system architecture. These design options have an effect on the radar system's weight, footprint, power demand, and cooling load. The effects on ship design can be significant. The ship impact analyses consider a radar system that includes ship-provided equipment such as electrical power distribution equipment and chill water plants. An analysis of radar systems, all with the same performance, shows that radar system power demand can change by as much as four megawatts for a notional surface combatant depending upon the radar designer's configuration choices. Radar system weight can vary by more than 100 metric tons. There is a cubic relationship between T/R module power and array face area for a constant sensitivity radar system. This relationship is examined to show that there is often a choice of T/R module power that minimizes radar ship impact. The exact choice of T/R module power depends upon the customer's preferences, the manufacturer's capabilities, and choice of vendors. This paper does not convey any official US government position or US Navy endorsement of any particular radar architecture or design approach. [ABSTRACT FROM AUTHOR]

Abstract: Air-cooled centrifugal chillers are commonly used in commercial buildings but their performance analysis is lacking. This paper investigates the part load performance of the chillers via a thermodynamic model. The model was validated using a wide range of operating data from an existing chiller with specific settings of outdoor temperature and condensing pressure in controlling the condensing temperature. The validated model was developed specifically to ascertain the maximum coefficient of performance of chiller (COP) together with the strategy for optimizing the condensing temperature under various operating conditions. It is found that the highest COP occurs at a part load ratio (PLR) of 0.71–0.84, depending on the outdoor temperature and the control of condensing temperature, rather than at full load. Yet the chillers operating at such part load conditions will cause extra energy used for the early staging of chilled water pumps. To minimize the overall chiller plant energy consumption, it is still preferable to implement chiller sequencing based on the full load condition than on the aforementioned PLRs. The results of this paper present criteria for implementing low-energy strategies for operating air-cooled chillers satisfying a given building cooling load profile. [Copyright &y& Elsevier]

The integration of passive features during the design/construction of sustainable buildings requires thorough modelling at the design stage as some features may have unintended consequences resulting in occupant dissatisfaction, and resulting in the building using more energy to maintain comfort. This paper reports the outcome of an investigation into the thermal performance of a recently built ‘sustainable science building’ in a school located in South Australia. The building consists of a 115 m 2 atrium which is naturally ventilated by a solar chimney integrated into a high pitch roof with low level and celestial window openings at the outlet of the chimney. The experiment was undertaken in January to monitor the airflow pattern and air temperatures at different location of the atrium. A mathematical model was used to predict the performance for comparison with experimental data. At some hours, it was observed that flow reversal in the chimney led to unwanted hot air entering into the building thus increasing the building cooling load. The model was able to predict the flow reversal at those times. The use of such a model at the design stage can help develop an improved chimney design which avoids the undesired flow reversal and demonstrates the potential value of modelling of passive features before construction. [ABSTRACT FROM AUTHOR]

Data centers are amongst the most complex and energy demanding building environments. The trends of increasing data center capacity and power use by information technology equipment, re-emphasize the need to reduce cooling loads, first cost for HVAC equipment, and finally related energy and operational costs. The first part of the paper presents an overview of relevant information and available resources for the efficient design and operation of these critical environments. The second part considers two large data centers located in Athens that serve two major Hellenic banks as case studies in order to investigate and quantify the potential measures for improving their energy performance. The two facilities were audited and actual energy consumption were used for an energy assessment. According to simulation results of various efficiency measures, the Power Usage Effectiveness may be improved from 2.49 to 2.11 for the first case study and from 1.89 to 1.66 for the second one. [ABSTRACT FROM AUTHOR]

Global warming and the urban heat island effect have led to the deterioration of the outdoor thermal environment and the rise of building cooling demand, calling for urban design with high environmental quality. However, little has been changed in the practice of urban street design. This paper bridges this gap by developing a framework of parametric simulation for design guidance of urban streets with an advanced urban canopy model that can simulate the interactive indoor-outdoor environment. Case studies are conducted at the neighborhood scale for six cities to improve outdoor thermal comfort and building energy efficiency in summer. The influence of street and building design parameters has been investigated based on 31104 simulations. Results reveal the conflict between optimizing outdoor thermal comfort and optimizing building energy efficiency. In the majority of the investigated cities, window-to-wall ratio, window type, and street orientation are the most influential parameters. Strategies by adjusting these parameters can significantly improve outdoor thermal comfort, as quantified by thermal stress hours, at a cost of increasing the building cooling load. Planting bigger and denser roadside trees always moderately reduces the thermal stress hours and building cooling load. These results demonstrate the potential of this framework to identify the design trade-offs between thermal comfort and building energy efficiency. The framework can be extended to various cities to help designers and policymakers at the early design stage. • A framework to explore early design guidance for urban streets is developed. • A total of 31104 design scenarios are performed for six cities in southern China. • Window-to-wall ratio, window type, and street orientation are most influential factors. • Pareto optimal solutions for outdoor thermal comfort and building energy are revealed. [ABSTRACT FROM AUTHOR]

In this paper, a solar liquid desiccant air conditioning (SLDAC) system has been studied. The effect of changing evacuated tube collector area on the performance of the SLDAC system was fulfillment. This inquest was done over all a year in Borg Al-Arab city located in the Northern region of Egypt. Meteorological data, such as hourly average solar radiations and temperatures, were needed to achieve this research. The hourly cooling loads were determined by using Hourly Analysis Program (HAP) 4.7. These loads are wall, illumination, people, and equipment loads. Then, the hourly differences of different parameters such as amount of water absorbed in conditioner, amount of water desorbed in regenerator, hot water temperature and coefficient of the performance were calculated. In addition, the maximum solar thermal energy was determined to meet the regeneration demand according to the hourly average solar radiation data. For 220 m 2 evacuated tube collector area, the maximum required heat energy is obtained as 38,286 kW h on December, while using solar energy, will save energy by 30.28% annual value. [ABSTRACT FROM AUTHOR]

In the office buildings, large energy is consumed due to poor thermal performance and low efficiencies of HVAC systems. A cooling load calculation is a basis for the design of building cooling systems. The current design methods are usually based on deterministic cooling loads, which are obtained by using design parameters. However, these parameters contain uncertainties, and they will be different from that used in the design calculation when the cooling system is put in use. The actual cooling load profile will deviate from that predicted in design. A modified bin method was used in this paper to optimize the energy efficiency ratio (EER). A design optimization method is proposed by considering uncertainties related to the cooling load calculation. Impacts caused by the uncertainties of seven factors are considered, including the outdoor weather conditions and internal heat sources. The cooling load distribution is analyzed. Comparison between the modified bin method and CLTD/SCL/CLF method is also conducted. With the distributions of their energy consumption, decision makers can select the optimal configuration based on quantified confidence. According to the economic benefits and energy efficiency ratio, using modified bin method will increase the overall energy efficiency ratio by 45.57%. [ABSTRACT FROM AUTHOR]

People spend about one third of their lives sleeping. Sleep is essential for the recovery of the body from both physical and psychological fatigue suffered throughout the day, the refreshment of mind, and the restoration of energy for maintenance of bodily functions. Current thermal comfort theories and standards are mainly concerned with people in waking state. However, many problems regarding thermal environment are found within a few field surveys in bedrooms, pushing out the need to investigate thermal environment and thermal comfort for sleeping people. In this paper, the questions concerning the measurement and evaluation of human sleep quality, the correlation between thermal regulation system and sleep regulation, and the characteristics of night-time space cooling load etc. are answered. The evidences illustrating the effects of thermal parameters on human sleep quality are also provided, in an attempt to shed light on the thermal comfort requirements of sleeping people. [ABSTRACT FROM AUTHOR]

For the better operation of air-conditioning systems and the improvement of office building thermal environment, internal heat loads resulting from occupants, equipment, and lightings need to be accurately quantified because they are main components of space cooling loads. However, existing methods are hard to describe the complicated variation characteristics of internal cooling loads and time lag effect of conversion processes between electric energy and internal cooling loads, leading to limited application and unstable accuracy. To tackle this problem, in this study, transfer function models for instantaneous internal cooling loads were firstly established. Second, an experiment was conducted based on a chamber with good insulation. Third, experimental data and radiant time factors were employed in model discretization, parameter identification, and order decrease steps to acquire unknown parameters and develop models as second-order and third-order discrete transfer functions. Fourth, a simulation was conducted to validate the models, and a mean absolute percentage error of 8.08% was attained. Finally, a comparison between proposed and previously developed methods was carried out to evaluate model performance. The proposed models achieved a maximum internal cooling loads reduction of 75.57%, and the maximum time lag resulting from the heat storage characteristics of indoor thermal masses was approximately 30 min. With two easily accessible input parameters, the proposed models exhibited promising applicability and feasibility during the real-time operation of buildings. This paper provides a theoretical basis for accurately obtaining instantaneous internal cooling loads and thus is meaningful in improving building thermal environment and enhancing comfort levels. • Transfer function models for acquiring instantaneous internal cooling load were developed. • With two accessible input parameters, proposed models were applicable to the operation of office buildings. • Compared with previous methods, a maximum decrease in errors of 75.57% was obtained after adopting the proposed models. • This study facilitated the description of time lag effect of conversion processes between electric energy and internal cooling loads. [ABSTRACT FROM AUTHOR]

• Methodology combining simulation and clustering with multi-criteria decision-making. • Load dominance rates and ternary diagrams are proposed to analyze the impact of load size. • New insights regarding the conditions that promote economic benefits when using CCHP-TS systems. • Depending on the SS rate, a dominance or equilibrium of loads influence the percentage of savings obtained. Trigeneration systems with Thermal storage (CCHP-TS) allow a distributed generation of energy. They also contribute to reducing greenhouse gas emissions by producing electricity, heating, and cooling from the same fuel. Current research targets their operational performance and feasibility. Nevertheless, expressing these concepts into standard criteria could foster their adoption by investors and policy-makers. This paper finds some rules of thumb for the technical and economic feasibility of CCHP-TS systems. The analysis comprises 600 scenarios, assessing the impact of different levels of spark spread (SS) rate and load size of Electricity, Heating, and Cooling. The methodology first optimizes the energy system with DER-CAM and after analyzes the output data through the clustering method k-means and the Multi-Criteria Decision-Making method ELECTRE 1S. Moreover, the paper proposes the dominance load rates to quantify the relative size of electricity, heating and cooling loads. The results show that for high SS rates, the percentage of savings improves with the dominance of electric loads. While for small SS rates, the improvement comes from the equilibrium of loads. Furthermore, for any SS, a high dominance of electricity promotes the use of Absorption and Cooling Storage, reducing the Heat Scrap. [ABSTRACT FROM AUTHOR]

• Technical-economic analysis of the combined cooling, heating, power, fresh water and hydrogen generation system (CCHPWH) are presented. • Optimization of the studied system was used by the genetic algorithm to obtain the minimum total annual cost (TAC). • CCHPWH system by the prime mover of gas engine has 10% lesser TAC than the system by the prime mover of gas turbine. • Exergy efficiency of the cogeneration system in the optimal state for the prime mover of the gas turbine and the gas engine was 31.21 and 45.58%. Multi-generation plant is a decentralized, energy-efficient method of different type of energy production. Such a system can deliver multiple benefits and advantages compared to conventional energy production such as improvement in the efficiency, emission, cost and reliability. Technical-economic analysis of the combined cooling, heating, power, freshwater and hydrogen generation system (CCHPWH) are presented in this paper. Selecting the nominal power of prime movers, their numbers, the cooling capacity of absorption and electrical chillers, the heating capacity of auxiliary boiler, electric cooling ratio (the ratio of electrical chiller capacity to the cooling load demand), motive steam pressure, number of effects, motive steam flow rate, feed flow rate and 24 partial loads for the prime mover during in the year are considered as 35 design parameters. The optimization of the studied system was used by the genetic algorithm to obtain the minimum total annual cost (TAC) as an objective function. The total annual cost includes economic, energy and environmental parameters. It should be noted that selling/buying electricity to/from the grid is allowable in this study. The optimum results showed 24.8% reduction in the total annual cost of the CCHPWH system using a gas engine as prime mover as compared with a gas turbine. In addition, the exergy efficiency of the cogeneration system in the optimal state for the prime mover of the gas turbine and the gas engine was obtained 31.21% and 45.58%, respectively. Finally, the optimal results in different cases were compared and results were discussed. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, the application of smart glazing systems as shading devices is evaluated for US residential buildings. Specifically, static and dynamic overhangs are considered using smart glazing that can change their tint state to reduce the heating and cooling thermal loads for prototypical housing units in high-rise apartment buildings. The tint settings as well as the overhang tilt angles are specified on hourly, daily, and monthly basis depending on the window orientation and the time of the year to minimize the annual energy demand for the housing units. The performance of smart glazed overhang systems is compared to both static and dynamic shading devices made-up of conventional opaque materials. In addition, the impacts of various design and climatic conditions are considered to assess the energy performance of the smart glazed overhangs. The results of the analysis indicate that the annual energy consumption for existing housing units with conventional windows located in Boulder, CO, can be reduced by over 7% for static smart glazed overhangs and by over 22% for dynamic smart glazed overhangs. These savings are even higher with larger windows and wider differentials between optical properties between clear and dark states. The smart glazed overhangs allow the use of low-cost smart glazing as a retrofit measure for existing buildings. Moreover, the smart glazed overhangs allow the specification of large windows for new constructions with limited energy penalties. • The energy performance of smart glazed overhangs is investigated for housing units. • Optimal controls are used to maximize the energy efficiency of the smart shades. • Switching of smart shades can be optimized on hourly, daily, or monthly basis. • Smart shades reduce energy demand up to 22% compared to unshaded clear low-E glazing. [ABSTRACT FROM AUTHOR]

A model of a quantum harmonic oscillator Carnot refrigerator with heat resistance, internal irreversibility and heat leakage is established in this paper. Based on the quantum master equation and semigroup approach, equations of some important performance parameters, such as cooling load, coefficient of performance (COP), exergy output rate, entropy generation rate and ecological function (a criterion E = A/τ-T0σ representing the optimal compromise between exergy output rate A/τ and exergy loss rate T0σ), for the irreversible quantum Carnot refrigerator are derived. The optimal ecological performance of the refrigerator at high temperature limit is analysed using numerical examples. The effects of internal irreversibility and heat leakage on the optimal ecological performance are discussed. Performance comparisons of the quantum refrigerator under maximum ecological function, maximum COP and maximum cooling load conditions are also performed. Some special cases, i.e. endoreversible, frictionless and without heat leakage, are discussed. Taking ecological optimisation criterion as the objective makes larger improvement of the COP and the reduction in the exergy loss rate at the cost of smaller cooling load drop. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to use detailed modelling techniques and develop a database for assessing in a quick and easy way the energy performance of green roof designs across a range of Chinese climates. The focus is on heating and cooling loads by calculating indoor temperatures using the EnergyPlus simulation tool. The study covers 5328 configurations by varying model parameters such as location, climate, seasonal periods, glazing type, wall insulation levels, roof insulation, soil thickness and condition, and vegetation density characteristics. It was found from the results that green roofs can offer significant energy savings for heating and cooling loads if they are applied on roofs without insulation but only limited energy savings where heavy insulation on the roof is also applied. This database can prove to be a useful tool to the practitioners who want to perform rapid assessments of the potential energy savings that could be gained from a green roof installation in a Chinese location. [Copyright &y& Elsevier]

Abstract: Presently, a green building concept is the design trend for new building. The Shading Device Integrated Photovoltaic system (SIPV) is one option can be applied for building energy conservation. Although, SIPV has some weakness when a building creates the shadow on SIPV by the sun ray projection. Nevertheless, SIPV operation has many benefits that are reduction and compensation the cooling load of air condition system that it follow from building code as OTTV indicator. Furthermore, Design can avoid a high performance glass window that is an expensive material. Therefore, the aim of this paper is to evaluate the annual energy yield per square meter of SIPV of the different slopes and directions of SIPV installation and different types of PV module as used for SIPV was compared. The evaluated location refers to building in Bangkok as 14o North latitude. The results shown that SIPV produces maximum energy yield when the slope nearly 120o on South, Southeast or Southwest direction, which is installed on the exterior wall that has the diffuse reflectance value approximately 30% like a rough semi-glossy surface. Amorphus Silicon and Polycrystalline Silicon technology produces the annual energy yield is 84 and 149 kWh/m2-Year respectively. Which replaces absolutely the cooling load from the glass area is 0.85 and 1.51 m2 respectively. [Copyright &y& Elsevier]

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• A NILM method of cooling load is proposed for smart buildings based on random forest. • Total cooling load is disaggregated into four sub-loads for building/HVAC optimization. • Two approaches are used depending on the availability of weather data. • The proposed NILM methods can realize load disaggregation accurately. Accurate load monitoring can provide detailed information for users to improve the energy efficiency of buildings. Non-intrusive load monitoring (NILM) has become popular in smart buildings because of its low cost and reasonable privacy. In this paper, a non-intrusive monitoring method for the cooling load of smart buildings is proposed based on random forest. The total building cooling load is disaggregated into four subloads, and two approaches are used to realize the NILM based on the direct or indirect cooling load using a Fourier transform. The proposed method is implemented in an office building, and results show the method can realize cooling load disaggregation accurately. The root-mean-square errors and mean relative errors of the four subloads between the NILM loads and reference loads are less than 51.9 kW and 19.1%. Among the four subloads, the equipment load can be disaggregated with the highest accuracy. Approach I is recommended because of its higher accuracy. The NILM method is optimized in terms of the estimator number, maximum depth, feature number, minimum samples for a split, minimum sample leaf, and size of training samples. The performance of the optimized NILM models is improved with RMSEs and MREs less than 48.3 kW and 6.4%. [ABSTRACT FROM AUTHOR]

A heat transfer model with a complex exponent between a thermoacoustic cooler and its surrounding heat reservoirs is established in the current paper. Both the real part and the imaginary part of the heat transfer exponent strongly affect the optimal performance of the cooler. The exergetic efficiency and the cooling load decrease with an increase in the imaginary part of the complex exponent when the real part is fixed. The optimal performance zone of the thermoacoustic cooler is obtained by numerical analysis. The results obtained herein may be useful for the selection of operation parameters for a real thermoacoustic cooler. [ABSTRACT FROM AUTHOR]

This paper presents the performance research of a hybrid air conditioning system (System II) equipped with novel dew point evaporative cooler (DPIEC) for a retail building located in temperate climatic conditions. The new cooler has a dedicated, adaptable structure that maximizes its performance in the climate conditions of central Europe. The unit can operate as a typical regenerative air cooler when outdoor air is drier than indoor air, it can operate as a counter-flow heat recovery unit when indoor conditions are more dry than outdoor and it can operate as a combination of both arrangements. The year-round, hourly-stepped building energy simulations were carried-out using a prognostic tool of energy consumption. The novel dew point evaporative cooler application potential was established using the black-box model based on regression equations was established based on experimental tests on a prototype of novel DPIEC. The hybrid system operation was compared to the typical air handling unit equipped with a standard energy wheel for heat recovery (System I). Presented research shows that DPIEC can cover about 95% of total cooling loads while the energy wheel covers only 9% of total cooling load. System II allows us to save 65% of seasonal electricity consumption comparing to System I. It comes from the fact that during most of the cooling season DPIEC is in operation and it covers most of the cooling loads without the need to switch the chilled water system. • Article presents performance analysis of a novel evaporative air cooler. • Cooler performance was evaluated through building simulation tools. • A comparison between new unit and traditional system was presented. • The unit was proven to achieve significant energy savings. [ABSTRACT FROM AUTHOR]

Due to the increase in cooling load globally, it needs to find an efficient, environment-friendly and sustainable cooling technology. The regenerative evaporative cooler is a better option in this direction. The regenerative evaporative cooler can be possible in different configurations depending on the primary air, secondary air and water flow directions, and it is required to select a thermodynamically, economically and environmentally best sustainable configuration. Hence, this paper numerically simulates exergy, economic and environmental parameters of regenerative evaporative cooler using the generalized model. All possible configurations of the regenerative evaporative cooler are compared based on exergy destruction, exergy efficiency, specific total cost, CO 2 emission and sustainability index. The effect of the geometric and operating parameters on the performance of all configurations is investigated. The analysis concluded that lower channel gap, extraction ratio and air flow rate improve exergetic efficiency and sustainability index and reduce CO 2 emission. Within studied configurations of the regenerative evaporative cooler, A and H are best in terms of higher exergy efficiency, lower specific total cost and higher sustainability index. • Eight regenerative evaporative cooling device topologies are compared in this study. • Simulation of all proposed configurations is done using unified numerical model. • Exergy efficiency, CO 2 emission, specific cost and sustainability index are evaluated. • Effects of various geometrical and operational parameters are investigated. • Configurations A and H are best in terms of exergy, cost and sustainability parameters. [ABSTRACT FROM AUTHOR]

• An AWHP based combined cooling and desalination system is proposed. • Low-grade waste heat is recovered from AWHP to be used for desalination step. • A bio-fueled combined cycle is used for powering both AWHP and hospital equipment. • Use of biofuel and air to water heat pump leads to a significant reduction in CO footprints. • Sensitivity of GOR to dehumidifier/humidifier effectiveness, air humidity, top/bottom temperature is analyzed. This paper presents a trigeneration facility based on a biogas driven gas turbine cycle for electricity production and an air to water heat pump for simultaneous extraction of cooling and potable water, and evaluates its robustness and effectiveness under different climatic conditions and variable demands. The air to water heat pump, which consists of an inside evaporator fan, expansion device, condenser, evaporator, and a compressor, is installed for supplying the cooling load of a hospital building in summer. In the refrigeration cycle, R134a absorbs heat from the inside warm air for space cooling and releases it to the saline water for driving a desalination process. Maximum values of cooling and electrical demands of a standard hospital building, where is located in south of Iran, over the hottest day of 2018 are considered for the worst case implementation. Engineering equation solver and general algebraic mathematical modeling system are employed to develop the non-linear optimization strategy, find the best operating point of the air to water heat pump based trigeneration plant, and minimize its energy cost under the greatest load level. Moreover, the sensitivity of the gained output ratio of desalination cycle to the relative humidity of the air entering and leaving the humidifier, the dehumidifier and humidifier effectiveness, and the top and bottom temperatures are comprehensively analyzed. The relative humidity of air entering the humidifier and the larger dehumidifier effectiveness have the significant effects on increasing the gained output ratio of the desalination cycle. Due to intense solar irradiation in summer, the seawater temperature naturally increases, which results in larger gained output ratio and higher mass flow rate of pure water. [ABSTRACT FROM AUTHOR]

• Previous studies on energy efficiency and fire safety for high-rise ventilation were reviewed. • Statistical analysis was conducted on the research methods, number of literature review sources, and topics. • Research gap on high-rise ventilation for achieving fire safety and energy efficiency was identified. With rapid economic growth, the number of high-rise buildings increases significantly due to land shortage in highly populated cities. Compared with other types of buildings, high-rise buildings have a higher cooling load and are more energy intensive, leading to huge cooling energy consumption and peak electricity demand. Ventilation has proved to be an effective approach to reduce cooling load and thereby save cooling-related energy and reduce peak electricity demand for high-rise buildings, which is important for achieving sustainable development of cities and society. Building safety is a challenge in high-rise ventilation. Fires and the resultant air pollution in high-rise buildings are often disastrous and cause huge losses if the high-rise ventilation system is not designed and operated well. This paper presents a review of previous studies on energy efficiency and building safety for high-rise ventilation, including natural ventilation, mechanical ventilation and hybrid ventilation. Statistical analysis was conducted on the research methods, number of literature review sources, and topics. The research gap was also discussed. Through the review, it was found that increasing research has been conducted on high-rise ventilation, especially on the topic of building safety. It was also recommended to consider both safety and energy simultaneously, in order to achieve energy efficiency and safety in high-rise ventilation and therefore to promote the application of ventilation in high-rise buildings. [ABSTRACT FROM AUTHOR]

• Five prediction models (MLR, AR, ARX, MNR, and BP models) were developed for short term cooling load prediction. • The prediction accuracy on different training time scales (T-1 to T-6) were analyzed, and was evaluated by five evaluation indices. • Performance results showed that prediction accuracy of MNR was highest than MLR, AR, ARX and BP models when using short time training scale T-1. • For short time scale prediction, MNR model requires less training data, low hardware requirements and low computational complexity, which can be easily used to quickly on-site load prediction. Data-mining approaches for improving building cooling load predictions are presented and analyzed on different training time scales (T-1 to T-6) in this paper. Multiple linear regression (MLR), auto regression (AR), autoregressive exogenous (ARX) model, multiple nonlinear regression (MNR), and a back propagation neural network (BP). In this study, a real case in Guangzhou was examined to verify the performance of the prediction models on different time scales using measured cooling load and weather data. Based on the sensitivity analysis, the variable with largest sensitivity is selected as the input to the proposed MNR model, which can ensure prediction accuracy while increasing prediction speed. The case study shows that the prediction from the MNR model is comparable to or better than that from the BP model on different training time scales. The results also show that the MNR model could provide satisfactory prediction accuracy with less data (e.g., 3 d of weather and historical load data), while the BP model requires at least one month of training data to provide the same prediction accuracy. An analysis of the prediction performance results shows that the prediction accuracy from the regression models will decrease and the prediction accuracy from the BP model gradually increases as the training time scale increases. Surprisingly, the prediction accuracy with the MNR model is superior to that from the BP model with T-1 to T-4 training time scales. Finally, it is shown that the MNR model with the limited variable as inputs provides higher prediction accuracy than four other models with training time scales T-1 to T-4. The MNR model requires less training data, simpler hardware, and low computational complexity, making it preferable for quick on-site load prediction. [ABSTRACT FROM AUTHOR]

The energy consumption and thermal comfort in buildings are heavily affected by weather conditions. Therefore, the aim of this paper is to analyze the bioclimatic potential of Algerian climate zones. This analysis was made based on eight representative locations using recent weather datasets (2003–2017). The thermal comfort and passive design potential analysis were based on a psychometric chart applying the adaptive comfort model ASHRAE 55–2017. In addition, an evaluation of the bioclimatic potential was conducted using simulations of a monitored and calibrated residential building model in Algeria using EnergyPlus. The building model has been tested in eight previously selected locations. The heating and cooling energy load results were calculated for each climatic zone and compared. The results allow architects and urban planners to better understand the climate and provide practical design guidance. • The bioclimatic potential of the six climate zones of Algeria was calculated. • A monitoring-based simulation model was created and calibrated. • A strong correlation exists between the bioclimatic potential and performance. • The average percentage of discomfort hours in Algerian households is between 58% and 75%. • Our study confirms the need for a new bioclimatic zoning map for Algeria. [ABSTRACT FROM AUTHOR]

Highlights • Reflective glazed façades have an important influence on the urban microclimate. • Reflected sunbeams increase air temperatures. • Cooling load is strongly impacted by the local solar radiation environment. • Main reason is the high reflectance of the curtain-wall. Abstract The urban landscape of the city of Algiers, Algeria, has seen a spread of reflective glass façades of new and rehabilitated office buildings. This type of glass can create visual glare in outdoor spaces and may lead to indoor thermal discomfort. The objective of this paper is to investigate experimentally and numerically the impact of the reflective glass façade of an existing building on the neighboring microclimate and the building cooling load. The modeling of the microclimate around the case study building is performed with ENVI-met software. The impact of the microclimate is investigated by calculating the cooling load of the case study building with three weather data files. The cooling load is calculated with the building energy simulation software Ecotect for a typical summer day. The weather data files investigated are the experimental data from the reference station of Algiers airport, experimental data measured on the case study building roof, and the data modeled by ENVI-met taking into account the microclimate created by the glazed building. It is found that the air temperature surrounding the building significantly increases due to the multiple reflections of the radiation heat flux, leading to an increase in the cooling demand. [ABSTRACT FROM AUTHOR]

Thermal stratification is the key to improving energy efficiency and indoor air quality for impinging jet ventilation (IJV) system in cooling mode. However, unclear thermal stratification characteristics of IJV system can degrade the ventilation performance of the IJV. In the present study, the thermal stratification characteristics of an IJV is investigated by the validated simulation model for different supply air parameters and internal heat sources in interior zone of office buildings. The critical value of supply air parameters for the formation of thermal stratification is determined by thermal length scale, which considers the combined effect of inertial force and thermal buoyancy on the supply airflow. In addition, the cooling load in an IJV cooling room caused by the heat source intensity can be calculated directly and the heat source distribution is negligible. The results also indicate that the thermal stratification height (H) only depends on supply air parameters, while the temperature difference between head and ankle level (Δ T) is affected by both supply air parameters and cooling load. The predictive models of H and Δ T are obtained based on the simulation results, which could provide the theoretical basis for optimizing the design scheme of IJV system in interior zone of office buildings. • Thermal stratification (TS) of impinging jet ventilation for cooling is studied. • Critical value of supply air parameter (L m) is determined for the formation of TS. • Thermal stratification height H is mainly affected by L m but not cooling load (q). • Temperature difference between head and ankle (Δ T) is affected by both L m and q. • Predictive models of H and Δ T are obtained for design of impinging jet ventilation. [ABSTRACT FROM AUTHOR]