Cooling Energy Research Articles

Decarbonization of Summer Cooling Energy Demands of Buildings Employing Absorption Systems in the Framework of Climate Change in Italy

Temperatures in the Mediterranean area have gradually risen in the last decades due to climate change, especially in the Italian Peninsula. This phenomenon has increased the cooling needs to ensure thermal comfort in buildings and, consequently, the use of refrigeration machines. Summer air conditioning is carried out mainly using compression machines powered by electricity supplied by the national network. All this contributes to the emission of climate-changing gases. To avoid this disadvantageous chain, compression machines could be replaced by absorption cooling systems powered by solar energy. The energy needs of the buildings in a time are directly proportional to the sum of positive differences between the outdoor air temperature and the indoor set point of the systems (equal to 26°C). The annual sum of hourly temperature differences defined above can be computed for each grid cell thanks to a numerical weather prediction model, namely the Weather Research and Forecasting model, that simulates the hourly temperatures on high-resolution computation grids and over fairly large extents. Maps of cooling consumption for buildings are thus produced. Choosing absorption solar energy-powered systems instead of vapor compression refrigeration systems leads to a drop in electrical energy consumption and therefore in emissions of greenhouse gases. In this work, different hypothetical scenarios of penetration of this technology have been considered. And the subsequent consumption of electricity withdrawn from the national grid has been estimated together with the reduction of greenhouse gas emissions.

Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City

Climate change has a major impact on the urban built environment, both with respect to the heating and cooling energy requirements, but also regarding the higher probability of confronting extreme events such as heatwaves. In parallel, the ongoing urbanization, the urban microclimate and the formation of the urban heat island effect, compounding the ongoing climate change, is also a considerable determinant of the building’s energy behavior and the outdoor thermal environment. To evaluate the magnitude of the complex phenomenon, the current research investigates the effect of climate change and urban heat island on heating and cooling energy needs of an urban building unit in Thessaloniki, Greece. The study comparatively evaluates different tools for the generation of future weather datasets, considering both statistical and dynamical downscaling methods, with the latter involving the use of a regional climate model. Based on the output of the regional climate model, another future weather dataset is created, considering not only the general climatic conditions, but also the microclimatic parameters of the examined case study area, under the future climate projections. The generated future weather datasets are then used as an input parameter in the dynamic energy performance simulations with EnergyPlus. For all examined weather datasets, the simulation results show a decrease of the heating energy use, an effect that is strongly counterbalanced by the rise of the cooling energy demand. The obtained simulation results also reveal the contribution of the urban warming of the ongoing climate change, demonstrating the need to perform a holistic analysis for the buildings’ energy needs under future climate conditions.

Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review

Optimizing the building performance at the early design stage is justified as a promising approach to achieve many sustainable design goals in buildings; in particular, it opens a new era of attractive energy-efficient design for designers and architects to create new building constructions with high-energy efficiency and better overall performance. Accordingly, this study aims to provide a comprehensive review of performance optimization studies on heating, cooling, and lighting energy systems of buildings during the design stages, conducting a systematical review covering various aspects ranging from the building type, optimization inputs, the approach used, and the main conclusion. Furthermore, the benefits and limitations of early optimizations in the energy-efficient design performance of buildings and future research directions are identified and discussed. The review results show that previous research efforts of optimizing energy-efficient design performance in buildings have addressed a wide variety of early stage design optimization issues, including orientation and multi-objective building function-related conflicts, such as cooling and lighting. However, significant research issues related to investigations of design envelope materials, proper energy-efficient design form, and other passive parameters, such as solar photovoltaic systems, are still lacking. Therefore, future research should be directed towards improving existing optimization approach frameworks in the context of appropriate energy-efficient design features; integrating sensitivity and uncertainty analyses in the performance optimization framework of buildings to provide a more balanced assessment of influential design envelope properties and extending optimal design envelope investigations of buildings to include other passive parameters and lifecycle assessment under long-term weather conditions.

A Hybrid Simulation Model to Predict the Cooling Energy Consumption for Residential Housing in Hong Kong

In Hong Kong, buildings consume 90% of the electricity generated and over 60% of the city’s carbon emissions are attributable to generating power for buildings. In 2018, Hong Kong residential sector consumed 41,965 TJ (26%) of total electricity generated, with private housing accounting for 52% and public housing taking in 26%, making them the two major contributors of greenhouse gas emissions. Furthermore, air conditioning was the major source consuming 38% of the electricity generated for the residential building segment. Strategizing building energy efficiency measures to reduce the cooling energy consumption of the residential building sector can thus have far-reaching benefits. This study proposes a hybrid simulation strategy that integrates artificial intelligence techniques with a building energy simulation tool (EnergyPlus™) to predict the annual cooling energy consumption of residential buildings in Hong Kong. The proposed method predicts long-term thermal energy demand (annual cooling energy consumption) based on short-term (hourly) simulated data. The hybrid simulation model can analyze the impacts of building materials, construction solutions, and indoor–outdoor temperature variations on the cooling energy consumed in apartments. The results indicate that using low thermal conductivity building materials for windows and external walls can reduce the annual cooling energy consumption by 8.19%, and decreasing the window-to-wall ratio from 80% to 40% can give annual cooling energy savings of up to 18%. Moreover, significant net annual cooling energy savings of 13.65% can be achieved by changing the indoor set-point temperature from 24 °C to 26 °C. The proposed model will serve as a reference for building energy efficiency practitioners to identify key relationships between building physical characteristics and operational strategies to minimize cooling energy demand at a minimal time in comparison to traditional energy estimation methods.

Multi-Scale Numerical Modelling for Predicting Thermo-Physical Properties of Phase-Change Nanocomposites for Cooling Energy Storage

One major limitation of phase-change materials (PCM) for thermal energy storage comes from their poor thermal conductivity hindering heat transfer process and power density. Nanocomposites PCMs, where highly conductive nanofillers are dispersed into PCM matrices, have been exploited in the past decades as novel latent heat storage materials with enhanced thermal conductivity. A computational model based on continuum simulations capable to link microscopic characteristics of nanofillers and the bulk PCM with the macroscopic effective thermal conductivity of the resulting nanocomposite is the aim of this work. After preliminary mean-field simulations investigating the impact of the nanofiller aspect ratio on the thermal conductivity of the nanocomposite, finite element simulations at reduced aspect ratios have been performed with corrected thermal conductivity values of the filler, to take into account the thermal interface resistances between fillers and matrix. Finally, the thermal conductivity at the actual aspect ratios has been extrapolated by the results obtained at reduced aspect ratios thus saving computational time and meshing efforts. This method has been validated through comparison against previous literature evidence and new experimental characterizations of nanocomposite PCMs.

Impact of Passive Energy Efficiency Measures on Cooling Energy Demand in an Architectural Campus Building in Karachi, Pakistan

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.

Efficient Envelope Designs to Maximize Residential Cooling Energy Savings in Bangkok Neighborhoods

Architectural design can significantly improve home energy-efficiency. New energy-saving techniques are regularly proposed; however, integrating all design parameters into the energy simulation specific knowledge and is time-consuming, making it difficult for non-experts in building energy analysis. This present study investigates the impact of envelope designs on household cooling energy consumption in housing complexes located in Bangkok neighborhood areas. The study selects a representative house and identifies a range of envelope designs, including thermal properties of exterior walls and roof, painted color, length of roof eaves, and window-to-wall ratio (WWR). The Latin hypercube method randomly generates two hundred sets of design scenarios based on those design parameters. The eQuest model is used to perform analysis of household cooling energy consumption for four orientations, and the simulation results are validated. The standardized regression coefficient (SRC) is used to determine a strong correlation between design parameters and cooling energy consumption in detached houses. The results reveal that improving a window’s solar heat gain coefficient (SHGC), wall painted color, wall u-value, and length of roof eaves could reduce energy consumption by up to 19.7 percent. The WWR and building orientation were found to have only a small impact on household cooling energy consumption, especially for a square-shaped house. The results provide designers and non-professional a simple design guideline to improve the energy efficiency of their home designs.

Effect of Pv Shadow on Cooling Load and Energy Consumption of Zone Toward Achieving NZEB

Development strategy offers us the resources required to investigate the connection between today’s environmental challenges and the possibility of their progress tomorrow. Currently, the world is facing the greatest surge of population expansion in modern history, which Forced governments to expand urbanization and establishing new cities to accommodate the massive population increase. As a result, the building sector’s CO2 emissions have proceeded to grow by almost 1% a year since 2010, So there is an urgent need to find untraditional solutions to overcome upcoming energy, emissions problems and facing the expected increase of electricity prices. Nearly zero-energy buildings (NZEB) is one of the emerging technologies in the building sector which depend on enhancing building’s energy performance and its extremely low energy demand is met with aid of renewable energy sources as PV solar panels. Via a study made on a conditioned zone located on the last floor of a university building belonging to Arab academy located in Alexandria, Egypt. The effect of the shadow caused by PV panels placed on the roof was studied. A 3D model of the zone was built, then a CFD analysis using the K-epsilon turbulence model was carried out to realize the essence of the shadow effect on this zone. For further clarity and using the DesignBuilder simulation tool the zone cooling load was calculated for both cases with and without PV on the roof, it was found that the zone cooling load reduced by 11.5% in case PV panels are installed on the roof.

Analysis of District Heating and Cooling Energy Systems in Spain: Resources, Technology and Management

District heating and cooling (DHC) systems play an important role under the new European Union (EU) energy transition strategy. Thermal energy networks are helping to stimulate the development of alternative technologies based on a broad range of renewable energy sources. The present study analysed the current situation of DHC systems in Spain and provides an overview of the challenges and future opportunities that their use will entail. Its objective is to assess thermal energy conversion and management from a holistic perspective, including a study of existing energy infrastructures. The focus of this study lies on Spain given the country’s abundance of natural resources such as renewable energy sources including solar energy, biomass and geothermal energy, among others, as well as its strategic location on the map of the EU. Based on the analysis of the three factors for energy conversion in a district heating system, namely resources, technology, and management, the methodology provided an assessment of the different factors involved in running a DHC system. The results show an estimated total production for DHC networks of 1448 MWth, of which 72% is supplied purely by renewable energy sources.

Thermal comfort standards in the Middle East: Current and future challenges

Cooling energy demand has increased three-fold in the Middle East (ME) over the last 30-years. This is driven by the need to maintain thermal comfort in an extremely hot climate, and supported by rising incomes, falling costs of air-conditioning and growth in the number of buildings. The definition of thermal comfort in these buildings is drawn from “international” standards, which, though empirically derived, have no basis data from this region. Hence, we ask, to what extent do indoor conditions in the ME fall within the standards recommended range of thermal comfort, and when they do, whether they are found to be comfortable by their occupants. We present the first large-scale study of thermal comfort in the ME, consisting of two approaches: (i) a meta-analysis of data from existing studies, (ii) independent field data covering four countries representing 27% of the region's population, 31 air-conditioned buildings of different types, including “green” buildings, and 1,101 subjects. The meta-analysis demonstrates that current thermal comfort standards fail to predict thermal sensation of 94% of occupants. Our own data show that, while indoor conditions are within standards-recommended ranges 58% of the time, only 40% of occupants find these conditions acceptable. We find evidence of overcooling in summers, with 39% occupants expressing cold discomfort. Computer models suggest that this is likely to have increased annual cooling energy demand between 13% and 20%, compared to non-overcooled conditions. These results suggest the necessity of localised thermal comfort standards that mitigate excess cooling energy demand, without compromising occupant thermal comfort.

L-shaped mini-louvers performance for reducing indoor temperature

Cooling energy demand is a global problem, especially in the hot area. According to the International Energy Agency, this problem is driven by complex factors, from economic condition to urbanization. This paper examines the use of simple sun shading design as one of possible solutions to reduce the cooling energy in buildings by lowering indoor temperature. Four south oriented wooden boxes were constructed; three of them have L-shaped mini louvers for sun shading attached while another one without any shading device acted as a base case. Mini-overhangs were also tested under the same conditions. The experiment was conducted in Kitakyushu, Japan for 5 days to show the performance of the sun shading in reducing the indoor temperature. The data were recorded using thermo recorder every 30 minutes. The mini louvers showed better performance than overhang. The mini louvers with gap to size ratio of 1:1 reduced around 12 percentage points of average and 33 percentage points of peak temperature. The overhang with same ratio could reduce around 6 percentage points of average and 28 percentage points of peak temperature. The mini louvers were also tested in east direction and the results were similar.

Economic Assessment of L-Shaped Minilouvers for Reducing Cooling Energy and Improving Daylight Condition in Offices: A Simulation Study in Jakarta

Energy consumption is a major sustainability issue. One of the largest portions of energy consumption in buildings comes from cooling. This paper proposes the use of L-shaped minilouvers as shading, which both improve useful daylight illuminance (UDI) and reduce cooling-energy consumption. Jakarta, Indonesia was chosen as the study location since it has driving factors for higher cooling energy, ranging from those of demographic to the environment. An open office was chosen for simulation in Rhinoceros 3D with the Grasshopper, LadyBug, and Honeybee plug-ins, which utilize the EnergyPlus engine. Following the UDI and cooling-energy simulations, surveys were conducted to gather the information of the price of materials for shading and electricity. Savings from cooling energy were compared with the cost of shading application to obtain the simple payback periods. The best shading was provided by L-shaped minilouvers, which can achieve a simple payback period of 0.86 years, reducing cooling-energy consumption by around 18% while improving around 16.78 UDI in comparison with the base case with the average of all the orientations. All simulated L-shaped minilouvers also performed better than the overhang did, which is a more common form of shading in the simulated location.

Experimental Application of Bioclimatic Design Strategies for The Reduction of Cooling Energy Demand in Office Buildings In Tropical Hot-humid Climate

Energy consumption in buildings remains a major driver of global warming and is highly impacted by climate change. A fast-growing sector in the construction industry is office development; consuming energy (mainly for heating, cooling, air-conditioning and lighting) 10-20 times more than the residential sectors. It was implied in recent literature that a continuous increase in development means a continuous rise in energy use and building carbon footprint. The study experimented with the innovative design of an office building which explores bioclimatic design concept, optimization of the efficiency of systems and use of renewable energy to determine their impact on cooling energy demand and building carbon footprint. The study developed an experimental model and simulated it through computer simulation using the passive house planning package (phpp) to investigate cooling energy demand within the tropical warm-humid climate of Lagos, Nigeria. Simulated result of the experimental model of office building showed a reduction in cooling demand by 4.42% to achieve passive house standard. The study encourages the implementation of bioclimatic design strategies in the design of office buildings by the building professionals.

Feasibility Study of Concrete Louvers for High-rise Residential Buildings in Terms of Cooling Energy Requirements

High-rise residential buildings are increasing worldwide, including cities in the Kurdistan Region of Iraq. Therefore, creating sustainable environments in and around these residential buildings are becoming an important problem. Improving energy efficiency in buildings has received critical attention worldwide. Countries have developed national sustainability strategies that lead to the lower energy consumption while maintaining comfort, reducing energy consumption, and minimizing harmful emissions. In this paper, an analysis of the impact of external shading devices in high-rise residential buildings on energy consumption of a 13-storey building in Sulaimani city is studied. The study is focused on fixed shading elements, explaining the influence of the design of vertical and horizontal shading devices on the total energy consumption of this type of building. The results show that both a single fixed horizontal blind with a depth of 20 cm and a triple vertical shading with the same depth are considered useless. The reduction in cooling loads by two fixed horizontal louvers almost doubled compared to a single fixed horizontal shading with 20 cm. Moreover, triple fixed horizontal louvers with 40 cm have almost the same effect on reducing cooling loads as triple fixed louvers with 60 cm. On the other hand, a triple fixed horizontal shading device with 60 cm has twice the effect on reducing annual cooling loads as a triple fixed vertical shading device with 60 cm.

A Data-Driven Approach to Forecasting Heating and Cooling Energy Demand in an Office Building as an Alternative to Multi-Zone Dynamic Simulation

Nowadays, as more data is now available from an increasing number of installed sensors, load forecasting applied to buildings is being increasingly explored. The amount and quality of resulting information can provide inputs for smarter decisions when managing and operating office buildings. In this article, the authors use two data-driven methods (artificial neural networks and support vector machines) to predict the heating and cooling energy demand in an office building located in Lisbon, Portugal. In the present case-study, these methods prove to be an accurate and appealing alternative to the use of accurate but time-consuming multi-zone dynamic simulation tools, which strongly depend on several parameters to be inserted and user expertise to calibrate the model. Artificial neural networks and support vector machines were developed and parametrized using historical data and different sets of exogenous variables to encounter the best performance combinations for both the heating and cooling periods of a year. In the case of support vector regression, a variation introduced simulated annealing to guide the search for different combinations of hyperparameters. After a feature selection stage for each individual method, the results for the different methods were compared, based on error metrics and distributions. The outputs of the study include the most suitable methodology for each season, and also the features (historical load records, but also exogenous features such as outdoor temperature, relative humidity or occupancy profile) that led to the most accurate models. Results clearly show there is a potential for faster, yet accurate machine-learning based forecasting methods to replace well-established, very accurate but time-consuming multi-zone dynamic simulation tools to forecast building energy consumption.

Abatement of the Increases in Cooling Energy Use during a Period of Intense Heat by a Network-Based Adaptive Controller

Various methods to control thermal conditions of building spaces have been developed to investigate their performances of energy use and thermal comfort in the system levels. However, the high control precision used in several studies dealing with data-driven methods may cause energy increases and the high energy efficiency may be disadvantageous for maintaining indoor environmental quality. This study proposes a model that optimizes the supply air condition to effectively reach the setting values by two-way controls of the supply air conditions. In such a process, if the results of the thermal comfort level are outside the range of the initial setting values, an adaptive model starts to work to send additional signals to adjust the set-point temperature. In order to assess its efficiency, the conventional thermostat model and fuzzy deterministic model are adopted as comparators. Comparing the results of the proposed network-based model with conventional control models, an improved control performance from 15.5% to 29.3% in thermal comfort indices was identified, as well as an over 30% improvement in energy efficiency. As a consequence, the network-based adaptive control rule supervising thermal comfort indices properly operates to abate increases in its energy use without compromising its thermal comfort. This performance can be significant in places where many spaces are woven at high density, and in situations where better thermal comfort can increase users’ workability and productivity.

Cooling system energy flexibility of a nearly zero-energy office building using building thermal mass: Potential evaluation and parametric analysis

Building energy flexibility has been considered as a key resource in achieving reliable energy systems. The nearly zero-energy buildings are low-energy and usually equipped with self-production energy systems, which are developing rapidly and play an important role in the energy network. This work aims to investigate the cooling system energy flexibility using building thermal mass in nearly zero-energy office buildings. A simulation-based methodology is proposed to obtain and evaluate the energy flexibility, including a rule-based control strategy and quantification method. The methodology is applied to assess the energy flexibility of a nearly zero-energy office building in Beijing. The influence of different structural parameters, internal heat gains, and cooling terminals on the cooling system energy flexibility performance is considered. Compared with the traditional night set-back control, the peak power and the peak energy can be curtailed by 55.6% and 54.0% in the investigated building under the rule-based control, respectively. The parametric analysis shows that the flexibility realized from thermal mass is highly dependent on the total structural thermal capacity, internal heat gains, and types of cooling terminals. However, the external wall insulation level is a non-significant parameter influencing the cooling system energy flexibility in nearly zero-energy office buildings.

User Placement and Optimal Cooling Energy for Co-working Building Spaces

Increasing real estate and other infrastructure costs have resulted in the trend of co-working offices where users pay as they use for individual desks. Co-working offices that provide personalized comfort need to address users with potentially widely varying thermal comfort preferences. Providing personalized comfort in cabins separated by physical partitions with neighboring thermal zones or open-plan offices with a single actuator has received attention in the literature. In this article, the problem of minimizing user discomfort in open-plan co-working offices with multiple actuators while being cognizant of the energy consumed is considered. Specifically, the decision problems of assigning users to desks based on their thermal preferences and jointly controlling the multiple actuators are addressed. The non-linearities in the underlying thermodynamic constraints and the seating decision together make the problem computationally hard. A two-step heuristic that addresses these issues is presented. First, using a model that accounts for spatio-temporal thermodynamics, a one-time assignment of users to desks is performed that reduces the thermal resistance faced by the HVAC systems to provide the preferred comfort levels. Next, the setpoints are decided for all actuators to jointly minimize user discomfort by optimization and model-predictive control. Further, scalability is addressed by clustering user preferences and the associated HVAC actuators’ setpoints for the cases where a large number of actuators may be present in the room.

Differences in Calculations of Annual Heating and Cooling Energy Need Carried out by Modified Simple Hourly Method and Dynamic Simulations

Differences in Calculations of Annual Heating and Cooling Energy Need Carried out by Modified Simple Hourly Method and Dynamic Simulations

Analysis of Heating and Cooling Energy Consumption in Rental and Sales Apartments in Busan

Analysis of Heating and Cooling Energy Consumption in Rental and Sales Apartments in Busan