Building Thermal Loads Research Articles

Optimal scheduling method based on building virtual energy storage equivalent battery

In this paper, an optimal scheduling method based on building virtual energy storage equivalent battery is proposed. Firstly, the thermal load prediction model is built based on the thermodynamic model, and then the equivalent battery model of virtual energy storage is established by combining with inverter air conditioning system model. Then, with the goal of minimizing the user’s electricity cost, considering the constraints of energy storage state and charging and discharging power of equivalent battery model, an optimal scheduling method of building virtual energy storage equivalent battery is constructed. The results show that the proposed method can predict the building thermal load, update the building virtual energy storage equivalent battery parameters, formulate the corresponding optimal scheduling strategy, and reduce the electricity cost of users for heating on the premise of ensuring the thermal comfort of users.

Energy Performance Evaluation of a Ventilated Façade System through CFD Modeling and Comparison with International Standards

Ventilated façades can help to reduce summer building thermal loads and, therefore, energy consumption due to air-conditioning systems thanks to the combined effect of the solar radiation reflection and the natural or forced ventilation into the cavity. The evaluation of ventilated façades behavior and performance is complex and requires a complete thermo-fluid dynamic analysis. In this study, a computational fluid dynamic (CFD) methodology has been developed for the complete assessment of the energy performance of a prefabricated timber–concrete composite ventilated façade module in different operating conditions. Global numerical results are presented as well as local ones in terms of heat flux, air velocity, and temperature inside the façade cavity. The results show the dependency of envelope efficiency on solar radiation, the benefits that natural convection brings on potential energy savings and the importance of designing an optimized façade geometry. The results concerning the façade behavior have been thoroughly compared with International Standards, showing the good accuracy of the model with respect to these well-known procedures. This comparison allowed also to highlight the International Standards procedures limits in evaluating the ventilated façade behavior with the necessary level of detail, with the risk of leading to design faults.

Large-scale estimation of buildings’ thermal load using LiDAR data

Increasing population and urbanisation threaten sustainable urban development due to increased resource consumption and emissions. As buildings are one of the largest energy consumers, it is crucial that their thermal load can be inspected on a large scale and at the highest resolution possible. The proposed method is performed in two stages. First, the LiDAR data and buildings’ metadata are preprocessed to generate high-resolution 3D building models that are represented by a triangle mesh. Thermal load of buildings throughout the year is then calculated per-triangle in a parallelised manner, while considering local micro-climate and shadowing from surroundings. Parallel design of the estimation enables significant speed-up of large-scale workloads, while maintaining accurate shadowing estimation. In experiments, the method was applied over a part of the city of Maribor, where heating and cooling loads were inspected in addition to other factors of thermal load estimation. Yearly thermal load calculation with an hourly time-step for 4,817 buildings with over 9.17 million triangles took about 8 min on a modern GPU. When comparing the run-times using a GPU and a modern CPU, the GPU was more than 60-times faster than a CPU for a million triangles. The speed-up grew with the number of triangles.

Vertical meteorological patterns and their impact on the energy demand of tall buildings

In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.

Tube-Based Model Predictive Controller for Building’s Heating Ventilation and Air Conditioning (HVAC) System

The proactive control of building’s heating, ventilation, and air conditioning (HVAC) system can reduce energy consumption and provides cost saving. An efficient design of a controller for a complex system such as a building, which is also prone to uncertainties and disturbances, calls for advanced control methods such as model predictive control (MPC). This article presents a tube-based MPC to minimize the net cost of energy usage by the building’s HVAC system while satisfying the comfort level of the building’s occupants. Contrary to the conventional MPC, this controller is robust against model uncertainty and exogenous disturbances affecting the building thermal load model. Compared to other robust approaches such as the min–max controller, the proposed controller is of lower computational complexity and can be used with the environment having complex models, e.g., with nonlinear dynamics. Moreover, the proposed controller shows a satisfactory performance when optimizing an economic objective, such as cost minimization. The merits of using the proposed MPC controller are demonstrated using several simulation cases.

Smoothing control of solar photovoltaic generation using building thermal loads

Distributed energy resources such as solar photovoltaic (PV) systems are seeing significant expansion in power grids worldwide. However, serious system integration issues have arisen including voltage fluctuations and accelerated aging of voltage regulation devices, when adopting mass amounts of volatile energy resources onto legacy distribution networks originally designed for unidirectional power flow. Building heating, ventilation and air-conditioning (HVAC) systems, collocated with the distributed generation, can be considered as flexible loads due to the inherent building thermal inertia. HVAC systems can be proactively controlled to improve voltage regulation of distribution networks with high PV penetrations. This paper presents a smoothing solution that modulates HVAC power in response to volatile PV generation as a means to mitigate fluctuations in the net demand and generation. To demonstrate the effectiveness and evaluate performance gains, hardware-in-the-loop (HIL) tests were carried out using a 3-ton variable-speed heat pump. The HIL tests leveraged a building thermal dynamic model and a steady-state power flow model for a 33-bus distribution network to capture realistic indoor thermal responses and distribution voltage variations during PV smoothing control. Test results showed that the developed strategy was effective in reducing variations of net demand and generation with negligible impact on indoor comfort. More than 55% reductions of voltage fluctuation were achieved and tap operations of voltage regulators could be fully or partially eliminated with proactive PV smoothing.

Performance Analysis of Single-Well Enhanced Geothermal System for Building Heating.

Deep borehole heat exchanger (DBHE) technology does not depend on the existence of hot water reservoir and can be used in various regions. However, the heat extraction from DBHE can hardly be improved due to poor thermal conductivity of rocks. Here, a single-well enhanced geothermal system (SWEGS) is proposed, which has a larger heat-exchange area of artificial reservoir created by fracturing hydrothermal technology. We find that, due to heat convection between rocks and fluid, the extracted thermal output for SWEGS is 4772.73 kW, which is 10.64 times of that of DBHE. By changing the injection water temperature, volume flow rate, and artificial reservoir volume, it is easy to adjust the extracted thermal output to meet the requirement of building thermal loads varying with outdoor air temperature. Understanding these will enable us to better apply SWEGS technology and solve the fog and haze problem easily and efficiently.

Application of an unconventional thermal and mechanical energy storage coupled with the air conditioning and domestic hot water systems of a residential building

This paper proposes the application on microscale of an innovative trigeneration system with micro CAES (Compressed Air Energy Storage) – TES (Thermal Energy Storage) and the integration of renewable energy production, focusing on the potential use for air conditioning and domestic hot water systems. The system allows storing mechanical energy in the form of elastic and thermal potential of compressed air through two thermal storage units, HTTES (High Temperature Thermal Energy Storage) and LTTES (Low Temperature Thermal Energy Storage). The proposed system is tested on a single-family building in a warm climate.The analysis is carried out for integrated and independent operating modes. In integrated mode, the LTTES refrigerant charge and the vapor compression chiller operate simultaneously to cover the building's thermal load. In this case the energy expenditure is only related to the power supply of the chiller. In independent mode, the cold storage and the chiller work alternately during evening operation to limit the absorption of energy from the distribution network.The results show that, in integrated operating mode with partial recirculation and internal temperature conditions of 26 °C and 50% of relative humidity, the system reaches, in relation to the peak thermal load, a maximum operating time of 236 min. The minimum operating time of 26 min is reached using the full external air operating mode with an internal temperature of 26 °C and relative humidity of 40%. In independent operation mode, it is possible to sustain the evening thermal load for up to a maximum of 5 h without electricity absorption from the distribution network.

Energy flexibility and shiftable heating power of building components and technologies

PurposeThe paper aims to clarify the relationship between energy flexibility and building components and technologies. It determines the energy flexibility potential of buildings in relation to their physical characteristics and heat supply systems with respect to external boundary conditions.Design/methodology/approachThe emphasis of the evaluation is based on the timing and the amount of shiftable and storable thermal loads in buildings under defined indoor thermal comfort conditions. Dynamic building simulation is used to evaluate the potential of selected building characteristics to shift heating loads away from peak demand periods. Insights on the energy flexibility potential of individual technologies are gained by examining the thermal behaviour of single-zone simulation models as different input parameters are varied. For this purpose, parameters such as envelope qualities, construction materials, control systems for heating are modified.FindingsThe paper provides a comprehensive understanding of the influence of the different building parameters and their variations on their energy shifting potential under “laboratory conditions” with steady boundaries. It suggests that the investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the heating load of a building, also influence the resulting potential for energy flexibility. The findings show that the combination of a slowly reacting heat transfer system, such as concrete core activation and a readily available storage mass in the room, and a high insulation standard proved to have a high potential to shift heating loads.Originality/valueIn this paper, energy-flexible components were evaluated in a steady-state simulation approach. Outside temperature, solar irradiation and internal loads over the simulation duration were set constant over time to provide laboratory conditions for the potential analysis. On the basis of both duration and performance of the load shifting or storage event, the components were then quantified in a parametric simulation. The determined energy flexibility is directly related to the power of the heating, cooling, hot water and ventilation system, which can be switched on or off. In general, it can be seen that high power (high loads) demand usually can be switched on and off for a short duration, and low power demand usually for a longer duration. The investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the load of a building, also influence the resulting potential for energy flexibility. Higher insulation standards, for example, lead to lower loads that can be switched on or off, but increase the duration of the event (flexibility time). So that, in particular, the shiftable load potential is low but results in a long switch-off duration. Furthermore, passive storage potential in buildings like the storage mass inside the room and the type of heat/cooling transfer system can affect the flexibility potential by more than three times. Especially the combination of a high storage mass and a concrete core heat transfer system can significantly increase the flexibility.

Performance of Hybrid Single Well Enhanced Geothermal System and Solar Energy for Buildings Heating

The energy reserves in hot dry rock and hydrothermal systems are abundant in China, however, the developed resources are far below the potential estimates due to immature technology of enhanced geothermal system (EGS) and scattered resources of hydrothermal systems. To circumvent these problems and reduce the thermal resistance of rocks, here a shallow depth enhanced geothermal system (SDEGS) is proposed, which can be implemented by fracturing the hydrothermal system. We find that, the service life for SDEGS is 14 years with heat output of 4521.1 kW. To extend service life, the hybrid SDEGS and solar energy heating system is proposed with 10,000 m2 solar collectors installed to store heat into geothermal reservoir. The service life of the hybrid heating system is 35 years with geothermal heat output of 4653.78 kW. The novelty of the present work is that the hybrid heating system can solve the unstable and discontinuous problems of solar energy without building additional back-up sources or seasonal storage equipment, and the geothermal thermal output can be adjusted easily to meet the demand of building thermal loads varying with outside temperature.

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day’s data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost’s accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model’s robustness. Our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

Thermal Characterization of Pinus radiata Wood Vacuum-Impregnated with Octadecane

The incorporation of phase change materials (PCM) in construction components has become an alternative to reduce the effect of thermal loads in buildings with low thermal inertia. This study put together the effective heat storage capacity of an organic phase change material (O-PCM, octadecane) with the construction and production potential of Pinus radiata in Chile. The wood is impregnated with octadecane by using the Bethell method, showing that it has good retention of the impregnator, and that its size was not modified. Differential scanning calorimetry analysis (DSC) showed that the composite material could achieve fusion enthalpy values from 36 (20.8 MJ/m3) to 122 J/g (108.9 MJ/m3). The transient line heat source method used, indicated that impregnation of Pinus radiata with octadecane increases its specific heat at temperatures from 15 to 20 °C, while its thermal conductivity decreases in the radial and the tangent directions, and increases in the longitudinal direction, showing a decrease in the orthotropic behavior of the wood. The ability of Pinus radiata wood to store latent heat positioned it as a candidate material to be considered in the building industry as a heat storage system.

Building thermal load management through integration of solar assisted absorption and desiccant air conditioning systems: A model-based simulation-optimization approach

Performance of standalone air-conditioning systems is affected while simultaneously handling both sensible and latent building loads. Model-based simulation and optimization is one of the best ways to analyze system's performance under load fluctuations at the initial design stages. Therefore, in the current study, seasonal transient simulations of an Integrated Absorption Desiccant System are carried out using TRNSYS to handle sensible (10.94 kW peak) and latent (4.44 kW peak) cooling load separately. Radiant cooling with chilled water from an absorption chiller mainly handles sensible cooling load, while the latent load is achieved by a solid desiccant dehumidification system. Initially, key components of the system are modeled in TRNSYS including a flat plate solar collector system, desiccant wheel, heat recovery wheel, and absorption chiller. Afterwards, the integrated model is coupled with GenOpt to optimize the solar fraction and thermal coefficient of performance by varying collector area, flow rate in the collector loop, flow rate in load side loop, and volume of storage tank. The resulted optimized value of solar fraction is 57.50%, and COPth is 0.55 for standalone absorption system, whereas the solar fraction of 56.20%, COPth of 1.52 are achieved for IADS. In addition, the effects of load variation in terms of sensible to latent load ratio on regeneration heat required for both IADS and conventional desiccant system are also analyzed. A critical value of load ratio of 0.75 is also observed in terms of heat regeneration requirements to compare the both systems. The proposed approach and analysis will be very helpful for HVAC designers for optimal system performance through separate load handling, especially at the initial design stage.

Local energy self-sufficiency for passive buildings: Case study of a typical Moroccan building

The building sector in Morocco represents about 25% of the country's total energy consumption, including 18% for the residential sector and 7% for the service sector. The integration of renewable energies in the building sector is the subject of a major trend in terms of future projects in Morocco. Today, Morocco is targeting a strategy that will allow it to achieve 50% of its electricity consumption from a renewable, new and clean local energy source. Through this current situation, this article has just made a positive contribution, by studying the impact of the passive part of a typical Moroccan R+1 building, in particular that of thermal insulation, on its energy self-sufficiency in different climates. TRNSYS simulation studio was used to design and develop a platform to calculate this objective in a global and specific way. This platform combines a whole hybrid system, based on two new and clean renewable energy sources (wind turbine and photovoltaic energy), to the building's thermal loads. The results show that the impact of thermal insulation on the building's energy self-sufficiency in all the studied climates is very significant, especially in Ifrane city (Morocco). Given that the energy self-sufficiency in this climate has been improved by 41.28% more than the baseline situation. Finally, we suggest that the Moroccan building thermal code should include the impact of the passive part of the building on its energy self-sufficiency in the form of numerical indicators, in order to encourage people to get involved in this development.

Typical Building Thermal and Thermal Load Forecasting Based on Wavelet Neural Network

Abstract The cold/heat/electrical load forecasting is of great significance for the planning and design of the terminal energy supply system. Based on the historical data of the cold/heat/electrical load of five typical buildings, the wavelet neural network is used for cold/heat/electrical short-term load forecasting. The simulation results show that the maximum absolute average error of the cold/heat/electrical load forecasting of the wavelet neural network is 1.8%, and the calculation speed is fast. It is a suitable cold/heat/electrical load forecasting method.

A Nonlinear Autoregressive With Exogenous Inputs Artificial Neural Network Model for Building Thermal Load Prediction

Abstract Thermal load prediction is a key part of energy system management and control in buildings, and its accuracy plays a critical role to improve building energy performance and efficiency. Regarding thermal load prediction, various types of prediction model have been considered and studied, such as physics-based, statistical, and machine learning models. Physical models can be accurate but require extended lead time for model development. Statistical models are relatively simple to develop and require less computation time, but they may not provide accurate results for complex energy systems with intricate nonlinear dynamic behaviors. This study proposes an artificial neural network (ANN) model, one of the prevalent machine learning methods to predict building thermal load, combining with the concept of nonlinear autoregressive with exogenous inputs (NARX). NARX-ANN prediction model is distinguished from typical ANN models because the NARX concept can address nonlinear system behaviors effectively based on its recurrent architectures and time indexing features. To examine the suitability and validity of NARX-ANN model for building thermal load prediction, a case study is carried out using the field data of an academic campus building at Mississippi State University (MSU). Results show that the proposed NARX-ANN model can provide an accurate and robust prediction performance and effectively address nonlinear system behaviors in the prediction.

A simplified numerical model for evaporative cooling by water spray over roof surfaces

Evaporative cooling is a well-known passive technique adopted especially in hot and dry climatic regions. This paper presents a simplified numerical model to assess the impact of water spray over roof surfaces on the building thermal load. First, we performed a series of long-term outdoor measurements of heat fluxes from an asphalt pavement and roof top of a laboratory building waterproofed by asphalt sheet. Based on the measured data, a correlation is proposed to estimate the evaporation rate of the concerned surfaces after rain showers. A simplified numerical model is then developed using this correlation based on the unsteady heat transfer to analyze the effect of precipitation and artificial water spray on the roof of the laboratory building. Simulation is performed with the help MATLAB using the hourly weather data from Fukuoka, Japan, and the simulated results are found to be in correspondence with the measured data. Finally, the cooling effect achieved by varying the amount and rate of water spray over the roof is compared to find out the optimum spraying conditions.The novelty of this study is that, in this model, the evaporation rate can be expressed in terms of the evaporation ratio, which is defined as a function of the water content of the surface layer of the roof. The water content of the surface layer can be obtained by the water balance equation, which is coupled dynamically with conductive equations. This procedure can drastically reduce the calculation load compared to the conventionally applied simultaneous hygrothermal transfer equation.

Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations

In the past decade, urban building energy models have been developed to address the increasing concerns over energy consumption and greenhouse gas emission due to rapid urbanization and building resilience as a result of climate change. These models can estimate energy consumption, GHG emission and resilience response of buildings in an urban area, and evaluate retrofit strategies for architects, engineers, researchers and policy makers. It has been recognized that local microclimate and neighborhood effects play an important role in urban building energy modeling. Creating an urban building energy model also requires the collection of extensive building data, which is a time-consuming process. In this study, we developed an integrated platform by combining CityFFD (City Fast Fluid Dynamics), an urban-scale fast fluid dynamics model for microclimate modeling, and CityBEM (City Building Energy Model), a new urban building energy model with a library of 1700 building archetypes for facilitating urban model creation. Local aerodynamics and heat transfer information are exchanged between both models at each time step. Graphics processing unit computing is also applied to CityFFD for simulation speedup. The simulation of the 1971 Montreal snowstorm of the century was conducted as a case study of more than 1500 buildings of an island near Montreal, Canada for the investigation of their resilience against the three-day power outage due to the storm. Building retrofit analysis was also conducted to evaluate the added level of resilience. The results show that the proposed platform can produce high-resolution results of building thermal load, microclimate condition, and building behavior during weather extremes.

Feasibility study of using solar energy as a renewable source in office buildings in different climatic regions

PurposePresent research focus on using solar energy as a renewable option for office buildings in different climatic conditions in Iran. To seeking a way to use clean solar energy and reduce current expense in buildings an investigation carried out. Nine office buildings in various climatic regions selected as case studies. Through a precise examination, buildings specifications, energy demand and climate information carried out. In the first step based on the buildings type and hot water demand, solar water heater systems designed for each case. In the second step, a cost-benefit analysis is done to detriment the economic aspects of implement aforementioned type of solar system. A cost-benefit analysis is done from saving energy and return time of investment point of view. Results indicate that solar water heater with low investment about US$500 and payback time between 2 and 5 years can be noticed as a desirable renewable option in case studies. Furthermore, analysis reveals that thermal load of building is more effective on fuel saving in building, while solar radiation intensity has more effective on the payback in solar water heater utilization.Design/methodology/approachIn this study based on thermal load of nine building office and radiation of different part of Kermnashah province, the possibility of solar water system is investigated.FindingsAnalyses reveal that the thermal load of building is more effective on fuel saving, while solar radiation intensity has more effective on the payback in solar water heater utilization. The main originality goes back to consideration of different meteorological conditions in solar water heater selection.

Effectiveness of cool walls on cooling load and urban temperature in a tropical climate

The urban overheating, driven by the increasing expansion of our cities and the global climate change, is becoming one of the main environmental challenges of today. Consequently, cooling technologies are emerging as mitigation and adaptation strategies. Reflective roof and pavement surfaces have been widely studied for their potential benefits, but detailed evaluations of the effect of wall albedo on the urban microclimate are limited. This study addresses this gap by evaluating the effects of reflective walls on urban energy use and outdoor climate. The energy balance of an idealized neighborhood is represented using a 3D numerical model, Temperature of Urban Facets Indoor-Outdoor Building Energy Simulator (TUF-IOBES), which determines the cooling loads and outdoor air temperature. The study focuses on the tropical climate of Singapore, addressing the urban climate in highly-populated cities in low latitudes that are significantly affected by the UHI. Simulations are conducted for two neighborhoods representative of low-rise residential and high-rise commercial urban areas, spanning a range of urban density, canyon geometry, building construction, and occupant schedules. The building thermal load and outdoor temperature are then calculated for these two idealized neighborhoods, analyzing the effectiveness of cool walls while also considering the role of other design factors such as window-to-wall ratio (WWR) and glazing solar heat gain coefficient (SHGC) in modulating the impact. Unlike the analysis of cool roofs, we find that a universal conclusion regarding the impact of cool walls cannot be drawn. The role of wall albedo significantly depends on the collective design of urban areas as well as the use and occupancy of buildings. We find that urban density (in other words the local climate zone) followed by window properties are important factors in determining the impact of wall albedo on thermal loads and UHI, as they determine the radiative exchange between and into the buildings. Accordingly, contrary to the general expectation, for a high urban density (commercial neighborhood LCZ6) and high WWR and SHGC, we observe that cool (reflective) walls can increase the building energy use. Regarding UHI, increasing the reflectivity of walls decreases the canopy air temperature but the impact is marginal ( ∼ 0.1 °C) compared to other urban design parameters.