Groundwater Utilisation for Energy Production in the Nordic Environment: An Energy Simulation and Hydrogeological Modelling Approach

Groundwater provides one option to utilise renewable energy sources. The long-term groundwater energy potential for three building complexes, situated at latitude of 64°, was investigated by combining an energy demand simulation for the buildings with hydrogeological modelling. First, a reference year for the building energy demand was created. Secondly, groundwater flow requirements were calculated. The results of the previous stages were utilised in groundwater heat transport modelling in an environment where the natural temperature of groundwater was 4.9°C. Finally, the long-term (50 years) groundwater energy potential was calculated. The groundwater maintained its heating potential during 50 years of operation. When both heating and cooling power were demanded, the long-term pumping rate of groundwater decreased by 60,000 m3/a. Energy utilisation created a cold groundwater plume downstream, in which the temperature decreased by 1 to 2.5°C within a distance of 300 m from the site. Groundwater can provide a long-term energy source for large building complexes in the Nordic climate. Results indicate that groundwater could effectively be utilised until the temperature reaches approximately 4°C. Accurate information on the building energy demand and hydrogeology is essential for successful operation.

Optimal retrofitting scenarios of multi-objective energy-efficient historic building under different national goals integrating energy simulation,reduced order modelling and NSGA-II algorithm

Retrofitting a historic building under different national goals involves multiple objectives,constraints,and numerous potential measures and packages,therefore it is time-consuming and challenging during the early design stage.This study introduces a systematic retrofitting approach that incorporates standard measures for the building envelope(walls,windows,roof),as well as the heating,cooling,and lighting systems.Three retrofit objectives are delineated based on prevailing Chinese standards.The retrofit measures function as genes to optimize energy-savings,carbon emissions,and net present value(NPV)by employing a log-additive decomposition approach through energy simulation techniques and NSGA-II,yielding 185,163,and 8 solutions.Subsequently,a weighted sum method is proposed to derive optimal solutions across multiple scenarios.The framework is applied to a courtyard building in Nanjing,China,and the outcomes of the implementation are scrutinized to ascertain the optimal retrofit package under various scenarios.Through this retrofit,energy consumption can be diminished by up to 63.62%,resulting in an NPV growth of 151.84%,and maximum rate of 60.48%carbon reduction.These three result values not only indicate that the optimal values are achieved in these three aspects of energy saving,carbon reduction and economy,but also show the possibility of possible equilibrium in this multi-objective optimization problem.The framework proposed in this study effectively addresses the multi-objective optimization challenge in building renovation by employing a reliable optimization algorithm with a computationally efficient reduced-order model.It provides valuable insights and recommendations for optimizing energy retrofit strategies and meeting various performance objectives.

Evaluating different levels of information on the calibration of building energy simulation models

A poorly calibrated model undermines confidence in the effectiveness of building energy simulation, impeding the widespread application of advanced energy conservation measures (ECMs). Striking a balance between information-gathering efforts and achieving sufficient model credibility is crucial but often obscured by ambiguities. To address this gap, we model and calibrate a test bed with different levels of information (LOI). Beginning with an initial model based on building geometry (LOI 1), we progressively introduce additional information, including nameplate information (LOI 2), envelope conductivity (LOI 3), zone infiltration rate (LOI 4), AHU fan power (LOI 5), and HVAC data (LOI 6). The models are evaluated for accuracy, consistency, and the robustness of their predictions. Our results indicate that adding more information for calibration leads to improved data fit. However, this improvement is not uniform across all observed outputs due to identifiability issues. Furthermore, for energy-saving analysis, adding more information can significantly affect the projected energy savings by up to two times. Nevertheless, for ECM ranking, models that did not meet ASHRAE 14 accuracy thresholds can yield correct retrofit decisions. These findings underscore equifinality in modeling complex building systems. Clearly, predictive accuracy is not synonymous with model credibility. Therefore, to balance efforts in information-gathering and model reliability, it is crucial to (1) determine the minimum level of information required for calibration compatible with its intended purpose and (2) calibrate models with information closely linked to all outputs of interest, particularly when simultaneous accuracy for multiple outputs is necessary.

Normalized urban heat island (UHI) indicators: Classifying the temporal variation of UHI for building energy simulation (BES) applications

Despite known effects of urban heat island(UHI)on building energy consumption such as increased cooling energy demand,typical building energy simulation(BES)practices lack a standardized approach to incorporate UHI into building energy predictions.The seasonal and diurnal variation of UHI makes the task of incorporating UHI into BES an especially challenging task,often limited by the availability of detailed hourly temperature data at building location.This paper addresses the temporal variation of UHI by deriving four normalized UHI indicators that can successfully capture the seasonal and diurnal variation of UHI.The accuracy of these indicators was established across four climate types including hot and humid(Miami,FL),hot and dry(Los Angeles,CA),cold and dry(Denver,CO),and cold and humid(Chicago,IL),and three building types including office,hospital,and apartments.These four indicators are mean summer daytime UHI,mean summer nighttime UHI,mean winter daytime UHI,and mean winter nighttime UHI,which can accurately predict cooling,heating,and annual energy consumption with mean relative error of less than 1%.Not only do these indicators simplify the application of UHI to BES but also,they provide a new paradigm for UHI data collection,storage,and usage,specifically for the purpose of BES.

Effect of typical meteorological year selection on integrated daylight modeling and building energy simulation

The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently.Luminous environment parameters have not been taken into consideration in existing TMY generation methods.In this study,the feasibility of existing TMY generation process has been examined.A generic office model implementing sided window daylighting is established.Historical meteorological data of Hong Kong region from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month(TMM)selection procedures.Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation.The result demonstrates that,on annual basis,the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value.The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%.However,further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level.The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%.As the energy performance daylight utilization is subject to weather change,analysis on daily and monthly energy level is important,especially during design stage.The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.

Coupled simulation of BES-CFD and performance assessment of energy recovery ventilation system for office model

Thermal comfort and indoor air quality as well as the energy efficiency have been recognized as essential parts of sustainable building assessment. This work aims to analyze the energy conservation of the heat recovery ventilator and to investigate the effect of the air supply arrangement. Three types of mixing ventilation are chosen for the analysis of coupling ANSYS/FLUENT （a computational fluid dynamics （CFD） program） with TRNSYS （a building energy simulation （BES） software）. The adoption of mutual complementary boundary conditions for CFD and BES provides more accurate and complete information of indoor air distribution and thermal performance in buildings. A typical office-space situated in a middle storey is chosen for the analysis. The office-space is equipped with air-conditioners on the ceiling. A heat recovery ventilation system directly supplies flesh air to the office space. Its thermal performance and indoor air distribution predicted by the coupled method are compared under three types of ventilation system. When the supply and return openings for ventilation are arranged on the ceiling, there is no critical difference between the predictions of the coupled method and BES on the energy consumption of HVAC because PID control is adopted for the supply air temperature of the occupied zone. On the other hand, approximately 21% discrepancy for the heat recovery estimation in the maximum between the simulated results of coupled method and BES-only can be obviously found in the floor air supply ventilation case. The discrepancy emphasizes the necessity of coupling CFD with BES when vertical air temperature gradient exists. Our future target is to estimate the optimum design of heat recovery ventilation system to control CO2 concentration by adjusting flow rate of flesh air.

Computation and field experiment validation of greenhouse energy load using building energy simulation model

Greenhouse Building Energy Simulation(BES)models were developed to estimate the energy load using TRNSYS(ver.16,University of Wisconsin,USA),a commercial BES program.Validation was conducted based on data recorded during field experiments.The BES greenhouse modeling is reliable,as validation showed 5.2%and 5.5%compared with two field experiments,respectively.As the next step,the heating characteristics of the greenhouses were analyzed to predict the maximum and annual total heating loads based on the greenhouse types and target locations in the Republic of Korea using the validated greenhouse model.The BES-computed results indicated that the annual heating load was greatly affected by the local climate conditions of the target region.The annual heating load of greenhouses located in Chuncheon,the northernmost region,was 44.6%higher than greenhouses in Jeju,the southernmost area among the studied regions.The regression models for prediction of maximum heating load of Venlo type greenhouse and widespan type greenhouse were developed based on the BES computed results to easily predict maximum heating load at field and they explained nearly 95%and 80%of the variance in the data set used,respectively,with the predictor variables.Then a BES model of geothermal energy system was additionally designed and incorporated into the BES greenhouse model.The feasibility of the geothermal energy system for greenhouse was estimated through economic analysis.

Analysis of energy saving optimization of campus buildings based on energy simulation

The energy consumption of campus buildings has specific characteristics, because of the concentrated distribution of people＇s working time and locations that change in line with distinct seasonal features. The traditional energy system design and operation for campus buildings is only based on the constant room temperature, such as 25~C in summer and 18~C in winter in China, not taking into consideration the real heating or cooling load characteristics of campus buildings with different func- tions during the whole day and whole year, which usually results in a lot of energy waste. This paper proposes to set different set-point temperatures in different operation stages of public and residential campus buildings to reduce the heating and cooling design load for energy station and total campus energy consumption for annual operation. Taking a campus under construction in Tianjin, China as an example, two kinds of single building models were established as the typical public building and residential building models on the campus. Besides, the models were simulated at both set-point room temperature and constant room temperature respectively. The comparison of the simulation results showed that the single building energy saving method of the peak load clipping could be used for further analysis of the annual energy consumption of campus building groups. The results proved that the strategy of set-point temperature optimization could efficiently reduce the design load and energy consumption of campus building groups.

Evaluation of the relative differences in building energy simulation results

Building energy modeling,also known as building energy simulation,has developed rapidly in recent years and plays a crucial role in building life-cycle analysis.It can be employed in the design phase to predict the energy consumption of different design schemes and evaluate various control and retrofitting measures at the operation stage.In such simulations,it is commonly understood and accepted that the simulated relative differences are more reliable than the predictions of absolute energy results.However,whether this common understanding is true is yet to be thoroughly investigated.In this study,we investigate the simulated relative differences and the extent to which they are affected by the degree of model input deviation.Simulation and Monte Carlo approaches are adopted for the analysis.The results indicate that the simulated relative differences are not as reliable as expected,and the outputs strongly depend on the degree of the model input deviation.When the degree of deviation is less than 15%or the model inputs are within reasonable ranges,the simulated relative differences match the baseline obtained using Monte Carlo simulations.Moreover,the model’s error indicators meet the requirements of the ASHRAE Guideline 14–2014 when the degree of input deviation is below 15%.

HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS

With high resolution （1 kin）, the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit （WEST） model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software Wasp （Wind Atlas Analysis and Application Program）. The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST＋WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.

Energy consumption simulations of rural residential buildings considering differences in energy use behavior among family members

The“average occupant”methodology is widely used in energy consumption simulations of residential buildings;however,it fails to consider the differences in energy use behavior among family members.Based on a field survey on the Central Shaanxi Plain,to identify the energy use behavior patterns of typical families,a stochastic energy use behavior model considering differences in energy use behavior among family members was proposed,to improve the accuracy of energy consumption simulations of residential buildings.The results indicated that the surveyed rural families could be classified into the following four types depending on specific energy use behavior patterns:families of one elderly couple,families of one middle-aged couple,families of one elderly couple and one child,and families of one couple and one child.Moreover,on typical summer days,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 25.39%and 28%lower than the simulation results obtained by the model proposed in this study for families of one elderly couple and families of one middle-aged couple,and 13.05%and 23.05%higher for families of one elderly couple and one child,and families of one couple and one child.On typical winter days,for the four types of families,the results of daily building energy consumption simulation obtained by the“average occupant”methodology were 21.69%,10.84%,1.21%,and 8.39%lower than the simulation results obtained by the model proposed in this study,respectively.

Energy Performance and Condensation Risk of DCDV System in Subtropical Hong Kong

The combined use of dry cooling(DC) system and dedicated ventilation(DV) system to decouple cooling and dehumidification process for energy efficiency was proposed for subtropical climates like Hong Kong. In this study, the energy performance and condensation risk of the use of DCDV system were examined by analyzing its application in a typical office building in Hong Kong. Through hour-by-hour simulation using actual equipment performance data and realistic building and system characteristics, it was found that with the use of DCDV system, the annual energy consumption could be reduced by 54% in comparison with the conventional system(constant air volume with reheat system). In respect of condensation risk, it was found that the annual frequency of occurrence of condensation on DC coil was 35 h. Additional simulations were conducted to examine the influence of different parameters on the condensation risk of DCDV system. Measures to ensure condensate-free on DC coil were also discussed.

Economic Analysis of Energy-efficient Buildings in China

Applying energy-saving measures in residential buildings is usually constrained by the increase of initial investment. ＂However, if it is analyzed from the view of energy cost and life-cycle cost, the energy-saving benefit can offset ~he increase of initial investment. An analysis method based on life-cycle concept was developed to calcu- late the energy cost of residential building flats. Several uncertain factors were included into the model, making it more accurate to reflect practical situation. The model was solved using the software DeST and applied to one resi- dential building project in Shanghai. The case study shows that the initial investment （cost） is paid back during the operational phase through less consumption of energy. It further indicates that the investment recovery period is between 10 and 19 years which are acceptable to households and developers in China.

Prediction of Residential Building’s Solar Installation Energy Demand in Morocco Using Multiple Linear Regression Analysis

The building sector is one of the main energy-consuming sectors in Morocco.In fact,it accounts for 33%of the final consumption of energy and records a high increase in the annual consumption of energy caused by further planned large-scale projects.Indeed,the energy consumption of the building sector is experiencing a significant acceleration justified by the rapid need for the development of housing stock,wich is estimated at an average increase of 1,5%per year;furthermore,tant is an estimated increase of about 6,4%.In this sense,building constitutes an important potential source for rationalizing both energy consumption and energy savings through the adoption of energy efficiency measures.Energy consumption control efforts in the residential building sector involve socio-economic,technological,and environmental concerns that require sophisticated research.Indeed,different types of quantitative models have been developed and examined so as to find a solution for the optimizing energy consumption.In this work,we have highlighted the importance of using solar heaters to reduce energy demand in terms of the use of domestic hot water.To do this,we have defined the needs and characteristics of a solar installation of a residential building located in Casablanca through a calculating tool“SOLO 2000”in addition to the use of multiple linear regression analysis to deduct the impact of irradiation and solar contributions on the energy demand of the solar installation.

A Predictive Nighttime Ventilation Algorithm to Reduce Energy Use and Peak Demand in an Office Building

The effect of two nighttime ventilation strategies on cooling and heating energy use is investigated for a prototype office building in several northern America climates, using hourly building energy simulation software （DOE2.1E）. The strategies include： scheduled-driven nighttime ventilation and a predictive method for nighttime ventilation. The maximum possible energy savings and peak demand reduction in each climate is analyzed as a function of ventilation rate, indoor-outdoor temperature difference, and building thermal mass. The results show that nighttime ventilation could save up to 32% cooling energy in an office building, while the total energy and peak demand savings for the fan and cooling is about 13% and 10%, respectively. Consequently, finding the optimal control parameters for the nighttime ventilation strategies is very important. The performance of the two strategies varies in different climates. The predictive nighttime ventilation worked better in weather conditions with fairly smooth transition from heating to cooling season.

Experiment and simulation of foaming injection molding of polypropylene/nano-calcium carbonate composites by supercritical carbon dioxide

Microcellular injection molding of neat isotactic polypropylene(iPP) and isotactic polypropylene/nano-calcium carbonate composites(i PP/nano-CaCO_3) was performed using supercritical carbon dioxide as the physical blowing agent. The influences of filler content and operating conditions on microstructure morphology of i PP and i PP/nano-CaCO_3 microcellular samples were studied systematically. The results showed the bubble size of the microcellular samples could be effectively decreased while the cell density increased for i PP/nano-CaCO_3 composites, especially at high CO_2 concentration and back pressure, low mold temperature and injection speed, and high filler content. Then Moldex 3D was applied to simulate the microcellular injection molding process, with the application of the measured ScCO_2 solubility and diffusion data for i PP and i PP/nano-Ca CO_3 composites respectively. For neat i PP, the simulated bubble size and density distribution in the center section of tensile bars showed a good agreement with the experimental values. However, for i PP/nano-CaCO_3 composites, the correction factor for nucleation activation energy F and the pre-exponential factor of nucleation rate f_0 were obtained by nonlinear regression on the experimental bubble size and density distribution. The parameters F and f_0 can be used to predict the microcellular injection molding process for i PP/nano-CaCO_3 composites by Moldex 3D.

Assessment of wind energy potential in China

China wind atlas was made by numerical simulation and the wind energy potential in China was calculated. The model system for wind energy resource assessment was set up based on Canadian Wind Energy Simulating Toolkit (WEST) and the simulating method was as follows. First, the weather classes were obtained depend on meteorological data of 30 years. Then, driven by the initial meteorological field produced by each weather class, the meso-scale model ran for the distribution of wind energy resources according each weather class condition one by one. Finally, averaging all the modeling output weighted by the occurrence frequency of each weather class, the annual mean distribution of wind energy resources was worked out. Compared the simulated wind energy potential with other results from several activities and studies for wind energy resource assessment, it is found that the simulated wind energy potential in mainland of China is 3 times that from the second and the third investigations for wind energy resources by CMA, and is similar to the wind energy potential obtained by NREL in Solar and Wind Energy Resource Assessment(SWERA) project. The simulated offshore wind energy potential of China seems smaller than the true value. According to the simulated results of CMA and considering lots of limited factors to wind energy development, the final conclusion can be obtained that the wind energy availability in China is 700～1 200 GW, in which 600～1 000 GW is in mainland and 100～200 GW is on offshore, and wind power will become the important part of energy composition in future.

Numerical Simulation of Multi-Directional Random Wave Transformation in a Yacht Port

This paper extends a prediction model for multi-directional random wave transformation based on an energy balance equation by Mase with the consideration of wave shoaling, refraction, diffraction, reflection and breaking. This numerical model is improved by 1) introducing Wen's frequency spectrum and Mitsuyasu's directional function, which are more suitable to the coastal area of China; 2) considering energy dissipation caused by bottom friction, which ensures more accurate results for large-scale and shallow water areas; 3) taking into account a non-linear dispersion relation. Predictions using the extended wave model are carried out to study the feasibility of constructing the Ai Hua yacht port in Qingdao, China, with a comparison between two port layouts in design. Wave fields inside the port for different incident wave directions, water levels and return periods are simulated, and then two kinds of parameters are calculated to evaluate the wave conditions for the two layouts. Analyses show that Layout I is better than Layout II. Calculation results also show that the harbor will be calm for different wave directions under the design water level. On the contrary, the wave conditions do not wholly meet the requirements of a yacht port for ship berthing under the extreme water level. For safety consideration, the elevation of the breakwater might need to be properly increased to prevent wave overtopping under such water level. The extended numerical simulation model may provide an effective approach to computing wave heights in a harbor.

Effects of Rotor Solidity on the Performance of Impulse Turbine for OWC Wave Energy Converter

Impulse turbine, working as a typical self-rectifying turbine, is recently utilized for the oscillating water column（OWC） wave energy converters, which can rotate in the same direction under the bi-directional air flows. A numerical model established in Fluent is validated by the corresponding experimental results. The flow fields, pressure distribution and dimensionless evaluating coefficients can be calculated and analyzed. Effects of the rotor solidity varying with the change of blade number are investigated and the suitable solidity value is recommended for different flow coefficients.

Assessing the energy saving potential of using adaptive setpoint temperatures:The case study of a regional adaptive comfort model for Brazil in both the present and the future

It has been found in recent years that using setpoint temperatures based on adaptive thermal comfort models is a successful method of energy conservation.Recent studies using adaptive setpoint temperatures incorporate international models from ASHRAE Standard 55 and EN16798-1.This study,however,has instead considered a regional Brazilian adaptive comfort model.This study investigates the energy demand arising from the use of a local Brazilian comfort model in order to assess the energy implications from the use of the worldwide ASHRAE Standard 55 adaptive model and various fixed setpoint temperatures.All of Brazil’s climate zones,full air-conditioning,mixed-mode building operating modes,present-day climate change scenarios,and future scenarios—specifically Representative Concentration Pathways(RCP)2.6,4.5,and 8.5 for the years 2050 and 2100—have all been taken into account in building energy simulations.The use of adaptive setpoint temperatures based on the Brazilian local model considering mixed-mode has been found to significantly reduce energy consumption when compared to static setpoint temperatures(average energy-saving values ranging from 52%to 58%)and the ASHRAE 55 adaptive model(average values ranging from 15%to 21%).Considering climate change and the mixed-mode Brazilian model,the overall energy demand for the three groups of climatic zones(annual average outdoor temperatures≤21℃,>21 and≤25℃and>25℃)ranged between 2%decrease and 5%increase,4%and 27%increase,and 13%and 45%increase,respectively.It is concluded as a consequence that setting setpoint temperatures based on the Brazilian local adaptive comfort model is a very efficient energy-saving method.