Energy Simulation Approach Research Articles

Future role of wave power in Seychelles: A structured sensitivity analysis empowered by a novel EnergyPLAN-based optimisation tool

Mitigating climate change requires a variety of energy technologies and energy simulation approaches to evaluate the best possible system structures. Screening whether novel technologies are a viable solution for a particular country within a cost-optimised system setup is usually simulation- and time-intensive. This study introduces the novel add-on optimisation tool EP-ALISON-LUT for use in combination with EnergyPLAN applied to the test case of wave power in the case of Seychelles in 2030 and 2050 within a structured sensitivity analysis. The tool enables a high number of possible system setups and scenarios, including the import and domestic production of electricity-based fuels, to be modelled, allowing for an in-depth view of the system impacts of integrating wave power. The results indicate a limited role for wave power due to its relatively low yield, especially in 2030. However, in 2050, up to 500 MW of wave power capacity is possible with a lower or similar levelised cost of final energy compared to the reference scenario in 2019, which can benefit the diversification of the power generation portfolio. Thus, this novel tool is fast and effective in technology screening studies requiring a fast optimisation algorithm.

Quantifying energy poverty vulnerability with minimal data – A building energy simulation approach

Energy poverty is a pressing issue that many countries currently face. The income per household and energy use data per household are variables used in widely known methodologies on the topic of energy poverty. However, due to different reasons, this data isn’t made available in many locations of interest, which prevents them from quantifying energy poverty. To overcome this problem, this study introduces a not yet explored asset-based workflow that makes use of income distributions and building energy modelling to quantify a household’s energy poverty vulnerability. This study defines a novel energy poverty vulnerability index (EVI) that makes use of the widely known ten-percent rule’s fundamental concepts but avoids the latter’s main critics through two major improvements; a varying threshold is introduced with a linear function and distortion is prevented using a weighted average. The methodology has been applied to more than 85,000 low-rise apartment buildings in Montreal, Canada to quantify their energy poverty vulnerability, a feat that wasn’t possible using typical methodologies. The case study results have shown that Montreal’s buildings’ energy poverty vulnerability is highly dependent on the household’s income, but also on the insulation level and floor area. A sensitivity analysis has been conducted to determine the EVI’s requirements and limitations. From this analysis, the EVI is most sensitive to variables related to the building’s energy consumption and is least sensitive to income.

Characterizing and structuring urban GIS data for housing stock energy modelling and retrofitting

Addressing the gap between available urban building data, energy performance evaluation, and spatial distribution of end-users is a growing concern of municipalities to support energy planning and urban retrofitting towards low carbon emission. These days, many existing urban building energy models (UBEM) use the non-geo-specified 3D building stock geometries or the digital twins of cities as their primary input for energy simulation. The digital twins of cities or the built environment is an accurate scale virtual representation (geo-specified geometry and information) of city objects enabled to be paired with dynamic predictive models of their energy performance. The use of built environment digital twins for their energy assessment works well for those cities whose digital twin datasets are readily available for public or private use. In the cities without digital twin datasets, their energy assessment is limited by tools that use 2D building stock footprints as their primary input or apply a top-down urban energy simulation approach. This gap motivated the current research to identify an extended UBEM data preparation workflow focused on generating city digital twins using accessible GIS datasets as well as national and local data sources. The workflow is majorly developed to deal with GIS data processing utilizing multilevel spatial data integration and refinement to fill in the recognized inconsistencies of building databases. Then, procedural 3D city modelling and an automated transformation to a semantic, CityGML format are successfully provided to generate digital twin of the study area in an open data model. The archetype modelling method is also employed to create a set of customized housing energy profiles to support tailored bottom-up UBEM and retrofitting scenarios relying on the simulation platform Insel4Cities, under development at Concordia University. The workflow was practically carried out on a case study, Kelowna city in British Columbia (BC)/Canada, to validate the district heating load. The average simulated heating energy use intensity showed a deviation of less than 2.5% from the BC measured data. As an example of workflow usability, the developed model was also utilized to assess a retrofit scenario, combining a decentralized heat pump and photovoltaic system, to present the district's potential for net-zero action planning.

Typical-year and multi-year building energy simulation approaches: A critical comparison

Building Energy Simulation (BES) tools usually make use of single Typical Weather Years (TWYs) but the increased calculation capacity now allows for multi-year simulations based on Actual Weather Years (AWYs). This research analyzes how the use of a TWY affects the prediction of the energy demand and the peak load in a residential and an office building located in Catania (Italy), if compared to a multi-year approach. Different TWYs are considered, either developed by the authors according to standard international procedures and based on recent measurements from a local weather station, or already available on the internet. Results show that the adoption of a TWY is useful to assess the mean long-term energy demand, with a preference for the IWEC procedure (mean bias error below 2%). However, TWYs would underestimate the peak heating load by 12.5% and the peak cooling load by around 18% in the residential building, while in the office building the underestimation can be even higher. In the absence of specific design weather files when the aim of the simulations consists in sizing the mechanical systems, the peak values of the AWYs distribution based on the last 10–15 years of measurement should be preferred to TWYs.

Relationship Between Energy Demand, Indoor Thermal Behaviour and Temperature-Related Health Risk Concerning Passive Energy Refurbishment Interventions

Abstract The main objective of this article is to demonstrate that passive energy refurbishment interventions influence comfort conditions of households for both cold and hot annual periods, while they help to avoid or promote temperature-related health risk situations. However, improving the thermal efficiency of the building envelope is encouraged in order to reduce energy demand for heating and cooling instead of considering also their impact on users’ health. The calculation methodology to quantify improvements, on the other hand, is drawn from regulation-based standards, which describe the optimal achievable efficiency levels and energy cost savings. The present study, however, addresses how diverse thermal performance variables are (climate, thermal comfort range and occupancy rate), and shows that different thermal assessment standards influence the obtained results. An energy simulation approach was developed to evaluate different scenarios and compare the results. In conclusion, the results contribute to an understanding or to a discussion of the suitability of current energy renovation policies with regard to indoor thermal comfort and temperature-related health risk situations.

BIM–energy simulation approach for detecting building spaces with faults and problematic behavior

Heating and cooling consumes most of the energy in buildings. Faults and problems in HVAC systems waste up to 20% of heating and cooling energy. Identifying spaces with HVAC problems within a facility remains a major challenge for facility managers. This study aims to detect spaces with potential problems that causes energy overconsumption, human discomfort, or HVAC work overload. To achieve that, a Building Information Model (BIM)-based framework that combines the output data of building energy simulations, Building Energy Management Systems (BEMS), and Computerized Maintenance Management Systems (CMMS) is proposed. The framework enables BIM components to utilize data collected by the other systems to determine the intended energy performance and compare it with actual energy performance, as well as to provide access to maintenance history and BEMS alarms occurred in the building at element level. The framework was tested using data collected from an educational building over one-month period when the building was unoccupied to prevent users from manipulating the results. Experimental results show that the framework enabled identification of building spaces with abnormal or malfunctioning behavior that was not detected by the BEMS. This study supplements the body of knowledge in facilities energy management by providing a BIM-based framework that utilizes output data of energy simulation, BEMS and CMMS to locate and detect building spaces with potential problems that need maintenance. Furthermore, it enables facility managers to collect and view relevant data from various systems in one central platform; BIM. It also allows them to adjust their maintenance plans based on the poor behavior of specific spaces within their building.

Analysis of the influence of cooling jets on the wind and thermal environment in football stadiums in hot climates

After winning the bid of the FIFA’s World Cup 2022, Qatar is facing the greatest challenges in terms of minimizing substantial energy consumptions for air-conditioning of stadiums and maintaining aero-thermal comfort for both players and spectators inside stadiums. This paper presents the results of temperature distributions and wind environment of the original stadium under the hot-humid climate and improvements on them for optimized scenarios of cooling jets. A combined computational fluid dynamics and building energy simulation approach was used to analyse the cooling performance and energy consumption per match of cooling air jets for 10 scenarios with different supply velocities, supply temperatures and locations of jets. The optimal scenario is to employ vertical jets above the upper tiers at supply temperature of 20°C and velocities of 2–12 m/s, integrated with horizontal jets of the same temperature at the lower tiers with 4 m/s and around the pitch with 7 m/s. This scenario can maintain the spectator tiers at an average temperature of 22°C and reduce the maximum predicted percentage of dissatisfied of thermal comfort from the original 100% to 63% for the pitch and 19% for the tiers, respectively. In terms of the energy consumption for the air-conditioning system per match, compared with one of the 2010 South Africa World Cup stadiums Royal Bafokeng stadium which consumed approximately 22.8 MWh energy for air-conditioning in winter (highest outdoor temperature 24.4°C), the maximum energy consumption of the optimal scenario in November (highest outdoor temperature 34.2°C) can reach 108 MWh. In addition, the spectator zones with scenario 8 have the potential to be resilient to the seasonal change of outdoor temperature if slight modifications of the supply velocities and precise temperature control on the spectator zones are applied. Moreover, the configurations presented in this paper can be used as a foundation of jets arrangement for future stadium retrofits in the hot climates. Practical application: This study assesses the aero-thermal conditions of a case study stadium under the hot climate of Qatar and explores the potential of applying cooling jets with different supply velocities, supply temperatures and their locations on the enhancement of both thermal and wind environment of spectator tiers and pitch. The assessment of the original stadium indicates that the ascending curved roof structure impedes the fresh air entering into the stadium and results in an asymmetric temperature distribution on the spectator tiers. The optimized design suggests a combination of vertical jets under the roof and both three arrays of horizontal jets at lower tiers and around pitch for future stadium optimizations in hot climates. It also recommends enhancing the thermal conditions on the pitch by optimizing the velocity of horizontal jets around the pitch. Moreover, the future design of the exact stadiums to be resilient to the seasonal changing outdoor temperature can be implemented based on scenario 8.

Cost premiums for green buildings in Qatar

The aim of this paper is to start a conversation about the cost premium for green buildings in Qatar. It examines what Qatar has achieved over the last decade and explores the root cause of green building cost premiums, why they exist, what can we do about them, and why should we accept them. For the purposes of this paper, the term green building specifically refers to buildings pursuing certification under USGBC's “LEED” or GORD's “GSAS” rating system, which are most commonly used in Qatar. However, lower oil prices have led to tighter spending and a greater focus on value engineering and cost savings. It is assumed that the environmental benefits of green buildings are understood and taken as given. Accordingly, here we aim to shift the conversation toward how to maximize value from implementing green building rating systems. We analyze the costs and benefits of the main GB rating systems currently used in Qatar, such as GSAS and LEED. By identifying the costs of constructing a green building, in this study, we aim to inform developers how to minimize the cost premium while getting more benefits. We also identify some of the causes of key problems that can occur on GB projects, where GB cost premiums can increase beyond what is typical for the certification level achieved. These problems can often lead to symptoms beyond cost over-runs and can manifest themselves as time delays, quality, and other issues. In addition, some of the key strategies to reduce GB costs and increase the economic benefits from achieving GB certifications are identified. We conclude the paper with some recommendations to authorities for adopting GB rating systems on a wider scale to achieve a greater scale of change. We focus on some key issues with the GSAS rating schemes that influence GB costs and strive for a common energy simulation approach for all regional GB rating systems in the GCC. We also discuss how the integrity of a GB rating system is imperative to building confidence in the value of each certification level, which should result in “Green Premiums” being reflected in the property market. Finally, we argue that with support from Qatar Green Building Council and GORD, Qatar's planning authorities should initiate programs for the sustainable development of buildings in Qatar.

Data analytics for occupancy pattern learning to reduce the energy consumption of HVAC systems in office buildings

In the last few years, the collecting and processing of occupancy data have become emerging issues since they can affect, either directly or indirectly, several energy operations in buildings. The application of data analytics-based methods makes it possible to exploit the potentialities of occupancy related knowledge to enhance the energy management in buildings. A methodology, aimed at implementing an occupancy-based HVAC system operation schedule, is presented in this article. The process is based on the convenience of displacing groups of occupants with similar occupancy patterns to the same thermal zone. An optimisation of the stop schedule of an HVAC system has been investigated, considering a typical week’s occupancy patterns. The methodology was used to analyse the Zaanstad Town Hall (The Netherlands), considering anonymous occupancy data for a monitoring period of four months. The resulting optimised schedule was tested, through an energy simulation approach, considering a model calibrated with real energy consumption data. The savings related to the energy consumption of the HVAC system, as a result of the implementation of the strategy, in comparison to an occupancy-independent operation schedule amounted to 14%. The proposed process can be generalized and drive energy managers in evaluating optimised occupancy-based HVAC system operation schedules.

A Proposed New Weighting System for Passive Design Approach in BEAM Plus

Abstract Building environmental assessment method (BEAM) has been practiced by local architects and engineers as references for green building design over the last 20 years. The current version of BEAM Plus v1.2 has introduced the passive design concept to make the rating scheme in line with the state-of-art energy efficient design in the world. However, the introduced passive design approach is criticized for its arguable criteria allocation, unjustified weighting system and incompatibility with the existing whole building energy simulation approach. In view of these flaws, a new weighting system based on different global sensitivity analysis methods, robust energy end-use statistics and a green building case study is proposed in this article. The total available credits of sub-criteria are determined according to the ratio of the cooling and lighting energy consumption in the total end-use energy data of residential buildings. Eventually, the priorities of assessment criteria are derived from the sensitivity analysis of a generic building model based on a simultaneous variation of different design parameters. The results from this research can help stakeholders in a green building project to identify design strategies with the largest impact over building performance and obtain an optimized preliminary design in the early planning stage.

Quantifying the impact of urban wind sheltering on the building energy consumption

Current building energy simulation approaches usually do not take into account the influence of the surrounding urban neighborhood on the energy consumption patterns. This study aims to address this limitation and quantify the impact of an urban neighborhood. Therefore, the current study develops and validates a framework using Computational Fluid Dynamics (CFD) and building energy simulations. The developed framework in this study relies on deriving wind multipliers for eight principal directions to adjust the wind velocity encountering the building of interest. The purpose of these wind multipliers is to adjust wind velocities in the weather data input files for building energy models. To support the developed framework, this study validated the simulated CFD temperatures with on-site measured data as well as compared the simulated heating and electricity consumptions with the metered energy consumptions. A comparison between the building energy simulation results using both the adjusted and original weather data indicates that the total building energy consumption decreased by 5%. Among the heat gain components, the infiltration component had the maximum percentage of reduction with 31% and 29% sensible cooling and heating decrease, respectively. Overall, even though the annual cooling energy demand increased, the energy demand decreased due to the decrease in the heating demand for the studied neighborhood located in the Northeastern USA.

Automated energy simulation and analysis for NetZero Energy Home (NZEH) design

NetZero Energy Homes (NZEHs) have emerged as a solution to alleviate the energy demand from residential building operation, where appropriate design of building envelope and mechanical system is a means to achieving energy conservation and recovery for NZEHs. This research thus proposes an informed decision making framework for NZEH building design based on an automated energy simulation approach. The Batch Version of HOT2000 is utilized to achieve automated single-factor and combined-factor simulations, and a total of 16 200 combinations of building envelope and mechanical device design options are simulated for NZEH design. An NZEH project in Edmonton, Canada, is utilized as the case study in this research. The initial design of the NZEH results in an estimated energy deficit of 6048.0 MJ, accounting for 8.8% of the total consumption, and, based on the combined-factor simulations results, improved design scenarios are recommended for this NZEH. The simulation results of the initial design are also validated using the monitored data, with the actual performance showing an energy deficit of 4.1% of total consumption. Furthermore, such analysis as regression, factor importance ranking, and temperature set-point simulation are also conducted for the NZEH building design. This research proposes a framework to support informed design decision making for NZEHs, and builds a baseline for future study.

Implementation of demand response strategies in a multi-purpose commercial building using a whole-building simulation model approach

This paper exploits a whole-building energy simulation approach to develop and evaluate demand response strategies for commercial buildings. The research is motivated by the increasing penetration of renewable energy sources such as wind and solar, which owing to their stochastic nature, means that enhanced integration of demand response measures in buildings is becoming more challenging and complex. Using EnergyPlus, a simulation model of a multi-purpose commercial building was developed and calibrated. Demand response strategies are evaluated for a number of building zones, which utilise different heating, cooling and ventilation equipment. The results show that for events of varying demand response durations, different strategies should be selected for each zone based on their thermal and usage profiles. Overall, a maximum reduction of 14.7% in electrical power demand was recorded when targeting a centralised chiller load, with smaller reductions for other decentralised building loads.

A novel energy simulation approach for thermal design of buildings equipped with radiative panels using inverse methodology

The purpose of this research is to present a novel approach to estimate thermal design parameters with unknown values in a building equipped with radiative panels with the use of inverse methodology. A direct model is selected to analyze thermal behavior of building components in order to determine indoor temperature field using direct numerical modeling. Using inverse analysis, three thermal design parameters with unknown values, such as conductivity, internal and external convection and total heat transfer coefficients, are estimated using Levenberg–Marquardt and conjugate gradient methods with the knowledge of temperature field resulted from direct modeling. To illustrate the sufficiency of inverse technique, the results of both noisy and non-noisy estimations are presented using sensitivity analysis. To verify the accuracy of the present study, the results of inverse analysis are compared with those of numerical simulation presented in the literature, which indicates a good agreement between numerical and inverse solutions. It is shown that inverse analysis can be used as an applicable approach to increase computational precision in building thermal design phase.

Challenges in computational studies of enzyme structure, function and dynamics

In this review we give an overview of the field of Computational enzymology. We start by describing the birth of the field, with emphasis on the work of the 2013 chemistry Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by experiments, has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-molecular mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.

Energy simulation approach to air-conditioning system evaluation

This paper deals with the energy simulation approach in evaluating some of the commonly employed air-conditioning systems for high-rise office buildings. These systems are evaluated on the basis of their thermal comfort performance and energy efficiency. It is found that the Two Pipe Induction Unit System (TPIUS) performs the best and is the most energy efficient, followed by the Variable Air Volume System (VAVS). The thermal comfort performance of Packaged Variable Air Volume System (PVAVS) and the Constant Air Volume System (CAVS) is less preferred among all systems studied and they also appear to be the least energy efficient.

The Free Energy Simulation Approach to Grain Boundary Segregation In Cu-Ni

ABSTRACTA new, accurate method for determining equilibrium segregation to defects in solids is employed to examine the segregation of Cu to grain boundaries in Cu-Ni alloys. The results are in very good agreement with the ones given by Monte Carlo. This method is based upon a point approximation for the configurational entropy, an Einstein model for vibrational contributions to the free energy. To achieve the equilibrium state of a defect in an alloy the free energy is minimized with respect to atomic coordinates and composition of each site at constant chemical potential. One of the main advantages this new method enjoys over other methods such as Monte Carlo, is the efficiency with which the atomic structure of a defect, segregation and thermodynamic properties can be determined. The grain boundary free energy can either increase or decrease with increasing temperature due to the competition between energetic and configurational entropy terms. In general, the grain boundary free energy increases with temperature when the segregation is strongest.