Energy Performance Simulation Tools Research Articles

Assessing the reliability of a ship energy performance simulation tool through on-board data

To mitigate the environmental impact of shipping on climate change, it is nowadays urgent to explore energy efficiency and cost-effective measures by means of reliable digital tools. These are becoming essential for assisting the design of new ships and the refurbishment of the existing ones, as well as for assessing and optimizing the energy performance of a ship during its entire life-cycle. This paper focuses on the verification of the reliability of a novel ship energy dynamic simulation tool, developed for the calculation of the energy, economic, and environmental performance of large ships, the design and optimization of energy system layouts and operational logics, as well as the definition of design and management guidelines for ships. The reliability of the developed model was verified through the use of data measured onboard an existing sample cruise ship. The verification procedure is conducted for assessing the reliability and for exploiting the potentiality of dynamic analysis for a more precise evaluation of ships energy loads, temperature levels, and necessary sizes of possible saving technologies. The validated tool will enable reaching two different goals: i) to evaluate different energy system layouts and to define the optimal one for achieving the present imposed targets and constraints, ii) to obtain a large amount of data for allowing the implementation of the digital twin approach in the maritime sector. The model validation was successfully achieved and very low or negligible deviations, lower than 4%, of numerical data vs. measurements were observed. Through the validated simulation tool approximately 23.4 GWh of primary energy from polluting fuels over two weeks is computed. In addition, the model provided insights into the flow rate, temperature levels, and energy flows of the ship energy system, necessary for identifying the amount of thermal energy to be recovered as well as potential solutions to enhance the energy efficiency of the entire system.

A/C usage intensity and adaptive comfort behaviour in residential buildings in South East Queensland, Australia

Occupants’ interaction with building controls has been recognised as a major contributing factor to the often-reported wide discrepancies between actual and predicted energy consumption in buildings. Accordingly, research into actual patterns of occupant behaviour is increasingly being incorporated into building energy performance simulation tools. However, utilizing a single behaviour pattern can also lead to differences between the actual and predicted energy use in a building. This study aims to classify patterns of occupant adaptive comfort behaviours based on longitudinal field observations made in Australian homes. A sample of 41 households was classified into ‘light’, ‘medium’ and ‘heavy’ usage types according to their annual A/C use. Statistical models describing the proportion of a specific adaptive behaviour (incl. A/C and window operation) in relation to outdoor temperature were developed for the three household classifications. The results indicate that more than 30% of the ‘heavy’ usage households operated their A/C for cooling as the outdoor temperature exceeds 30℃, in contrast to 10% for the ‘medium’ and nearly none for the ‘light’ A/C usage groups. In general, the household A/C usage and hours of windows being open in living rooms were found to be inversely proportional. This study also proposes a probability model for classifying the A/C usage levels of a given dwelling into the three groups (i.e. light, medium and heavy) based on simple background information that can be acquired at the design stage (i.e. site and construction characteristics).

Enhancing energy efficiency and comfort with a multi-domain approach: Development of a novel human thermoregulatory model for occupant-centric control

Occupant Centric Control (OCC) strategies aims to achieve a more personalized and comfortable indoor environment, translating occupants' comfort requirements into real environmental conditions. This strategy relies on a multilevel non-linear programming optimization procedure to determine optimal thermo-hygrometric setpoints. The objective is to minimize space heating and cooling requirements while addressing multi-domain comfort concerns related to individual thermal sensations and perceived air quality. To facilitate this process, this study adopts a novel Personal Comfort Model (PCM), incorporating physiological factors to predict occupants' thermal sensations and CO2 intakes. The PCM's reliable predictive capabilities are confirmed through validation with real experimental data from a test room at the University of Perugia. For detailed energy analyses, considering occupants' subjective comfort preferences, the PCM is seamlessly integrated into DETECt, an in-house building energy performance simulation tool developed by the University of Naples Federico II, for the design of advanced control algorithms and energy efficiency strategies. To effectively manage the HVAC system, a model predictive control is implemented, using the determined setpoints to ensure mechanical ventilation and maximize cost savings. The proof of concept for the developed methodology involves simulating experimental tests using the thermal model of the human body and the new facility management system, to be simulated and optimized by means of the enhanced building energy performance simulation tool, exploited for the design and operation of more occupant-centric and sustainable buildings. The proposed study demonstrates that through the developed OCC strategy enables a significant reduction in thermal discomfort (40 % and 60 % less than the occupation time for test 1 and test 2, respectively) compared to reference scenarios. Additionally, energy analysis reveals high efficiency, achieving savings of 12.8 % and 7.8 % of electricity consumed for HVAC system operation.

A New Approach in Daylighting Design for Buildings

Daylighting is a future building design trend, subjected to all the global energy efficiency standards, but its design still largely depends on the architect and it is difficult for electrical engineers to precisely quantify the energy efficiency of the solution. This study presents an innovative integration process of design and simulation, rooted in the parameters of existing standards and regulations, and leveraging architectural design and simulation software tools. Within this novel integrated design methodology, the peripheral zones of the building envelope and the central core areas of the structure are discretely conceptualized and designed. Daylight intensity in the building envelope’s peripheral zones is calculated based on the average daylight factor and the building’s optimized window-to-wall ratio. In contrast, the central core areas are designed to attract daylight from open spaces on the roof, roof structure, reflective roofs, and clerestories. A building energy performance simulation tool is utilized to validate the energy efficiency of these new design techniques. This fresh approach is tested on a complex pilot-scale building in Nhon Trach, Dong Nai, Vietnam, to evaluate the method’s feasibility and scientific soundness. The simulation results corroborate the accuracy of the proposed approach in quantifying the efficiency of reducing a building’s lighting system energy consumption by 34%, equivalent to an annual CO2 saving of over 4,000 tons. Through the proposed daylighting design, an approximate 7% increase incurs in total initial investment, promising substantial profitable returns.

An envelope airtightness predictive model for residential buildings in Spain

The need for airtightness control is a reality given its impact on buildings' energy use and Indoor Air Quality (IAQ). For the past few years, this fact has resulted in energy performance regulations establishment that involves airtightness requirements in many countries in Europe and North America. In this sense, efforts should not only be focused on new buildings, but also existing ones. Considering that around 90% of the built stock in the EU is expected to still be standing in 2050 and that almost 75% of the buildings are energy inefficient, attention must be paid to retrofitting actions.Airtightness predictive models have become useful in the decision-making process and to estimate input values in energy performance simulation tools. So far, several predictive models have been developed in different countries. However, specific construction systems and practices lead to a lack of consensus regarding the impact of different factors on airtightness performance. Therefore, the applicability of existing models is limited to their specific contexts.This paper presents a predictive model for envelope airtightness, which was developed from a database that contains a fully characterised representative sample of the residential building stock in Spain. A General Linear Model (GLM) was considered to assess significant variables related to the age of the building, typology, building state, construction system, and dimensions. As a result, a predictive model is presented and validated. Overall, even if some limitations were identified, the relevance of the model proposed is warranted from the statistical point of view. The airtightness predictive model presented offers a procedure for airtightness estimation of residential buildings in Spain.

Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings

Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and actual energy use. The objective of this study was to develop a stochastic model for predicting occupant behaviour relating to A/C cooling and heating in residential buildings located in the Subtropical Sydney region of Australia. Multivariate logistic regression was used to estimate the probability of using A/C in living rooms and bedrooms, based on a range of physical environmental (outdoor and indoor) and contextual (season, day of week, and time of day) factors observed in 42 Sydney region houses across a two-year monitoring period. The resulting models can be implemented in building energy performance simulation (BEPS) tools to more accurately predict indoor environmental conditions and energy consumption attributable to A/C operation.

A Comparative Study of Artificial Intelligence Models for Predicting Interior Illuminance

ABSTRACT Thanks to the recent advances in computer technology, many building energy performance simulation tools have been developed in the current market. Designers and architects are interested in working on this topic in the early phases of the project. However, effective energy solutions are computationally expensive. As a result, having a comprehensive insight into the project conditions in the early phases of the work is a vital issue. The present study aimed to propose an artificial intelligence (Al) model to generate a reasonably accurate estimate in a short time. To this end, four machine learning models and one artificial neural network (ANN) are selected and their results are compared to assess their capabilities in energy performance estimation. This study investigates the influence of the exterior louver design on the interior energy performance of a structure. A specific dataset is generated and tested on four powerful regression models (i.e., polynomial Linear Regression, Random Forests (RF), Decision Tree (DT), and Support Vector Regression (SVR)) and one Artificial Neural Network (ANN). Finally, a comparative analysis is presented. The findings of this research support the use of machine learning tools and ANNs as a convenient and accurate strategy for predicting building parameters.

Opportunities and Limitations of Building Energy Performance Simulation Tools in the Early Stages of Building Design in the UK

This research investigates the use of Building Energy Performance Simulation (BEPS) tools in the early stages of building design in UK architectural practices with a particular focus on the barriers and opportunities to their effective application and further uptake. Two primary methods of investigation were undertaken; the first was a wide survey among UK architects and architectural practices, where the responses of 418 participants were electronically gathered and analysed. A deeper understanding of the issues was developed through an analysis of the process of low-energy building design using semi-structured interviews with six representatives of well-established architectural practices in the UK. The findings reveal that while there is an increasing understanding of the importance of BEPS involvement at the early design stages, there was limited evidence of actual early implementation of BEPS tools other than a few well known but specialised tools such as Passive House Planning Package (PHPP) which were used mainly for domestic energy performance evaluation. However, many practices surveyed showed interest in achieving higher standards than the “basic” regulatory backstops, which has resulted in Passive House and BREEAM seeing increasing use in domestic and non-domestic projects respectively. Although there has been a significant increase in the development and availability of tools and methodologies for assessing building energy performance our study shows that the focus for future research needs to be shifted from the “tool development” to looking at methods of implementing and using such tools in practice at the early design stages.

The impact of thermophysical properties and hysteresis effects on the energy performance simulation of PCM wallboards: Experimental studies, modelling, and validation

This paper presents a combined experimental and numerical procedure, developed to test the thermophysical behaviour of a real scale PCM wallboard, aiming at providing reliable data for the validation of building energy performance simulation tools. Data obtained from two experimental tests, conducted on real building elements integrating PCM undergoing complete and incomplete phase change, are considered for assessing the impact of thermal properties and hysteresis. A comprehensive comparative numerical analysis, performed by means of an in-house developed simulation tool, called DETECt, is carried out to investigate the reliability of several modelling and simulation approaches available in literature.Monitored data are used to compare the reliability of several modelling and simulation approaches (three different specific heat curves and four modelling approaches for hysteresis) to find out the appropriate temperature dependent heat capacity curves which realistically describe the PCM performance. ResultsThe use of cp – temperature curves characterized through thermophysical analysis (e.g. DSC) under conditions much different than those that the PCM can undergo during the operation of a building can lead to significant discrepancies in performances with the actual data. Moreover, in case of incomplete phase transitions, the lower the accuracy of the cp – temperature curves, the higher the influence of the hysteresis modelling approach on the reliability of simulation results; a better agreement between monitored data and simulation results is observed when hysteresis is modelled by considering the transition between heating and cooling (and vice versa), by switching from the melting to the solidification curves according to the liquid and solid mass fraction.The study shows that the more refined modelling of the phase change allows results to be consistent with the thermo-physics phenomena of composite PCM under real conditions and achieve more reliable results.

Minimalist RC network for building energy simulations: a case study based on OpenBPS

Robust and fast dynamic simulation tools are crucial for the sizing of the components of complex HVAC system and for the definition of the optimal control strategy. In this work, a first step towards the extension of OpenBPS, a new building energy performance simulation tool, to the dynamic simulation of HVAC systems is presented. In particular, the building model has been reduced to a Resistors-Capacitors (RC) network and OpenBPS has been used for the identification of the parameters of the grey-box model. Indeed, the reduction and identification of the building energy model is the fundamental step for extension of the tool to perform dynamic simulations of complex HVAC systems with the advantage of low computational load, thus suitable for parametric yearly simulations and control strategy analyses. The toolkit of identification and cross validation of a minimalist RC network is presented in this paper, discussing the results obtained for a case study building under study in the European project Heat4Cool founded by Horizon 2020 programme. The identified model demonstrated a good accuracy in the estimation of the room temperature under different tests settings representative of the actual operating conditions.

Building Energy Performance Analysis: An Experimental Validation of an In-House Dynamic Simulation Tool through a Real Test Room

This paper focuses on the experimental validation of a building energy performance simulation tool by means of a comparative analysis between numerical results and measurements obtained on a real test room. The empirical tests were carried out for several months under variable weather conditions and in free-floating indoor temperature regime (switched off HVAC system). Measurements were exploited for validating an in-house simulation tool, implemented in MatLab and called DETECt, developed for dynamically assessing the energy performance of buildings. Results show that simulated indoor air and surface room temperatures resulted in very good agreement with the corresponding experimental data; the detected differences were often lower than 0.5 °C and almost always lower than 1 °C. Very low mean absolute and percentage errors were always achieved. In order to show the capabilities of the developed simulation tool, a suitable case study focused on innovative solar radiation high-reflective coatings, and infrared low-emissivity materials is also presented. The performance of these coatings and materials was investigated through a comparative analysis conducted to evaluate their heating and cooling energy saving potentials. Simulation results, obtained for the real test cell considered as equipped with such innovative coatings and material, show that for the weather zone of Naples a 5% saving is obtained both in summer and in winter by simultaneously adopting a high-reflectance coating and a low- emissivity plaster for roof/external walls and interior walls, respectively.

Determination of Accuracy Level for Energy Modelling Tools in Office Buildings in Jos, Nigeria

The research undertook a comparative analysis of results obtained from both Real-time energy consumption measurements and computerized energy use simulations. The purpose was to find the level of accuracy/reliability of data obtainable (Test-Out-Theory) thus leading to a greater efficiency of energy planning decision support tools in the context of their utilization in the sub Saharan regions. eQUEST 3-65 software was used for the purpose of simulation of energy consumption. A 72% cumulative accuracy level was obtained for randomly selected buildings under study. The research therefore recommends that energy performance simulation tools are veritable and viable devices for estimation of potential energy consumption of building at pre and post design stages. Keywords: Sustainability, Energy Performance, Energy Planning, Energy Modelling, Computerized Energy Simulation, eQUEST 3-65 software. DOI : 10.7176/CER/11-1-07

Impact of IPPC Scenarios on indoor environment quality of historic buildings

Ensuring proper indoor environment quality in buildings with historic value or buildings located in historic centres of cities is not an easy task. These buildings are frequently listed in historic preservation lists; thus, the amount of possible refurbishment methods is significantly limited due to increased protection. This article deals with comprehensive analysis of internal microclimate of a multi-purpose building located in the historic centre of Prague during summer period. Possible refurbishment methods permitted by the National Heritage Institute are analysed and compared using building energy performance simulation tool BSim in order to achieve proper working conditions in offices in the building. Structural and technical modifications are proposed in order to optimize the amount of solar heat gains leading to reduction of overheating and increase of energy efficiency. Furthermore, two global warming projections from the Fourth Assessment Report of Intergovernmental Panel on Climate Change are applied to the current weather data to examine the impact of the global climate change on the building. As expected, the cooling demand increases with the climate change scenarios presenting more difficult challenges to maintain the indoor environment quality within the limitations given by the legislation.

Integration time step issue in Mediterranean Historic Building energy simulation

The European target towards Zero Energy buildings is focusing on the energy retrofit of existing buildings. Often, in Mediterranean countries, existing buildings have historical relevancies, involving constraints, when dealing with their energy renovation, due to conservation reasons. To analyze possible energy retrofit actions, building energy performance simulation tools (BEPSt) are valuable. However, old buildings are often made of large stone walls whose resolution through conduction transfer function (CTF) used for sub-hourly time step simulation might be critical. This paper analyses how EnergyPlus and TRNSYS address such problem, explaining the differences between them and the reasons for low quality results.

Numerical investigation of the energy performance of an Opaque Ventilated Façade system employing a smart modular heat recovery unit and a latent heat thermal energy system

The building sector is responsible for more than 40% of the EU’s total energy consumption. To reduce the energy consumption in buildings and to achieve the EU’s fossil fuel saving targets for 2020 and beyond 2050, the energy efficient retrofitting strategies are critically important and need to be implemented effectively. This paper presents a dynamic numerical investigation of the energy performance of an innovative façade integrate-able energy efficient ventilation system (E2VENT) that incorporates a smart modular heat recovery unit (SMHRU) and a latent heat thermal energy system (LHTES). A number of component simulation models, including SMHRU, LHTES, Cladding and Building Energy Management System (BEMS), were developed and then integrated using the TRNSYS software which is an advanced building energy performance simulation tool. On this basis, sizing, optimisation and characterisation of the system elements including the HVAC system and insulation layer thickness were carried out. The overall energy efficiency of the E2VENT system and its impact on the energy performance of a post-retrofit building were then investigated. In particular, the heating and cooling energy performance of the E2VENT façade module was numerically studied at five different climatic conditions in Europe. Furthermore, the innovative E2VENT retrofitting was compared with traditional retrofittings in terms of the energy efficiency and primary energy savings. It was found that the innovative E2VENT solution can achieve 16.5–23.5% building primary energy saving and compared to the traditional retrofitting, the E2VENT solution can achieve two times less primary energy consumption. Thanks to this efficiency the development of this solution for buildings retrofit is promising.

Evaluation of Performance Modelling: Optimizing Simulation Tools to Stages of Architectural Design

Given the necessity of resilience architecture is vital, the most effective decisions on building performance are made at design stages. Simulation represents a possible solution to the complex problem of enabling comprehensive and integrated appraisals of design options under realistic operation conditions [1]. Building Energy Performance Simulation tools (BEPS) provide an opportunity for architects to assess their design strategies in order to reach a high performance building. According to the current developments of Building Information Modeling (BIM) as an Integrated Project Delivery (IPD) tool this study tries to define a logical relation between level of development in different stages of architectural design and BEPS tools in order to fill the gap between architects and engineers in earlier stages of building design. In order to assess the current capability of the simulation tools and evaluate their platforms as an Integration of tools in building design decision making by defined criteria of Input data required for simulation, Usability and graphical visualization of the interface, Interoperability of building modelling, Accuracy and ability to simulate detailed and complex building components. In order to have a market assessment of these types of building performance tools, a survey was conducted of architectural and engineering firms of diverse size.

EnergyPlus as a forensic tool: Thermal reconstruction of a crime scene using calibrated simulation

This study utilized energy simulation in support of a forensic pathology time-of-death analysis for a corpse discovered in a single-family residence two years prior to the study. In order to produce an accurate estimate of the interior temperature profile at the time of death, a thermal model was constructed using EnergyPlus and calibrated using environmental monitoring data from the site. The calibration methods used in the study draw from several precedents and are presented in detail. The thermal model was able to predict the temperature in the room of interest within 1.4°C (2.5°F) with 90% confidence. This model was then altered to account for known differences between the monitoring period and the period of interest, and used to predict what the temperature profile had been at the time of death. This study adds to a small body of work that compares simulated to measured performance data for unconditioned spaces, which should have a growing relevance as building energy performance simulation tools are used to model passive strategies.

EPAR: Energy Performance Augmented Reality models for identification of building energy performance deviations between actual measurements and simulation results

Building energy performance simulation tools such as EnergyPlus, Ecotect, and eQuest are widely used to model energy performance of existing buildings and assess retrofit alternatives. Nevertheless, predictions from simulations typically deviate from actual measurements. Monitoring actual performance and measuring deviations from simulated data in 3D can help improve simulation accuracy through model calibrations, and in turn facilitate identification of energy performance problem. To do that, this paper presents Energy Performance Augmented Reality (EPAR) modeling that leverages collections of unordered digital and thermal imagery, in addition to computational fluid dynamics (CFD) models. First, users collect large numbers of digital and thermal imagery from the building under inspection using a single thermal camera. Through an image-based reconstruction pipeline, actual 3D spatio-thermal models are automatically generated and are superimposed with expected building energy performance models generated using CFD analysis through a user-driven process. The outcomes are EPAR models which visualize actual and expected models in a common 3D environment. Within the EPAR models, actual measurements and simulated results can be systematically compared and analyzed. The method is validated on typical residential and instructional buildings. The results demonstrate that EPAR models facilitate calibration of building energy performance models and support detection and analysis of building performance deviations.

Rooftop photovoltaic (PV) systems for industrial halls: Achieving economic benefit via lowering energy demand

Industrial halls are characterized with their relatively high roof-to-floor ratio, which facilitates ready deployment of renewable energy generation, such as photovoltaic (PV) systems, on the rooftop. To promote deployment of renewable energy generation, feed-in tariff (FIT) higher than the electricity rate is available in many countries to subsidize the capital investment. FIT comes in different forms. For net FIT, in order to maximize the economic benefit, surplus electricity generation at each hour is desirable.One way to achieve surplus electricity generation is by increasing generation capacity, which is synonymous to higher capital investment. In fact, surplus electricity generation can also be achieved by lowering the energy demand of the building. This particularly the case for industrial halls, which are usually subject to high energy demand for space conditioning in order to remove the excess heat gain due to the many power-intensive processes.Building energy performance simulation tools can be used to explore the different building design options that could lower the energy demand. In this paper, single-objective optimization on investment return will be deployed to study the cost effectiveness among different options in lowering energy demand. It will be demonstrated with a case study of a warehouse.

Building modeling as a crucial part for building predictive control

Recent results show that a predictive building automation can be used to operate buildings in an energy and cost effective manner with only a small retrofitting requirements. In this approach, the dynamic models are of crucial importance. As industrial experience has shown, modeling is the most time-demanding and costly part of the automation process. Many papers devoted to this topic actually deal with modeling of building subsystems. Although some papers identify a building as a complex system, the provided models are usually simple two-zones models, or extremely detailed models resulting from the use of building simulation software packages. These are, however, not suitable for predictive control. The objective of this paper is to share the years-long experience of the authors in building modeling intended for predictive control of the building's climate. We provide an overview of identification methods for buildings and analyze their applicability for subsequent predictive control. Moreover, we propose a new methodology to obtain a model suitable for the use in a predictive control framework combining the building energy performance simulation tools and statistical identification. The procedure is based on the so-called co-simulation that has appeared recently as a feature of various building simulation software packages.