On the Utilization of an Ensemble of Meta-Heuristics for Simulating Energy Consumption in Buildings

Predicting energy consumption has been a substantial topic because of its ability to lessen energy wastage and establish an acceptable overall operational efficiency. Thus, this research aims at creating a meta-heuristic-based method for autonomous simulation of heating and cooling loads of buildings. The developed method is envisioned on two tiers, whereas the first tier encompasses the use of a set of meta-heuristic algorithms to amplify the exploration and exploitation of Elman neural network through both parametric and structural learning. In this regard, ten meta-heuristic were utilized, namely differential evolution, particle swarm optimization, invasive weed optimization, teaching-learning optimization, ant colony optimization, grey wolf optimization, grasshopper optimization, moth-flame optimization, antlion optimization, and arithmetic optimization. The second tier is designated for evaluating the meta-heuristic-based models through performance evaluation and statistical comparisons. Besides, an integrative ranking of the models is achieved using average ranking algorithm.

Mitigating Harmful Effects of Climate Warming on Ceiling Paintings by Ceiling Insulation: An Evaluation Using Timed IR Imaging and Numeric Modelling

Due to climate change, ceiling paintings in many historic buildings are subjected to increasingly high short-term temperature change, resulting in high thermal tension caused by the construction assembly. This article focuses on the combined use of timed IR imaging and numeric modelling to evaluate insulation measures on the upper side of a ceiling to reduce thermal tensions in the painting layers, overheating in summer as well as cooling down in winter. As a model room, the southern splendour stair hall in the Burgtheater Vienna was chosen. Famous ceiling paintings created from 1886 to 1888 by Gustav Klimt and his brother Ernst Klimt can be found on this ceiling. The results show that timed IR imaging is an adequate tool to study the transient thermal behaviour of ceiling paintings which are not accessible to standard sensor measurements. Moreover, it could be shown that the presented measurement technique is well suited to validate a numeric model. The latter was applied to evaluate the potential insulation on the top of the ceiling. It was shown that cooling loads and energy loss in the room underneath can be reduced and most importantly the thermal stress in painting layers is reduced. The findings are relevant as, due to global warming, the current situation in many buildings is worsening. Considering the great intangible cultural value of many ceiling paintings, the application of the presented evaluation strategy for building physical boundaries on a ceiling with paintings seems to be appropriate.

An Evaluation of the Performance of a Ground-to-Air Heat Exchanger in Different Ventilation Scenarios in a Single-Family Home in a Climate Characterized by Cold Winters and Hot Summers

In the present study, the real-world performance of a ground-to-air heat exchanger (GAHE) was analyzed in the Polish climate which is characterized by warm summers and cold winters. The heat exchanger’s performance was monitored over a period of three years (2017 to 2019), and real-world conditions were compared with a Typical Meteorological Year (TMY). The aim of the study was to assess the exchanger’s energy-efficiency potential in various ventilation scenarios in a single-family home under variable real-world conditions, rather than to simply determine its heating and cooling capacity. The analyzed single-family home was a modern, single-story building with a usable floor area of 115 m2. The building’s thermal insulation and airtightness met stringent energy-efficiency standards. Energy consumption in a building equipped with a natural ventilation system was compared with three other scenarios: ventilation coupled with a GAHE, mechanical ventilation with heat recovery and a high-efficiency heat exchanger (HE), and mechanical ventilation with heat recovery coupled with a GAHE. Sensible heating and cooling loads were calculated based on standard ISO 13790:2008, and latent heating and cooling loads were also included in the energy balance. During the year, the GAHE generated around 257.6 W of heating energy per hour and 124.7 W of cooling energy per hour. Presented results can be used to select the optimal HVAC system scenarios for engineering projects as well as private investors.

A short review on passive strategies applied to minimise the building cooling loads in hot locations

Cooling and air-conditioning systems are responsible for the highest energy consumption in buildings located in hot areas. This high share does not only increase the building energy demand cost but also increases the environmental impact, the topmost awareness of the modern era. The development of traditional systems and reliance on renewable technologies have increased drastically in the last century but still lacks economic concerns. Passive cooling strategies have been introduced as a successful option to mitigate the energy demand and improve energy conservation in buildings. This paper shed light on some passive strategies that could be applied to minimise building cooling loads to encourage the movement towards healthier and more energy-efficient buildings. For this purpose, seven popular passive technologies have been discussed shortly: multi-panned windows, shading devices, insulations, green roofing, phase change materials, reflective coatings, and natural ventilation using the windcatcher technique. The analysis of each strategy has shown that the building energy could be improved remarkably. Furthermore, adopting more passive strategies can significantly enhance the building thermal comfort even under severe weather conditions.

ENERGY EFFICIENT IMPROVEMENT OF HISTORIC BUILDINGS: A CASE STUDY IN SINOP

Although historical buildings are ecological with their construction systems and materials, they cannot provide necessary performance in today's comfort conditions and therefore they are abandoned and remain in a damaged or dysfunctional state. Energy efficient improvement works are carried out in historical buildings in order to bring the historical buildings today's conditions, re-use and ensure their sustainability. However, there are many limitations in these studies due to the heritage characteristics of historical buildings. With these limitations, the works to be done should be carried out with the least intervention without damaging the heritage values of the historical buildings. For this reason, it is necessary to specially select the applications to be realized within the scope of energy efficiency in historical buildings and scaling the physical effects of the applications relative to each other. In this context, in this study, it is aimed to reveal the appropriate improvement methods in order to reach the maximum energy efficiency with the least physical intervention, with the techniques suitable for the historical texture by preserving the original qualities in the historical buildings. Based on the Historic England intervention evaluation scale developed in this framework, 5 scenarios, including the current situation and 4 different design scenarios, including interventions from small to large impacts, were created on a sample historical residential building, and the data of each scenario in terms of energy consumption were obtained. Models created within the framework of the scenarios were evaluated with the Design Builder simulation program, and annual heating and cooling loads and the amount of energy consumed per total m² were obtained. Evaluations were made by comparing the energy efficiency of applications at different degrees with the graphics and tables prepared in the light of these data. As a result, suggestions have been developed regarding the interventions to be made to historical buildings according to the intervention effect sizes in the context of energy efficiency with the evaluations made.

Tuning Deep Neural Networks for Predicting Energy Consumption in Arid Climate Based on Buildings Characteristics

The dramatic growth in the number of buildings worldwide has led to an increase interest in predicting energy consumption, especially for the case of residential buildings. As the heating and cooling system highly affect the operation cost of buildings; it is worth investigating the development of models to predict the heating and cooling loads of buildings. In contrast to the majority of the existing related studies, which are based on historical energy consumption data, this study considers building characteristics, such as area and floor height, to develop prediction models of heating and cooling loads. In particular, this study proposes deep neural networks models based on several hyper-parameters: the number of hidden layers, the number of neurons in each layer, and the learning algorithm. The tuned models are constructed using a dataset generated with the Integrated Environmental Solutions Virtual Environment (IESVE) simulation software for the city of Buraydah city, the capital of the Qassim region in Saudi Arabia. The Qassim region was selected because of its harsh arid climate of extremely cold winters and hot summers, which means that lot of energy is used up for cooling and heating of residential buildings. Through model tuning, optimal parameters of deep learning models are determined using the following performance measures: Mean Square Error (MSE), Root Mean Square Error (RMSE), Regression (R) values, and coefficient of determination (R2). The results obtained with the five-layer deep neural network model, with 20 neurons in each layer and the Levenberg–Marquardt algorithm, outperformed the results of the other models with a lower number of layers. This model achieved MSE of 0.0075, RMSE 0.087, R and R2 both as high as 0.99 in predicting the heating load and MSE of 0.245, RMSE of 0.495, R and R2 both as high as 0.99 in predicting the cooling load. As the developed prediction models were based on buildings characteristics, the outcomes of the research may be relevant to architects at the pre-design stage of heating and cooling energy-efficient buildings.

RE-EVALUATION OF THE EGYPTIAN CODE OF HOUSING AND ENERGY CONSUMPTION WITH EMPHASIS ON SHADING DEVICES ROTATION ANGLES

The passive system technique is dynamically used as an alternative to the active system, in order to minimize the peak loads and the total EUI in kWh/ m2 for any building prototype. Sun breaker or shading device is a basic traditional method and Mashrabiya previously used for privacy and reduces the heat gained and emitted from sun`s rays, in addition to the fabricated wood material and its specs of bad conductor. the study aims to investigate the effect of rotational shading devices around the y-axis, will the rotation have a significant impact on the EUI or not? The research methodology is built upon generative modeling tool of parametric design, Rhinoceros Version 6.0, with the cooperation of Grasshopper, Ladybug& Honeybee, and Toolbox. Five hundred running simulations are carried out to determine the optimal angle of rotation with maximum reduction in cooling loads, and the interpretation is 30°. Two linear regression equations are derived out of this valuable study to deduce the correlation between independent and dependent variables when the sun breaker material is matt or reflective, and how the total EUI kWh/m2 can be minimized?

System-Scale Modeling of a Building-Integrated, Transparent Concentrating Photovoltaic and Thermal Collector

The buildings sector is a principal contributor to global greenhouse gas emissions, but consistently falls short of targets for harnessing on-site energy resources towards sustainable operation. Emerging integrated solar technologies could transform buildings and urban settings into resilient, self-sufficient, and healthy environments. But if effects of these technologies are not understood in the multiple contexts in which they operate (human-scale, building-scale, district-scale), their potential is difficult to project. To explore building-scale metabolization of solar energy, a previously-developed analytical model of a Building Envelope-Integrated, Transparent, Concentrating Photovoltaic and Thermal collector (BITCoPT) was run to project electrical and thermal energy and exergy production (cogeneration) in a range of orientations and operating temperatures. Simulated annual cogeneration efficiency was noted at 27% (exergy) at an operating temperature of 55°C, and up to 55% (energy) at 25°C. Exergetic efficiency remained nearly constant as operating temperatures increased through 75°C, indicating the thermal energy collected would be some heat-engine-based applications. Although the scope of this study excludes broader architectural benefits of daylighting (lighting load reduction), and reduction of solar gains (cooling loads), these results suggest BITCoPT merits further investigation for on-site net-zero and energy-positive commercial building design, and might contribute to expanding net-zero and energy-positive architecture opportunities.