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The aim of this study is to present a novel data-driven approach developed for space heating energy demand calculation of the whole EU building stock. To develop a computationally efficient bottom-up model that takes into account building physics parameters and details of the building stock make-up, an artificial neural network (ANN) is trained on a dataset of precise building-physics models. For this purpose, 2025 building energy simulations were performed in this study, ensuring...

With increasing energy consumption, how to achieve the energy-saving operation of air-conditioning systems is crucial for improving the energy efficiency of buildings. The accurate and reliable energy consumption prediction of air-conditioning systems can be useful for optimizing the energy supply and equipment operation strategies. However, most existing studies focus on the prediction of the long-term energy consumption of air-conditioning systems, which usually exceeds the individual...

Climate change is the greatest challenge of the 21st century. It is threatening all aspects of societal life. The right to education of children is negatively impacted by these climate-induced challenges. This chapter presents findings of a study on the effects of climate change on the education of the younger generation. The study used a mixed research design method and was done within Kisii Municipality, Kenya. The findings were that climate change and its effects have brought about...

The effects of climate change are a major global concern. In Kenya, the impact of climate change has been felt in perennial droughts which sometimes result into conflict as communities fight for pasture and water. In a bid to address climate change issues, Kenya has developed policies that focus on mitigation and adaptation measures borrowed from ideas outlined in global climate change strategies. One such strategy is the employment of education as a tool to create awareness on climate...

With the increasing incidence of power blackouts attributed to climate change, climate-resilient load forecasting is increasingly necessary to enable timely network reconfiguration during extreme weather events. This paper proposes a generalised multi-factor Deep Learning (DL) model to forecast electricity load in Distribution Networks (DNs) during extreme climate periods. We optimise factors that affect forecast accuracy, including input matrix structures, calendar effects, and...

With the increasing incidence of power blackouts attributed to climate change, climate-resilient load forecasting is increasingly necessary to enable timely network reconfiguration during extreme weather events. This paper proposes a generalised multi-factor Deep Learning (DL) model to forecast electricity load in Distribution Networks (DNs) during extreme climate periods. We optimise factors that affect forecast accuracy, including input matrix structures, calendar effects, and...

Deep learning models have been increasingly applied in the field of solar radiation prediction. However, the characteristics of a deep learning black box model restrict its application in practical scenarios such as model predictive control. Because energy system controllers may be unable to make final decisions based solely on the predictions of a black-box model. This study considers both the temporal and spatial dependencies of solar radiation predictions through unfolding sequences and...

Individuals globally spend about 88–92% of their entire time in the indoor environment. The implementation of regularly scheduled systems operation is common in many commercial and residential building types. Occupant Behavior (OB) is highly stochastic, making it difficult to depict the human factor using simple schedules. In the present work, window-opening tendencies were found to be highest in summer and transition seasons and lowest during winter. The Air Changes per Hour (ACH) value...

This qualitative study aims to investigate the outlook of geography educators in Pakistan. It involves a group of around twelve participants, primarily aiming to understand their viewpoints regarding the goals of climate change education; it also explores how these viewpoints influence their teaching approaches, especially when dealing with contentious topics in geography education. The research delves into the complex educational landscape related to climate change education in Pakistan....

The farmer field school (FFS) has been promoted as an approach for educating farmers on making adaptive farming decisions. In Malawi, the FFS has been used to enhance food security within the context of adaptation to climate change. Monitoring, evaluation and learning (MEL) extends the learning cycle from the core of the FFS to the project level to facilitate learning and adaptation for improvement of interventions. This study’s objectives were to test the utility of a MEL framework for the...

Solar shading devices, such as Venetian blinds, are effective in controlling heat and light gain in buildings. This study focuses on developing an Artificial Neural Network (ANN) to automate the management of Venetian blinds in order to find a balance between energy savings and visual comfort. Typically, automatic control strategies rely on cut-off angles or maintaining appropriate indoor illuminance. However, finding the optimal trade-off between solar gain and daylight is challenging,...

Due to climate change, the intensity, duration and frequency of heatwaves are likely to increase in the coming years. Excessive heat events can increase local urban heat island intensity affecting the health and wellbeing of urban dwellers vulnerable to heat stress. Heat-Health Warning Systems (HHWSs) have been developed to warn the public of impending heat events and to advise on preventable negative health outcomes. However, metrics upon which action triggers are made in HHWSs rely on...

Due to climate change, the intensity, duration and frequency of heatwaves are likely to increase in the coming years. Excessive heat events can increase local urban heat island intensity affecting the health and wellbeing of urban dwellers vulnerable to heat stress. Heat-Health Warning Systems (HHWSs) have been developed to warn the public of impending heat events and to advise on preventable negative health outcomes. However, metrics upon which action triggers are made in HHWSs rely on...

Model-based optimal control has proven its effectiveness in optimizing the performance of central air-conditioning systems in terms of thermal comfort and energy efficiency. It was often assumed that temperature distribution in the entire air-conditioned space is uniform and can be represented by a single or averaged measurement in optimization. However, actual distribution in the air-conditioned space is usually uneven, which can affect thermal comfort and indoor air quality. The dynamics...

In an increasingly digital world, there are fast-paced developments in fields such as Artificial Intelligence, Machine Learning, Data Mining, Digital Twins, Cyber-Physical Systems and the Internet of Things. This paper reviews and discusses how these new emerging areas relate to the traditional domain of building performance simulation. It explores the boundaries between building simulation and these other fields in order to identify conceptual differences and similarities, strengths and...

Abstract Enhancing community capacity towards resilience is key to reducing climate disaster risk, especially in Black immigrant communities in Canada. While there are many extreme climate change events occurring, such as hailstorms, floods, snowstorms, forest fires, droughts, and heat waves in western Canada, there is no known study that has explored resilience within sub‐Saharan African immigrant communities to climate disaster risks in western Canada. All these extreme climate change...

Teachers’ personal beliefs and understanding about science topics play a vital role in students learning. This is especially relevant for the teaching of climate change which is a scientifically complicated topic that can also be influenced by personal and political views. Semi-structured interviews were conducted with thirteen Pakistani chemistry teachers (grades 10 & 12) to understand their knowledge about the science of climate change as well as their beliefs and practices related...