Special Issue "Sustainable Future-Proofing of Heating and Cooling in Buildings: Heat Pumps, Passive Measures, and Low-Carbon Interventions"

Dear Colleagues,

The latest IPCC report (Intergovernmental Panel on Climate Change, 2022) confirms the strong interactions of the natural, social and climate systems, and that human-induced climate change has caused widespread adverse impacts to nature and people. It is clear that across sectors and regions, the most vulnerable people and systems are disproportionately affected, and climate extremes have led to irreversible impacts. The assessment underscores the importance of limiting global warming to 1.5°C if we are to achieve a fair, equitable and sustainable world. One of the key contributors to increasing worldwide energy consumption is the service sector, which covers all types of buildings with a wide range of HVAC systems. The global energy consumption of the service sector has increased by 295 Mtoe in 2018 compared to 2000 levels, and with this trend, the sector would consume a further 323 Mtoe by 2040.

The increase in the global temperatures and carbon emissions, accompanied by recent geo-political developments, has triggered drastic measures by most governments to reduce the dependency of heating and cooling in buildings on fossil fuels. As a result, new policies are being introduced to boost technological advances, which could speed up the sustainable future-proofing of heating and cooling in buildings. We are at a critical point in history where we need to act decisively to encourage energy savings while protecting vulnerable households, and prepare smart energy programs.

This Special Issue of Sustainablity, “Sustainable Future-proofing of Heating and Cooling in Buildings: Heat Pumps, Passive Measures, and Low-Carbon Interventions”, is focused on new methodologies, low-carbon strategies and technologies, passive cooling and heating measures, and heat pumps to reduce the fossil fuel-reliance of heating and cooling in buildings. We invite researchers to contribute original research articles as well as review articles that will stimulate the continuing efforts to understand the recent advances and innovation in these research fields. Manuscripts combining experimental implementation with theoretical calculations and technoeconomic assessment are also welcome.  

Themes and topics for this Special Issue include:

• Sustainable transition to low-carbon heating and cooling in buildings;
• Passive measures to reduce demand and fossil fuel dependency in buildings;
• Low-energy cooling technologies and strategies;
• Technological advances in heat pump development;
• Solar-assisted and building-integrated heat pump technologies;
• Occupants’ comfort, health and wellbeing in a changing climate;
• Energy flexibility and resilience in the built environment;
• Personal comfort systems and other alternative low energy heating and cooling technologies;
• 2050 road maps and pathways to develop net-zero buildings.

Dr. Ali Badiei
Dr. Arash Beizaee
Dr. Jing Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• sustainable
• buildings
• heat pumps
• low-carbon
• low-energy
• passive
• flexibility
• resilience
• thermal comfort
• occupancy patterns
• alternative technologies

Title: Energy Schedule Setting Based on Clustering Algorithm and Pattern Recognition for Non-residential Buildings Electricity Energy Consumption in Guangdong, China
Authors: Yu Cui; Zishang Zhu *; Xudong Zhao *; Zhaomeng Li
Affiliation: Center for Sustainable Energy Technologies, Energy and Environment Institute, University of Hull, Hull HU6 7RX, UK
Abstract: Building energy modelling (BEM) is the key technology to achieve building energy conservation. Occupants’ energy-related behaviour is currently acknowledged as a significant and less understood impact factor in BEM. In practice, it is always simplified as varieties of fixed schedule settings in commonly used engineering energy modelling methods. The conventional fixed schedule setting method is more suitable for engineering simulation methods because it is easy to explain and adjust according to the real situation. However, targeted to recently popular data-driven BEM, fixed schedule setting brings high uncertainty to the model and further causes a large deviation between calculation result and real energy consumption. A novel schedule-setting method developed for data-driven BEM utilization should be more flexible and data-related. This paper systematically clusters a comprehensive building energy historical dataset in three different time scales to explore the energy usage profile patterns instead of the fixed schedule setting ruled by building regulation for data-driven energy consumption forecasting. K-medoids clustering with Principal Component Analysis (PCA) dimensional reduction and Dynamic Time Warping (DTW) distance measurement is applied to the dataset. According to the clustering result, a new schedule setting matrix is developed to compare with the default setting and calendar data in a single-layer neural network (NN) model (data-driven building energy prediction model). In conclusion, the Year-Month data is partitioned into two clusters; the Week-Day data is partitioned into three clusters; the Day-Hour data is partitioned into two clusters. Under the same temporal resolution, the schedule setting based on the clustering results performs much better on data-driven predictive models than the default schedule setting (25.7% improvement). Compared with the calendar data which has better resolution, the data-driven schedule setting is also more advantageous with a 9.2% improvement.

Title: Energy Saving Potential of Air-Side Economisers in Modular Data Centres: Analysis of Opportunities and Risks in Different Climates
Authors: Ali Badiei ^1,*; Eric Jadowski ²; Saba Sadati ³; Arash Beizaee ⁴; Jing Li ⁵; Leila Khajenoori ¹; Hamid Reza Nasriani ¹; Guiqiang Li ⁶; Xin Xiao ⁷
Affiliation:

1. School of Engineering, Faculty of Science and Technology, University of Central Lancashire, Preston, PR1 2HE, UK
2. Department of Engineering, Faculty of Science and Engineering, University of Hull, Hull, HU6 7RX, UK
3. School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M13 9PL, UK
4. School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough, LE11 3TU, UK
5. Centre for Sustainable Energy Technologies, Energy and Environment Institute, University of Hull, Hull, HU6 7RX, UK
6. Department of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei City 230026, China
7. School of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China

Abstract: Data centres’ Information Technology (IT) equipment can generate substantial amount of heat which must be removed to maintain efficiency and safe operation of the IT equipment. Typically, mechanical air conditioning and ventilation systems are used to remove the heat from data centre facilities to maintain their effective operation. This paper investigates the potential for using outside air for ‘free cooling’ utilising an air-side economiser to offset the energy required for mechanical cooling in modular data centres. Utilising Dynamic Thermal Modelling, a 90 kWh modular data centre is used as a base case for model validation and analysis of energy reduction potential from using an air-side economiser compared to traditional mechanical air conditioning systems, in four different climatic zones. The model was calibrated and empirically validated using Power Usage Effectiveness (PUE) values provided by the Open Compute project, and simulations were run for Stockholm, Dubai, San Francisco, and Singapore, representative of di-verse worldwide climates. The simulations predicted air-side economiser enables energy reduc-tions of up to 86% in moderate climates while in dry and hot climates no significant reduction was recorded. The findings provided insight into the complex relationship between modular data centres, their operation, and viability of utilising air-side economisers for free cooling and energy reduction in diverse climates.