Building retrofit is an important facet in the drive to reduce global greenhouse gas emissions. However, delivering building retrofit at scale is a significant challenge, especially in how to automate the process of building surveying. On-site survey by expert surveyors is the main approach in the industry. This can lead to a high workload if planning retrofit at a large-scale. An advanced vehicle-mounted data capturing system has been built to collect urban environmental multi-spectral data. The data contains substantial information that is essential in identifying building retrofit needs. Although the data capturing system is able to collect data in a highly-efficient manner, the data analysis is still a big data challenge to apply the system into delivering building retrofit plans. In this paper, a street-view building facade image segmentation model is designed as the foundation of the holistic data analysis framework. The model is developed on the deep learning-based semantic segmentation technology and uses an ensemble learning strategy. The object detection technology is fused into the model as an magnifier to improve the model performance on small objects and boundary predictions. The model has achieved state-of-the-art levels of accuracy on a built street-view building facade image dataset.

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The need to accelerate the decarbonization of heating, as well as the rise of the ‘smart home’, mean that there is an increasing focus on the role of innovative consumer offerings in driving the shift to zero carbon domestic heating. In this context, Heat as a Service (HaaS) business models, which provide consumers with an agreed heating plan rather than simply paying for units of fuel, are receiving increased attention. This paper explores HaaS based on insights from facilitated group discussions with key stakeholders, and learning from HaaS trials, in the United Kingdom. Results identified evidence needs and research gaps related to: addressing issues of trust between consumers and suppliers, supportive policies, financing business models, and openness and interoperability of technology and data. Based on the findings, we propose policy and research recommendations to better understand the role of HaaS business models in decarbonization.

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Next-generation concentrated solar power (CSP) plants are expected to work above the current temperature limit of 565 °C for the benefit of enhanced efficiency. This poses significant challenges in the construction materials, among others, in terms of corrosion. In this work, we investigate the spray-graphitization method to improve the compatibility of SS310 and SS347 with molten Li2CO3-Na2CO3-K2CO3 carbonate salt. Improved compatibility was observed due to the formation of protective carbonate or carbide layers on SS347 and SS310 surfaces, respectively. Detailed characterization of the corrosion products, including chemical reactions and wettability allowed the mechanism of anticorrosion protection to be proposed, which could be used for other construction materials in direct contact with high-temperature molten salts for next-generation CSP plants and beyond.

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In this study, hiTRANTM wire matrix tube insert was used to improve the heat transfer deterioration of supercritical nitrogen (N2) in a heated tube caused by the effects of thermo-physical property variations and buoyancy force. Heat transfer experiments were carried out with N2 flowing upwardly in a vertical circular tube with and without the wire matrix insert under a sequence of experimental conditions including pressures of 35 and 40 bar, mass flow rate of 27.6 and 41.3 g/min and constant heat flux conditions at 6.8, 8.0 and 9.3 kW/m2, respectively. Experimental results show that N2 exhibits similar heat transfer behaviour when transiting across the pseudo-critical point as other fluids such as water and CO2. Due to the addition of the wire matrix insert, that intensified the overall fluid mixing in the test tube, the heat transfer performance of N2 was enhanced by more than 42% and up to 2.35 times while the pressure drop increase was negligible compared to the system inlet pressure. Moreover, it has been demonstrated that there might exist an optimum combination of experimental conditions leading to the maximum performance of the wire matrix insert. Furthermore, as the results show, with the Dittus-Boelter correlation and correlations for water and CO2 falling short of fitting the heat transfer data of N2, a heat transfer correlation, exclusively for N2 going through the pseudo-critical point is needed. The findings in this study also reveal that both supercritical N2 internal flow heat transfer and the use of wire matrix insert to enhance the deteriorated heat transfer of supercritical fluids are promising topics and require more significant attentions in future studies.

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Molten salts-based nanofluids have been widely considered for Thermal Energy Storage (TES) applications due to their enhanced thermophysical properties. However, the application of such fluids faces many challenges, among which are the correct determination of their properties, stability, compatibility with construction materials and the overall environmental impact. In this work, we attempt to provide a comprehensive analysis of nanofluids based on nano-alumina and molten carbonate salt for the benefit of next-generation high-temperature TES applications. In particular, considerable statistics, cross-verification, novel preparation and characterization methods were applied to record ~12% increase of thermal conductivity, ~7% increase of heat capacity and ~35% increase of viscosity. It was demonstrated that such nanofluids have poor dispersion stability under static conditions; however, the enhanced thermophysical properties can be maintained by mechanical stimuli, e.g. mixing or redistribution. We show that some nanoparticles interact with typical construction materials such as stainless steel 310 by forming mixed oxides and considerably reducing the corrosion rates. An erosion study has been performed demonstrating negligible effect of nanoparticles even in the case of their strong agglomeration. Finally, life cycle analysis revealed that viscosity and preparation method of such nanofluids must be targeted to minimize the environmental impact.

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This paper reviews the state-of-the-art knowledge of boiling heat transfer in binary mixtures with special emphasis placed on the heating and cooling industry. The advantage of using refrigerant mixtures over pure refrigerants include the enhancement of system coefficient of performance (COP), better match with the desired thermal load and being safer, more environmental-friendly refrigerants. In other words, the concept of using mixtures enables more flexible selection of suitable working fluids in particular thermal applications. The purpose of this review article aims to summarize the important published articles on boiling heat transfer in binary mixtures, as well as to identify limitations to existing studies, hereby providing guidelines, directing future studies and invoking further innovations of this well-established but still promising thermal management technique. The present article reviews straightforward on both pool boiling and flow boiling of binary mixtures in a systematic and comprehensive way. Specifically, in addition to the effects of fluid composition, heat flux, mass flux, pressure and heater surface condition, this article also reviews the effects of mass diffusion, heats from dilution and dissolution on pool boiling heat transfer of binary mixtures, along with the effects of flow orientation, flow regime and flow instability on flow boiling heat transfer of binary mixtures. Many papers reviewed herein relate to the heat transfer correlations towards boiling of binary mixtures.

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Calcium-based materials are considered to be promising heat storage methods for the upcoming 3rd generation concentrated solar power systems (CSP) due to their high operation temperatures and energy storage densities. However, pure calcium carbonate (CaCO3) particles suffer from poor solar absorptance and stability. In this work, we successfully enhance solar absorptance, cycle stability, and decrease decomposition temperature, simultaneously, based on proposed doped CaCO3 particles. A fabrication method, which is cheap and suitable for large scale applications, is proposed based on doping Al and Fe elements into CaCO3 powders via sol–gel processes. The average solar absorptance is enhanced by about 560%, and the energy storage density decay rate after 50 cycles is prominently reduced to be as low as 4.5% from 35.5%. The decomposition temperature is reduced by 15 to 24 K depending on the atmospheres, and the decomposition kinetics of both doped and pure CaCO3 particles is found to follow the equation of phase boundary controlled reaction. The activation energy increases only slightly after doping, but will have a sharp increase when switching the atmosphere from N2 to pure CO2. This work paves the way to the design of high-performance calcium-based materials for next-generation high temperature thermal energy storage system.

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The energy industry needs to take action against climate change by improving efficiency and increasing the share of renewable sources in the energy mix. On top of that, refrigeration, air conditioning , and heat pump equipment account for 25-30% of the global electricity consumption and will increase dramatically in the next decades. However, some waste cold energy sources have not been fully used. These challenges triggered an interest in developing the concept of cold thermal energy storage, which can be used to recover the waste cold energy, enhance the performance of refrigeration systems, and improve renewable energy integration. This paper comprehensively reviews the research activities about cold thermal energy storage technologies at sub-zero temperatures (from around −270°C to below 0°C). A wide range of existing and potential storage materials are tabulated with their properties. Numerical and experimental work conducted for different storage types is systematically summarized. Current and potential applications of cold thermal energy storage are analysed with their suitable materials and compatible storage types. Selection criteria of materials and storage types are also presented. This review aims to provide a quick reference for researchers and industry experts in designing cold thermal energy systems. Moreover , by identifying the research gaps where further efforts are needed, the review also outlines the progress and potential development directions of cold thermal energy storage technologies.

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Publicly available electrical generation and interconnector data is combined to create a half-hourly dataset for Great Britain's electrical demand. The method uses Elexon data for power plants connected at the transmission level, monitored as part of the balancing mechanism, and combines these with the estimates for embedded generation for solar and wind generation from the system operator National Grid. The resulting dataset therefore has both transmission connected and distribution connected generation. Finally, to arrive at a closer representation of Great Britain's demand rather than its generation, the net imports are calculated from summing the values of all imports and exports. The resulting dataset termed ESPENI (Elexon Sum Plus Embedded Net Imports) keeps within 11 per cent of the official quarterly values from BEIS, which include auto generation that is not publicly available. The datasets are presented in both a cleaned and raw form and have been parsed to provide UTC and local time columns to be more easily utilised by a wider group of researchers.

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Thermal energy storage (TES) technologies have been traditionally classified into sensible, latent and thermochemical categories. TES needs significant research efforts to address some fundamental challenges to reach its full potential. The hybridisation of TES technologies provides potentially a highly effective solution to the challenges. We present here a new concept, the 3 in 1 system, examining the feasibility, and the applied aspects of the newly proposed technology. The 3 in 1 system integrates the three known thermal storage methods of sensible heat, latent heat and thermochemical based TES into one system, providing three different operational configurations with cascading, charging integrated and discharging integrated working conditions. These different configurations offer controllability of TES charge/discharge processes while enhancing system-level efficiency. The proof of concept consists of a co-working matrix of a polymer as the phase change material (PCM), high-density polyethylene, and one of the most studied thermochemical material (TCM), MgSO4·7H2O. The feasibility of the composite containing 80–90 wt% of TCM was studied, over 15 cycles, for mechanical integrity, stability, energy stored and reaction kinetics. The results show that the system has a great potential for storing heat, up to 2 GJ∙m−3 and offers a wide working temperature range, from 30 °C to ∼150 °C. The combination of the PCM/TCM pairs give the composites mechanical integrity while accommodating the volume change and maintaining the structural stability during thermal cycling. This novel idea addresses some key technology gaps in TES particularly degradation and hence short life-span of TCM, cost-effectiveness and flexibility of the TCM based technology, thus offers potential paradigm shift to the thermal energy storage technology.

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This paper presents a building-level analysis of almost 600,000 houses in London, using EPC data alongside 3DStock, a new highly detailed urban model. Focussing on the building envelope (specifically roofs, walls and glazing), the paper examines the current condition of the stock, as well as the opportunities for improving energy efficiency as defined by the EPC recommendations. Using highly detailed building level data, the areas of single-glazed windows, uninsulated walls, and poorly insulated lofts are quantified across the sample. It also examines the magnitude of this low-efficiency envelope that is not currently recommended for improvement in the EPCs. Finally, the paper estimates the total retrofit potential for houses in London.

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In Brazil, the delivery of homes for low-inc ome households is dictated by costs rather than performance. Issues such as the impact of climate change, affordability of operational energy use, and lack of energy security are not taken into account, even though they can severely impact the occupants. In this work, the authors evaluated the thermal performance of two affordable houses as-built and after the integration of envelope improvements. A new replicable method to evaluate the cost-effectiveness of these improvements was proposed. The case study houses comprise the most common affordable housing type delivered widely across Brazil and a proposition of a better affordable housing solution, built in Porto Alegre, southern Brazil, integrating passive design strategies to increase thermal comfort. The findings reveal a potential for improving indoor thermal conditions by up to 76% and 73%, respectively, if costs are not a concern, and 40% and 45% with a cost increase of 12% and 9% if a comfort criterion of 20–25 °C was considered. Equations to estimate costs of improvements in affordable housing were developed. The authors concluded that there is a great scope for building envelope optimisation, and that this is still possible without significant impact on budget.

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In this study, an experimental setup is developed to assess the thermal performance of a compact Latent Heat Thermal Energy Storage System (LHTESS) prototype during the charging/discharging stages. The LHTESS consists of a shell and horizontally oriented multi-tube heat exchanger and a commercially available paraffin wax RT44HC, which has a phase change temperature between 41°C and 43 °C as the energy storage medium. The testing campaign evaluated the influence of several operating conditions including the heat transfer fluid (HTF) volume flow rate and inlet temperature on the LHTESS power input and output, melting and solidification time and the energy stored and released. From the experimental results, it was observed that increasing the HTF inlet temperature has a significant effect on charging time compared to changing the HTF volume flow rate. When the LHTESS was charged using a fixed HTF inlet temperature of 60 °C, the charging process period took 296.3 min, 233.5 min, 204.8 min and 197.8 min when the HTF volume flow rate is 3.0, 4.5, 6.0 and 7.5 L/min. However, when the LHTESS was charged at HTF volume flow rate of 4.5 L/min, the results show that the charging completion time for HTF inlet temperatures of 55°C, 60 °C and 65°C are 316.6, 233.5 and 209.67 min, respectively. The results from the experimental analysis showed that the discharge time was significantly longer than the charging time due to an ever-growing layer of solid PCM around the external surface of heat exchanger throughout the discharging process which reduces the heat transfer coefficient between the PCM and HTF. This did not change substantially with the changing HTF volume flow rate.

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Effective control of energy storage system (ESS), supplying an ancillary service to a grid, requires effective and critical calculation of state‐of‐charge (SoC). Charging and discharging values from battery operations are essential in calculating the efficiency and performance of a storage system. This information can also be a key to understand and forecast peak demand performance. Missing data is a real problem in any operations system, and it appears to be more common within powers systems due to sensor and/or network malfunctioning problems. Missing data imputation techniques have evolved in power systems research using smart meter data, but little research has gone into understanding how missing data can be best handled within storage management systems. This paper builds on a year's worth of charging and discharging data collected from a real 6MW/10MWh lithium‐ion storage battery deployed on the distribution network at Leighton Buzzard, UK. Using R Studio version (1.3.959‐1) open‐source software, eight selected imputation techniques were applied in identifying the best suited technique in replacing various missing data amounts and patterns. Findings from the study open up avenues for discussion and debate in identifying an appropriate imputation technique within the storage management context. The study also provides a pioneering lead in understanding the importance of decomposition in evaluating the right imputation technique.

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The decarbonisation of residential building stock in the UK requires accessible tools that can reliably and rapidly model residential building power demands as a function of multiple low carbon technologies and building control schemes. Whilst a variety of modelling tools exists, these platforms are either intended for expert analysts, are not suited to rapid simulation (and therefore cumbersome at stock modelling scale) or are not flexible enough to allow analysis of detailed active control schemes. This work builds on a previously developed dynamic domestic building modelling tool developed in MATLAB/Simulink environment and intended for rapid generation of electrified heat demand profiles in buildings. The number of parameter inputs and time-resource required to prepare EWASP tool is several order of magnitude smaller than an equivalent EnergyPlus model, computational efficiency of this tool as well as its prediction accuracy are benchmarked against an equivalent E+ model. The EWASP model required 13 times less parameter input, reducing analyst time requirement and human effort. Both models produced similar trends of loads against external climatic changes for a Passivhaus case-study fabric while overall EWASP generated smaller ASHP electrical loads (4.4 kWh·m 2 ·yr) than EnergyPlus model (5.8 kWh·m 2 ·yr) which will be examined in future works. EWASP tool can assist assessment of the impact of fabric or HVAC retrofit and design and control scenario in buildings on the local distribution network and wider power grid

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The dataset includes the bibliographic information for all literature retrieved from the associated systematic literature search. The following information are included - which searches were used to acquire the literature, the ability to download the literature and the classification of the literature following the abstract review. The dataset summarizes the literature searches that were completed on December 16, 2019.

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Dataset for the journal paper "Towards Active Buildings: rating grid-servicing buildings", which describes the simulations for the 20 case study buildings. The simulation inputs describe the intended characteristics as part of the early design stage process, and the outputs the performance metrics under the rating system introduced in the journal paper, called the ABCode1. Such outputs rate the relative merits of each case study in terms of embodied carbon, energy requirements, energy generation and energy flexibility.

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Temporary urbanism is an approach to reactivate urban spaces through short-term interventions in a range of urban contexts. In central São Paulo, the Luz and Santa Ifigênia neighbourhoods, characterized by deprivation of their physical environments and social structures, were the focus of this investigation. The Mungunzá Container Theatre and the General Osório Square, located within these neighbourhoods, were selected as case studies. Whilst the thermal performance of the container theatre itself was the main interest, in the case of the Square the fundamental issue was the environmental noise. The objective was to identify adequate strategies to improve environmental conditions in these locations in order to enhance positive social impact, and, then, contribute to the regeneration of these neighbourhoods. This research was based on fieldwork and analytical procedures of thermal and acoustic performances. In the container theatre building, the adoption of external shading and wider openings for ventilation reduced its indoor peak temperatures and delivered thermal comfort during the warmest period of the year. In the Square, sound absorber road surface material and an acoustic shell were proposed to reduce noise and promote better acoustic quality for outdoor performances.

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Cyber‐Physical Systems (CPS) and Internet‐of‐Things (IoT) plus energy are the enabling technology of modern power systems also known as the Smart Grid (SG). A SG may consist of thousands of interconnected components communicating and exchanging data across layers that stretch beyond technical capabilities, for instance, markets and customer interactions. Cyber‐physical security is a major source of concern due to the high reliance of the SG on Information and Communication Technologies (ICT) and their widespread use. Addressing security requires developing modelling and simulation tools that approximate and replicate adversarial behaviour in the SG. These tools have in fact two simulators, one handling continuous power flows and another for capturing the discrete behaviour when communicating across CPS or IoT components. The technique of composing two models of computation in a global simulation of these coupled systems is called co‐simulation. Although there are many frameworks and tools for co‐simulation, the set of features for modelling cyber‐physical security incidents in the SG lacks thorough understanding. We present a systematic review of features and tools for co‐simulating these concerns in CPS. We also highlight and discuss research gaps with respect to the most used tools in industry and academia and comment on their relevant features.

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A brief history is provided of models of energy use in the UK building stock, with the focus on the non-domestic sector. This history leads to an account of the development, since 2009, of the 3DStock method for modelling complete building stocks, both domestic and non-domestic. The paper explains how 3DStock models are built and the data sources used. Special emphasis is placed on the relationship of premises (the floorspace occupied by organisations) to buildings. Energy use may be metered at the level of premises, buildings or groups of buildings. Representing the patterns in which premises relate to buildings is therefore crucial to the modelling process, and in particular to the precise measurement of energy intensities. Applications of 3DStock models in building science and policy tools are reviewed, including the London Building Stock Model (LBSM), delivered to the Greater London Authority (GLA) in 2020. This ‘digital twin’ can be used for the monitoring, simulation and analysis of the building stock. Implications for research and policy are discussed, particularly for energy epidemiology, density, high-rise buildings, retrofit potential, energy-use intensity and benchmarking. Data are in place to extend 3DStock modelling to the whole of England and Wales.

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The London Building Stock Model, commissioned by the Greater London Authority (GLA) contains detailed data on every separate domestic and non-domestic building in Greater London. It includes three dimensional information about buildings including their heights, volumes, wall areas, floor areas and the distribution of activities between different floors. These data are drawn from University College London Energy Institute’s existing 3DStock model of London. Within the model information is attached on the ages of buildings, their materials of construction, and (in some cases) their servicing systems. Energy Performance Certificates (EPCs) and Display Energy Certificates (DECs) are also attached to premises and dwellings along with gas and electricity energy consumption. Buildings in London are responsible for over 65% of the total carbon dioxide (CO2) emissions attributed to the Greater London region in 2016. Reducing CO2 emissions that can be attributed to buildings is the key focus of this work in line with the GLA’s ambition to dramatically reduce these overall CO2 emissions; aiming to make London a zero-carbon city by 2050. Improving the energy performance of existing buildings has to be a key strategy if the overall CO2 emissions are to be reduced. Knowing the characteristics and current energy efficiency of the building stock is the first step towards reducing direct and indirect CO2 emissions from these buildings. Collecting the data is one challenge, but making sense of these huge quantities of data is a bigger challenge. Structuring the data can help here and so for this paper we present the evaluation of energy efficiency of buildings in London using urban density to aggregate the data. Energy efficiency is measured from both EPCs and energy consumption. Some of the existing measures that might influence current energy efficiency are then shown at different levels of urban density. Finally, in order to address the improvement of the energy efficiency we quantify the ‘potential’ improvements of these buildings (according to the EPC recommendations) and hence the suitability of different retrofit solutions, again aggregated by urban density. The results show that energy use intensity decreases as urban density increases; that urban density has some influence on existing efficiency measures and finally that most of the measures of retrofit potential change with increasing urban density.

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With the recent removal of the solar PV feed-in tariff on ≤4 kWp arrays, installation of domestic rooftop PV has become significantly less commercially feasible in the UK. Whilst alternative trading schemes are beginning to emerge, the adequacy of their return on investment is questionable. However, the extent to which installation may need to be subsidised has not yet been quantified. Furthermore, the extent to which increased peer-to-peer trading could contribute to network constraints, and the environmental and economic costs of managing such schemes, have not been examined extensively. In this paper, the subsidy required to encourage a rooftop PV uptake rate of 0.5% homeowners/year is determined and the costs of constraint management are calculated for various network topologies. The problems presented are solved using time series analysis, power flow simulations, and optimisation processes with Monte Carlo methods. It was found that P2P trading is the most promising post subsidy revenue stream, reducing the required feed-in tariff from £0.14 to £0.10 for systems installed in 2020. Furthermore, it was found that with P2P trading, requirement for feed-in tariff support should end by 2032. Reconductoring was the most economically effective constraint management strategy, costing £50 k to £200 k less than curtailment when applied to 29 networks over 30 years. From an environmental perspective, it was found that reconductoring had a carbon footprint 2 orders of magnitude lower than curtailment & battery storage.

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Alongside a mean global rise in temperature, climate change predictions point to an increase in heat waves and an associated rise in heat-related mortality. This suggests a growing need to ensure buildings are resilient to such events. Unfortunately, there is no agreed way of doing this, and no standard set of heatwaves for scientists or engineers to use. In addition, in all cases, heat waves are defined in terms of external conditions, yet, as the Paris heat wave of 2003 showed, people die in the industrialised world from the conditions inside buildings, not those outside. In this work, we reverse engineer external temperature time series from monitored conditions within a representative set of buildings during a heat wave. This generates a general probabilistic analytical relationship between internal and external heatwaves and thereby a standard set of events for testing resilience. These heat waves are by their simplicity ideal for discussions between clients and designers, or for the setting of national building codes. In addition, they provide a new framework for the declaration of a health emergency.

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Globally, a primary concern is whether green office buildings perform as promised in terms of providing better indoor environment quality (IEQ) for employees, which may affect their satisfaction and work performance. In the Middle East, although there has been renewed interest in green building design, post occupancy evaluation of performance has never been conducted to-date, and evidence of actual occupant perception in green and non-green buildings is still ambiguous. Hence, we present the first study on IEQ performance in the Middle East. We show that Jordan can be taken as a representative example and systematically compare five “green” office buildings (representing 71% of all green-certified office buildings) against eight comparable conventional office buildings (CBs). Detailed bi-lingual survey data on perceived IEQ (n = 502) and work performance are accompanied by high-resolution continuous physical measurements of air temperature + relative humidity (n = 83) and CO2 concentrations (n = 21) with periodic measurements of mean radiant temperature and air speed, covering two typical summers and one typical winter. Results show both buildings types comply with design standards for indoor CO2 levels, while thermal comfort in green buildings is better than in CBs. However, CBs have a higher overall occupant satisfaction of IEQ. Work performance measured as absolute and relative absenteeism was slightly higher in CBs, with no significant differences in relative and absolute presenteeism between the two buildings types. These findings challenge the notion that green buildings improve occupant satisfaction and work performance over CBs and suggest the need for a better understanding of the performance-satisfaction gap.

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The disparity between disciplinary approaches to bioinspired innovation has created a cultural divide that is stifling to the overall advancement of the approach for sustainable societies. This paper aims to advance the effectiveness of bioinspired innovation processes for positive benefits through interdisciplinary communication by exploring the epistemological assumptions in various fields that contribute to the discipline. We propose that there is a shift in epistemological assumptions within bioinspired innovation processes at the points where biological models derived from reductionist approaches are interpreted as socially-constructed design principles, which are then realized in practical settings wrought with complexity and multiplicity. This epistemological shift from one position to another frequently leaves practitioners with erroneous assumptions due to a naturalistic fallacy. Drawing on examples in biology, we provide three recommendations to improve the clarity of the dialogue amongst interdisciplinary teams. (1) The deliberate articulation of epistemological perspectives amongst team members. (2) The application of a gradient orientation towards sustainability instead of a dichotomous orientation. (3) Ongoing dialogue and further research to develop novel epistemological approaches towards the topic. Adopting these recommendations could further advance the effectiveness of bioinspired innovation processes to positively impact social and ecological systems.

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Buildings contribute a significant portion of global greenhouse gas emissions and have the potential for large-scale impact reductions. Reducing the whole-life impacts of buildings is critical for creating a net-zero carbon built environment. For this to be achieved, the whole-life carbon impacts of design decisions must be considered during the building design process. A systematic review of academic literature was conducted to assess how life cycle assessment (LCA) is incorporated at various stages of the building design process, and what improvements are needed to support net-zero carbon design. The review compiled 274 papers that were published up to the end of 2019, of which 108 were subject to detailed review following screening. The review found that LCA is generally used late in the design process, when it is too late to greatly influence the design. Incorporating LCA with either building information modelling or life cycle costing is seen to have the same challenges as undertaking a traditional LCA. Parametric methods show promise for design development, but tools and algorithms require further verification and regionalisation to be implemented throughout industry. The use of benchmarks, target values and other pre-populated information can be used to incorporate life-cycle thinking without the need to undertake a detailed LCA. The review has demonstrated that LCA continues to face barriers, in both methods and practice, preventing its ability to guide early-stage design decisions and have a large impact on the environmental performance of buildings.

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In most industrialized countries, the buildings sector is the largest contributor to energy consumption and associated carbon emissions. These emissions can be reduced by a combination of energy efficiency and the use of building integrated renewables. Additionally, either singularly or as a group, buildings can provide energy network services by timing their use and production of energy. Such grid-aware or grid-responsive buildings have been termed Active Buildings. The recent UK Government investment of £36m in the Active Building Centre is a demonstration that such buildings are of considerable interest. One problem with the concept, however, is that there is no clear definition of Active Buildings, nor a building code to design or research against. Here we develop and test an initial novel code, called ABCode1. It is based on the need to encourage: (i) the minimisation of energy consumption; (ii) building-integrated generation; (iii) the provision of grid services; and (iv) the minimisation of embodied carbon. For grid services, we find that a lack of a precise, quantifiable measure, or definition, of such services means that for the time being, theoretical hours of autonomy of the building is the most reasonable proxy for these services within such a code.

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The Smart Grid (SG) is a Cyber-Physical System (CPS) considered a critical infrastructure divided into cyber (software) and physical (hardware) counterparts that complement each other. It is responsible for timely power provision wrapped by Information and Communication Technologies (ICT) for handling bi-directional energy flows in electric power grids. Enacting control and performance over the massive infrastructure of the SG requires convenient analysis methods. Modelling and simulation (M&S) is a performance evaluation technique used to study virtually any system by testing designs and artificially creating 'what-if' scenarios for system reasoning and advanced analysis. M&S avoids stressing the actual physical infrastructure and systems in production by addressing the problem in a purely computational perspective. Present work compiles a non-exhaustive list of tools for M&S of interest when tackling SG capabilities. Our contribution is to delineate available options for modellers when considering power systems in combination with ICT. We also show the auxiliary tools and details of most relevant solutions pointing out major features and combinations over the years.

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Cyber-Physical Systems (CPS) are present in many settings addressing a myriad of purposes. Examples are Internet-of-Things (IoT) or sensing software embedded in appliances or even specialised meters that measure and respond to electricity demands in smart grids. Due to their pervasive nature, they are usually chosen as recipients for larger scope cyber-security attacks. Those promote system-wide disruptions and are directed towards one key aspect such as confidentiality, integrity, availability or a combination of those characteristics. Our paper focuses on a particular and distressing attack where coordinated malware infected IoT units are maliciously employed to synchronously turn on or off high-wattage appliances, affecting the grid's primary control management. Our model could be extended to larger (smart) grids, Active Buildings as well as similar infrastructures. Our approach models Coordinated Load-Changing Attacks (CLCA) also referred as GridLock or BlackIoT, against a theoretical power grid, containing various types of power plants. It employs Continuous-Time Markov Chains where elements such as Power Plants and Botnets are modelled under normal or attack situations to evaluate the effect of CLCA in power reliant infrastructures. We showcase our modelling approach in the scenario of a power supplier (e.g. power plant) being targeted by a botnet. We demonstrate how our modelling approach can quantify the impact of a botnet attack and be abstracted for any CPS system involving power load management in a smart grid. Our results show that by prioritising the type of power-plants, the impact of the attack may change: in particular, we find the most impacting attack times and show how different strategies impact their success. We also find the best power generator to use depending on the current demand and strength of attack.

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As Internet of Things (IoT) technologies enable greater communication between energy assets in smart cities, the operational coordination of various energy networks in a city or district becomes more viable. Suitable tools are needed that can harness advanced control and machine learning techniques to achieve environmental, economic and resilience objectives. In this paper, an energy management tool is presented that can offer optimal control, scheduling, forecasting and coordination services to energy assets across a district, enabling optimal decisions under user-defined objectives. The tool presented here can coordinate different sub-systems in a district to avoid the violation of high-level system constraints and is designed in a generic fashion to enable transferable use across different energy sectors. The work demonstrates the potential for a single open-source optimisation framework to be applied across multiple energy vectors, providing local government the opportunity to manage different assets in a coordinated fashion. This is shown through case studies that integrate low-carbon communal heating for social housing with electric vehicle charge-point management to achieve high-level system constraints and local government objectives in the borough of Greenwich, London. The paper illustrates the theoretical methodology, the software architecture and the digital twin-based testing environment underpinning the proposed approach.

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In this study, the thermal performance of latent heat thermal energy storage system (LHTESS) prototype to be used in a range of thermal systems (e.g., solar water heating systems, space heating/domestic hot water applications) is designed, fabricated, and experimentally investigated. The thermal store comprised a novel horizontally oriented multitube heat exchanger in a rectangular tank (forming the shell) filled with 37.8 kg of phase change material (PCM) RT62HC with water as the working fluid. The assessment of thermal performance during charging (melting) and discharging (solidification) was conducted under controlled several operational conditions comprising the heat transfer fluid (HTF) volume flow rates and inlet temperatures. The experimental investigations reported are focused on evaluating the transient PCM average temperature distribution at different heights within the storage unit, charging/discharging time, instantaneous transient charging/discharging power, and the total cumulative thermal energy stored/released. From the experimental results, it is noticed that both melting/solidification time significantly decreased with increase HTF volume flow rate and that changing the HTF inlet temperature shows large impacts on charging time compared to changing the HTF volume flow rate. During the discharging process, the maximum power output was initially 4.48 kW for HTF volume flow rate of 1.7 L/min, decreasing to 1.0 kW after 52.3 min with 2.67 kWh of heat delivered. Based on application heat demand characteristics, required power levels and heat demand can be fulfilled by employing several stores in parallel or series.

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‘Community Energy’ refers to people working together to reduce and manage energy use and increase and support local energy generation. It has the potential to support the infrastructural, social and cultural changes needed to reduce the impact of climate change and increase energy security. The core part of community energy initiatives is people; therefore, successful engagement strategies are essential. SCENe (Sustainable Community Energy Networks) was a research and development project focused on community energy application in a real-world setting involving in its first phase 44 new homes built along the banks of Nottingham’s River Trent (UK). The project team adopted a variety of established and innovative engagement strategies including website and social media channels, an online platform, a physical community energy hub where meetings and workshops were held and an interactive virtual energy model could be accessed, and in-home smart voice-controlled and visual technologies. The influence of the project and the effectiveness of the engagement tools to generate behaviour changes were investigated through a survey, workshops and interviews. The results suggest that engagement with SCENe increased awareness of energy issues and supported wider participation in community initiatives.

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Airtightness refers to the amount of air leakage through a building’s envelope. This uncontrolled exchange of air between inside and outside, either infiltration or exfiltration, may lead to thermal discomfort. Nevertheless, little or no attention has been given to airtightness in some countries including Brazil. In Brazil, a range of different strategies are suitable to achieve thermal comfort depending on the several climatic regions. In those regions where winter conditions are noticeable, such as in São Paulo, airtightness is a key parameter, but it has been historically overlooked. In this work, the authors deployed the innovative Pulse test methodology to determine airtightness levels for the first time in Brazil, in the city of São Paulo. Three representative multifamily residential buildings dating from the 1970s, 1980s and 2000s were measured, and the results’ values widely ranged from 1 to 5.7 h−1, at 4 Pa. Next, dynamic building simulations were conducted using measured and representative airtightness values (converted to infiltration) to understand the contribution of this variable on the thermal comfort. The results suggested that up to 9% improvement in the thermal comfort levels could be achieved by adopting 1 h−1 as maximum infiltration, and up to 14% by adopting 0.5 h−1.

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The measures to control the spread of COVID-19 are unparalleled, and this is already having an effect on Britain’s energy system. There have been massive short-term changes in the past: for instance the temporary imposition of a three-day week in the 1970s may have had an even greater overall effect, but this was due to industrial action in the coal sector affecting the supply of energy. This time, the disruption is on the demand side – the energy is still available, but the demand for it has reduced.

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In 2010, Great Britain generated 75% of its electricity from coal and natural gas. But by the end of the decade*, these fossil fuels accounted for just 40%, with coal generation collapsing from the decade’s peak of 41% in 2012 to under 2% in 2019.

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Martin Mayfield (University of Sheffield) explains the importance of Urban Scale Digital Twins for providing a holistic approach to urban and infrastructure design, operation and future proofing.

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Data collection is a fundamental component in the study of energy and buildings. Errors and inconsistencies in the data collected from test environment can negatively influence the energy consumption modelling of a building and other control and management applications. This paper addresses the gap in the current study of missing data treatment. It presents a comparative study of eight methods for imputing missing values in building sensor data. The data set used in this study, are real data collected from our test bed, which is a living lab in the Newcastle University. When the data imputation process is completed, we used Mean Absolute Error, and Root Mean Squared Error methods to evaluate the difference between the imputed values and real values. In order to achieve more accurate and robust results, this process has been repeated 1000, and the average of 1000 simulation is demonstrated in this paper. Finally, it is concluded that it is necessary to identify the percentage of missing data before selecting the proper imputation method, in order to achieve the best result.

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Within the context of the Smart City, the need for intelligent approaches to manage and coordinate the diverse range of supply and conversion technologies and demand applications has been well established. The wide-scale proliferation of sensors coupled with the implementation of embedded computational intelligence algorithms can help to tackle many of the technical challenges associated with this energy systems integration problem. Nonetheless, barriers still exist, as suitable methods are needed to handle complex networks of actors, often with competing objectives, while determining design and operational decisions for systems across a wide spectrum of features and time-scales. This review looks at the current developments in the smart energy sector, focussing on techniques in the main application areas along with relevant implemented examples, while highlighting some of the key challenges currently faced and outlining future pathways for the sector. A detailed overview of a framework developed for the EU H2020 funded Sharing Cities project is also provided to illustrate the nature of the design stages encountered and control hierarchies required. The study aims to summarise the current state of computational intelligence in the field of smart energy management, providing insight into the ways in which current barriers can be overcome.

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