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Nowadays, the load monitoring system is an important element in smart buildings to reduce energy consumption. Nonintrusive load monitoring (NILM) is utilized to determine the power consumption of each appliance in smart homes. The main problem of NILM is how to separate each appliance's power from the signal of aggregated consumption. In this regard, this paper presents a combination between particle swarm optimization (PSO) and artificial neural networks (ANNs) to identify electrical appliances for demand‐side management. ANN is applied in NILM as a load identification task, and PSO is used to train the ANN algorithm. This combination enhances the NILM technique's accuracy, which is further verified by experiments on different datasets like Reference Energy Disaggregation Dataset, UK Domestic Appliance‐Level ElectricityUK‐DALE, and Indian data for Ambient Water and electricity Sensing. The high accuracy of the proposed algorithm is verified by comparisons with state of the art methods. Compared with other approaches, the total mean absolute error has decreased from 39.3566 to 18.607. Also, the normalized root mean square error (NRMSE) method has been used to compare the measured and predicted results. The NRMSE is in the range of 1.719%–16.514%, which means perfect consistency. This demonstrates the effectiveness of the proposed approach for home energy management. Furthermore, customer behavior has been studied, considering energy costs during day hours. [ABSTRACT FROM AUTHOR]

There has been general recognition within the construction industry that there is a discrepancy between the amount of energy that buildings actually use and what designers considered that they should use. This phenomenon is termed “The Performance Gap” and is normally associated with new buildings. However, existing and older buildings contribute a greater amount of operational carbon. In response to the Performance Gap, CIBSE have developed the TM54 process which is aimed at improving energy estimates at design stage. This paper considers how the TM54 process can also be used to develop energy management procedures for existing buildings. The paper describes an exercise carried out for a university workshop building in which design energy use has been compared with the actual building energy use and standard benchmarks. Moreover, a sensitivity assessment has been carried out using different scenarios based on operation hours of building/equipment, boiler efficiency and impact of climate change. The analysis of these results showed high uncertainty in estimates of energy consumption. If carbon challenges are to be met then improved energy management techniques will require a more systematic approach so that facilities managers can identify energy streams and pinpoint problems, particularly where they have assumed responsibility for existing buildings which often have a legacy of poorly metered fuel consumption. [ABSTRACT FROM AUTHOR]

Building stock modelling usually deploys representative building archetypes to obtain reliable results of annual energy heating demand and to minimise the associated computational cost. Available methodologies define archetypes considering only the physical characteristics of buildings. Uniform occupancy schedules, which correspond to national averages, are generally used in archetype energy simulations, despite evidence of occupancy schedules which can vary considerably for each building. This paper presents a new methodology to define occupancy-integrated archetypes. The novel feature of these archetype models is the integration of different occupancy schedules within the archetype itself. This allows building stock energy simulations of national population subgroups characterised by specific occupancy profiles to be undertaken. The importance of including occupant-related data in residential archetypes, which is different than the national average, is demonstrated by applying the methodology to the UK national building stock. The resultant occupancy-integrated archetypes are then modelled to obtain the annual final heating energy demand. It is shown that the relative difference between the heating demand of occupancy-integrated archetypes and uniform occupancy archetypes can be up to 30%. [ABSTRACT FROM AUTHOR]

Highlights • Energy consumption in higher education institutions (HEIs) modelled. • For the first time, panel data used, with cross-sectional and time-series variations. • Over time and across HEIs, energy use increases as income and size increase. • Economies of scale as HEIs grow, but energy use still rising with sector growth. • Research universities more energy intensive. Abstract Among the various sustainability goals of higher education institutions (HEIs), reducing energy use and carbon emissions are particularly important. However, not much is known about energy demand from the higher education sector – especially since there is a lack of robust models of energy demand in this sector. This paper, the first to utilize a panel dataset and advanced panel econometric techniques in order to model energy use in higher education, investigates variations in energy use between HEIs (cross-sectional analysis), and also changes in energy use over time (temporal analysis), using the UK as a case study. We argue that panel dataset and methods are more useful for understanding growth (and reduction) in energy use within the HE sector than the methods used within previous cross-sectional studies. Results show that, over time and also across the sector, energy consumption in the HEIs increases with increases in income and floor space, but at a slower rate. As HEIs grow overall (in terms of income, floor space, student and staff number) over time, they become more 'energy efficient' (using less energy per unit of area, population or income), indicating economies of scale in the temporal dimension. Results also show that after controlling for income and size, research intensive HEIs consume more energy. We also find a small but statistically significant effect of energy prices on energy consumption, as might be expected. Simulation using the model parameters for an example scenario suggests that energy consumption will continue to increase unless there is a significant change in the policies driving income growth and spatial expansion in the HE sector in the UK. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of building fabric, services and occupant related factors on actual energy use of six case study dwellings, located in three new low energy social housing developments in UK, covering a variety of built forms and construction systems (timber frame, hempcrete, steel-frame). Physical monitoring of indoor environment and window-opening is cross-related with building fabric and systems’ performance, and qualitative data gathered through occupant surveys, review of control interfaces and handover guidance, to understand the causes of the gap between modelled and measured energy use. Actual energy use is found to exceed design expectations by a factor of three, questioning the need for whole-house mechanical ventilation heat recovery (MVHR) systems at measured air permeability rates of 6 m³/(h.m²) against the design target of 3 m³/(h.m²). Lack of proper commissioning of MVHR and heating systems, combined with inadequate user comprehension about their operation and control leads to occupant ‘misuse’ wherein systems are de-activated, thereby negatively affecting indoor air quality. This is confounded by occupant factors related to higher demand temperatures, unexpected opening of windows during winters due to under-performance of MVHR combined with habitual behaviours, and over-use of heating systems to compensate for higher than expected air permeability. [ABSTRACT FROM AUTHOR]

This paper presents results of a research study into improving energy performance of small-scale district heat network through water supply and return temperature optimization technique. The case study involves establishing the baseline heat demand of the estate’s buildings, benchmarking the existing heat network operating parameters, and defining the optimum supply and return temperature. A stepwise temperature optimization technique of plate radiators heat emitters was applied to control the buildings indoor thermal comfort using night set back temperature strategy of 21/18 °C. It was established that the heat network return temperature could be lowered from the current measured average of 55 °C to 35.6 °C, resulting in overall reduction of heat distribution losses and fuel consumption of 10% and 9% respectively. Hence, the study demonstrates the potential of operating existing heat networks at optimum performance and achieving lower return temperature. It was also pointed out that optimal operation of future low temperature district heat networks will require close engagement between the operator and the end user through incentives of mutual benefit. [ABSTRACT FROM AUTHOR]

In the UK, 20% of houses were built before 1919 and are protected from energy efficiency requirements that would unacceptably alter their character. To meet carbon emission reduction targets, however, it is necessary to keep the number of buildings exempt from energy efficiency improvements to a minimum. The need to preserve the aesthetic and structural qualities of historic buildings makes energy retrofit complicated and costly but these arguments should not be used to resist change. The research presented in this paper investigates how conservation professionals in the UK approach and sanction energy retrofit measures in historic buildings. It provides an overview of the current UK legislation and guidance relating to energy efficiency in heritage buildings and presents findings from a study focused on the approach of conservation professionals to retrofit slim profile double glazing (SPDG). It finds that there is regional variation to energy retrofit in historic buildings between Scotland and the rest of the UK, and that individual conservation professionals hold different views on the use of SPDG, which leads to inconsistencies in its application. Recommendations are made for a more consistent approach to window upgrade as a means of improving the energy efficiency and comfort of historic buildings and for greater interdisciplinary cooperation to align conservation of energy with conservation of heritage. [ABSTRACT FROM AUTHOR]

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

This paper presents a systematic, socio-technical and empirical evaluation of the actual energy and environmental performance of a sustainably-designed institutional building (Southeast England), intended to be a teaching tool and ‘living laboratory’ of sustainability. Despite the building being designed to high sustainability standards (Energy Performance Certificate rating of A, low reliance on fossil fuels, natural ventilation and rainwater harvesting) and also being under-utilised during the in-use stage (lower hours of occupation and number of occupants), its actual energy-related carbon dioxide-equivalent emissions are four times more than predicted. This is due to poor energy management of the building, underperformance of the biomass boiler and wasteful energy practices in terms of excessive winter overheating in the atrium, inappropriate lighting controls, and electrical equipment being left on standby. Due to lack of training and understanding of the energy manager, the building management system was not used adequately and issues with installation, commissioning and maintenance of the biomass boiler led to its disuse; however the photovoltaic system generated electricity as expected. Findings from the study show how a mixed-methods approach of building performance evaluation (BPE) should be embedded as part of the build process, to ensure that performance outcomes are met in reality. [ABSTRACT FROM AUTHOR]

• Implementation of a model predictive control scheme for HVAC systems is presented. • The hardware/software solution is generalisable to most building management systems. • Cloud solutions can offer low-cost, scalable control in commercial buildings. • Economic MPC reduced energy usage by 1.7% compared to baseline control. • Building thermal performance strongly affects viability of MPC schemes. Many businesses are looking for ways to improve the energy and carbon usage of their buildings, particularly through enhanced data collection and control schemes. In this context, this paper presents a case study of a food-retail building in the UK, detailing the design, installation and cost of a generalisable model predictive control (MPC) framework for its Heating, Ventilation and Air Conditioning (HVAC) system. The hardware/software solution to collect relevant data, as well as the formulation of the MPC scheme, is presented. By utilising cloud-based microservices, this approach can be applied to all modern building management systems with little upfront capital, and an ongoing monthly cost as low as $6.39/month. The MPC scheme calculates the optimal temperature setpoint required for each Air-Handling Unit (AHU) to minimise its overall cost or carbon usage, while ensuring thermal comfort of occupants. Its performance is then compared to the existing legacy controller using a simulation of the building's thermal behaviour. When simulated across two months the MPC approach performed better and achieved the same thermal comfort for a lower overall cost. The economic optimisation resulted in an energy saving of 650 kWh, with an associated cost savings of $240 (an improvement of 1.7% compared to the baseline), while the carbon optimisation gave negligible CO 2 savings due to the inability of the building to shift heating to low-carbon periods. Findings from this study indicate the potential for improving building performance via MPC strategies, however the level of impact will depend on specific building attributes. [ABSTRACT FROM AUTHOR]

Electricity consumption in the administration buildings of a typical higher education campus in the UK accounts for 26% of the campus annual electricity consumption. A reliable forecast of electricity consumption helps energy managers in numerous ways such as in preparing future energy budgets and setting up energy consumption targets. In this paper, we developed two models, a multiple regression (MR) model and a genetic programming (GP) model to forecast daily electricity consumption of an administration building located at the Southwark campus of London South Bank University in London. Both models integrate five important independent variables, i.e. ambient temperature, solar radiation, relative humidity, wind speed and weekday index. Daily values of these variables were collected from year 2007 to year 2013. The data sets from year 2007 to 2012 are used for training the models while 2013 data set is used for testing the models. The predicted test results for both the models are analyzed and compared with actual electricity consumption. At the end, some conclusions are drawn about the performance of both models regarding their forecasting capabilities. The results demonstrate that the GP model performs better with a Total Absolute Error (TAE) of 6% compared to TAE of 7% for MR model. [ABSTRACT FROM AUTHOR]

Short-term building energy consumption forecasting is vital for energy conservation and emission reduction. However, it is challenging to achieve accurate short-term forecasting of building energy consumption due to its nonlinear and non-stationary characteristics. This paper proposes a novel hybrid short-term building energy consumption forecasting model, SSA-CNNBiGRU, which is the integration of SSA (singular spectrum analysis), a CNN (convolutional neural network), and a BiGRU (bidirectional gated recurrent unit) neural network. In the proposed SSA-CNNBiGRU model, SSA is used to decompose trend and periodic components from the original building energy consumption data to reconstruct subsequences, the CNN is used to extract deep characteristic information from each subsequence, and the BiGRU network is used to model the dynamic features extracted by the CNN for time series forecasting. The subsequence forecasting results are superimposed to obtain the predicted building energy consumption results. Real-world electricity and natural gas consumption datasets of office buildings in the UK were studied, and the multi-step ahead forecasting was carried out under three different scenarios. The simulation results indicate that the proposed model can improve building energy consumption forecasting accuracy and stability. [ABSTRACT FROM AUTHOR]

• New building development projects underperform often. • Underperformance leads to increased energy consumption and CO 2 emissions in building operation. • The paper links building project development and building operational performance. • Two simulation methods are combined in a multi methodology framework in the paper. • The paper explores the implications of project partner collaboration for operational building performance in the case of a recent building project. The "performance gap" in the United Kingdom construction industry is a persistent problem as new building development projects underperform more often than not. The "performance gap" is partially attributed to the number of stages involved in building project development and the coordination difficulties of partners with different incentives. The project outcome is important for energy consumption, carbon emissions and occupant well-being. Thus, it is important to study the project management process in terms of the standard time, cost and quality parameters, but also in terms of project partner incentives and coordination, and the subsequent energy performance and resultant indoor environmental conditions. A system dynamics model of project management processes is developed to explore the implications of partner coordination for building quality. The system dynamics model is coupled to a building performance simulation model to explore building energy consumption and Indoor Environmental Quality, and apply this on a recent building project case study. Results show that greater project partner alignment can reduce annual energy consumption up to 12% and CO 2 emissions up to 37%, with greater emphasis in the design stage of the project subject to resource availability. The trade-offs involved on value appropriation are considered and discussion of results points to possible ways for improvement. [ABSTRACT FROM AUTHOR]

• A switchable photovoltaic window based on thermotropic hydrogel is developed. • Selected hydrogel can reversibly switch between highly transmissive and scattering states. • The window performance is evaluated by indoor and outdoor experiments. • This window can passively control daylighting and heat gain during hot sunny days. • This window offers better electrical performance than conventional PV glazing. Daylighting control technologies have become an essential part of sustainable building design to reduce overheating, glare and energy consumption in buildings. In this paper, a smart glazing system where a Building Integrated Photovoltaic (BIPV) glazing is coupled with an optically switchable thermotropic hydrogel layer is proposed to improve the daylighting control and electricity generation performance of traditional BIPV glazings. Thermotropic (TT) hydrogels made of various weight percentage combinations of hydroxypropyl cellulose (HPC) polymer, gellan gum and sodium chloride (NaCl) salt were synthesised and first evaluated by visible-near-infrared spectroscopy. Subsequently, small-scale prototypes of the proposed BIPV thermotropic (BIPV-TT) laminated glazing based on these TT hydrogels were fabricated and characterised experimentally under controlled laboratory conditions. The TT hydrogel, which was synthesised of 6 wt% HPC, 0.5 wt% gellan gum and 4.5 wt% NaCl, was selected for further experimental characterisations in a dynamic outdoor environment, due to its appropriate transition temperature of 30.7 °C for use in mild climates with a wide modulation range of solar transmittance from 85.8% (in the transparent state) to 9.6% (in the light-scattering state). The outdoor tests were conducted in Nottingham, the UK, on typical summer days with sunny and partial cloudy conditions. The results showed that using the prototype BIPV-TT laminated glazing can reduce up to 80% of the solar radiation transmitted into the outdoor test cell, while providing up to 12% higher electrical power outputs, compared to its counterpart system with no thermotropic hydrogel applied. [ABSTRACT FROM AUTHOR]

Abstract: An archetypal simulation model of office building representing variability in UK office building stock by parameterising built form, construction elements, occupancy/usage and operational/control strategy has been developed thus enabling detailed energy performance simulation to be used for stock modelling and parametric studies. The paper discusses the building characteristics needed to be considered for energy performance simulation, their values, and how they can be used in parametric studies. These parameters include built forms, fabrics (including thermal mass and insulation positioning), glazing percentages and characteristics, daylight and solar control measures and activity and operational related parameters (heating and cooling set points, ventilation rate, occupancy density and metabolic rate, equipment and lighting gain). The default parameter values suggested for the archetypal simulation model reflect typical existing and currently proposed UK office building stock. An archetypal model, combined with parametric studies, can be used in assessing energy performance of building stock and evaluating adaptation/retrofitting strategies. [Copyright &y& Elsevier]

Abstract: This paper examines the efficiency (in terms of energy use and carbon emissions) with which 5 different types of domestic water heating systems employed in the UK are able to produce hot water for sanitary use. A method of normalisation is employed allowing results from case studies with different systems and usage levels to be compared. Water heating appliances studied include gas boilers, a micro CHP, heat pumps, an immersion heater, and a solar thermal system. It is found that instantaneous production of hot water is much more efficient than delivery via tank storage for gas-fuelled systems. For electrical systems, an immersion heater is found to perform better in some circumstances than heat pumps and also has advantages when combined with a solar thermal system leading to the proposal that this combination offers the most potential as a low carbon method for domestic hot water provision in the long term. Opportunities are identified to improve the performance of all systems with storage through better control of heat inputs. Inconsistencies in, and problems of compliance with, established standards for mitigation of Legionella in hot water systems are also identified. [Copyright &y& Elsevier]

Abstract: Following the Japanese Cool Biz campaign which advocated relaxed dress codes and cooling set-points of 28°C in air-conditioned public buildings, other countries have introduced similar policies, with temperature limits varying in different countries. In the UK the British Council for Offices suggested that the summer cooling set-points of UK air-conditioned offices should be increased by 2°C from the previously recommended 22±2°C. However, these recommendations are largely supported by desk-based analysis rather than using field studies. This paper presents the findings of a blind, controlled intervention study conducted in the summer of 2010 in an office building in London to investigate the effects of increasing the current cooling set-point to 24°C. The temperature of one floor was changed and compared with a ‘control’ floor where the set-point remained unchanged. The indoor air temperatures were measured at various locations across the floors to monitor the temperatures the occupants were experiencing. The BUS post-occupancy evaluation survey was used to assess occupants’ self-reported comfort and satisfaction, whilst the NEP questionnaire was used to estimate occupants’ environmental attitudes. The findings from statistical analyses of the data collected for all 129 participants suggest that increasing the set-point temperature led to the occupants feeling significantly warmer in comparison with the group at lower temperature settings. Nevertheless, this did not affect the self-reported thermal comfort of the occupants in the intervention group, as depicted by an insignificant difference between the two groups. It was also observed that there is a positive correlation between the occupants’ tolerance of higher indoor air temperatures and their environmental attitudes, indicating that this could play a key role in the acceptance of indoor temperature changes in the UK. [Copyright &y& Elsevier]

• Effects of multi-zone heating systems in residential buildings are assessed. • Data obtained from 336 scenarios in Mediterranean climates are evaluated. • Results are evaluated under economic and energy criteria. This paper explores the effects of multi-zone heating systems in residential buildings in different Mediterranean climates. The aim is to evaluate their potential in residential sectors to provide a general basis from the results (from the energy and economic point of view). In addition, if feasible, a further detailed evaluation of this management strategy for optimising the energy use in residential buildings would also be carried out. To do so, the effects of two different zoning controls in different types of apartment, occupancy patterns, building characteristics and locations in Spain, have been assessed. Different combinations of these parameters have resulted in 336 different scenarios that have been dynamically simulated using Design Builder software. The obtained energy results have been analysed in detail. Moreover, an economic analysis of these results has also been carried out to evaluate the economic feasibility of these systems in residential buildings located in temperate climates. This has been calculated by evaluating the maximum investment that can be assumed in each scenario to achieve different payback periods (namely 10 and 20 years). The results obtained show that these systems could be a cost-effective strategy aimed at reducing the energy consumption in residential buildings, not only in cold climates, such as is shown in the literature (the majority of the studies found are located in the UK and northern countries), but also in more temperate climates, such as that of Spain. Savings of around 20% were obtained in the most usual scenarios in Spain (coherent with results obtained in previous studies in the UK found in the literature), showing that in several cases, the initial investment in zone-controlled systems could be paid off in less than ten years, especially in large apartments and the coldest weather conditions. [ABSTRACT FROM AUTHOR]