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• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

This paper provides a review of the literature concerning the impact of temporarily increased cooling setpoint temperature on occupant thermal comfort during demand response (DR) events in commercial, air-conditioned buildings. We address concerns regarding thermal comfort as it relates to zone temperature modifications that may be implemented as a part of DR measures. Increased zone setpoint temperatures during the cooling season can adversely affect building occupants physically and psychologically, and impair their perceived indoor air quality and self-estimated performance. In some cases, however, improved occupant thermal comfort due to warmer zone setpoint temperatures during DR events has also been reported. In order to reduce the negative impacts on building occupants, DR must be implemented with careful control and monitoring. There are significant differences in assumptions made about the way people would respond to a thermal environment between the static heat balance model and the adaptive approach, with the adaptive approach offering a wider range of acceptable indoor temperatures. Therefore, application of the adaptive approach could be one option to improve building energy performance by taking advantage of occupant adaptive behaviors during DR events. Depending on the building services and systems available, expectations of the occupants, and the control options they are given to adjust to their thermal environment, occupants could potentially adapt to temperatures higher than what are currently being practiced in buildings. However, an upper limit threshold for temperature modifications, even if temporary ones, must be recognized to minimize adverse impacts on building occupants prior to DR implementation. Therefore, the ideal goal would be to develop menthods that would identify an optimum balance between energy consumption and the building occupant thermal comfort before applying DR strategies. Prior review papers relevant to DR have generally concentrated on the energy saving potential alone, or where energy savings have been prioritized over occupant thermal comfort. This paper reviews implementation of DR from the perspective of occupant thermal comfort and presents a summary of the most relevant experimental and field studies regarding occupant thermal comfort during DR events in commercial, air-conditioned buildings. [ABSTRACT FROM AUTHOR]

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

In a traditional building design process (TDP), design variables are fixed sequentially, as opposed to integrated design process (IDP) which tends to avoid sequential design phases to create more sustainable buildings. First, a reference building is introduced and an energy model based on TRNSYS is presented to determine the energy consumption and comfort in the building. The model is validated based on energy bills, certified simulations and literature. Then, the paper performs an extended sensitivity analysis (SA) of 30 design variables with respect to different performance criteria related to energy consumption and comfort, based on a TRNSYS model. Three SA techniques were used, namely standard regression coefficients (SRC), partial rank correlation coefficients (PRCC) and Sobol indices. Results show that all three techniques yielded a similar ranking of the importance of the variables for most model outputs. Interactions between variables were identified with second-order Sobol indices. In the second part of this paper, a traditional design framework was adopted in which sets of variables were fixed sequentially. A SA was performed at each phase of the process, assuming fixed values for parameters chosen in previous design phases. Results show that fixing variables during the phases of a traditional design process tends to reduce the probabilities of finding low-energy consumption designs. Moreover, the influence of some variables was found to change during the design phases. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two modules were analyzed during Antarctic summer at Spanish research station. • Measured transmittances and infiltrations were excessively high, resulting in high energy consumption for heating. • Indoor air conditions were poor in both modules, particularly the CO 2 concentration. • Extreme weather conditions accelerated the degradation of insulating materials and sealants. • Energy efficiency standards are urgently needed to improve the carbon footprint of Antarctic bases. In this paper, we present the energy characterization of two habitable modules at the Spanish station "Gabriel de Castilla", located on Deception Island, Antarctica. The analysis includes profiles of energy consumption for space heating and domestic hot water, as well as indoor air conditions, which were all recorded during one month of Antarctic summer. Additionally, the measurement of walls' transmittance and air infiltrations, together with thermography analysis, enabled evaluating the conservation state of the buildings' envelope. Upon analyzing all this data, it is evident that there is potential to enhance the design of future modules, improving the thermal comfort while significantly reducing the energy consumption. This will contribute to decrease the logistics and environmental impacts of these research stations, crucial considerations in human activity on the Antarctic continent. [ABSTRACT FROM AUTHOR]

In times of great transition of the European construction sector to energy efficient and nearly zero energy buildings (nZEB), a market observation containing qualitative and quantitative indications should help to fill out some of the current gaps concerning the EU 2020 carbon targets. Next to the economic challenges, there are equally important factors that hinder renovating the existing residential building stock and adding newly constructed high performance buildings. Under these circumstances this paper summarises the findings of a cross-comparative study of the societal and technical barriers of nZEB implementation in 7 Southern European countries. The study analyses the present situation and provides an overview on future prospects for nZEB in Southern Europe. The result presents an overview of challenges and provides recommendations based on available empirical evidence to further lower those barriers in the European construction sector. The paper finds that the most Southern European countries are poorly prepared for nZEB implementation and especially to the challenge/opportunity of retrofitting existing buildings. Creating a common approach to further develop nZEB targets, concepts and definitions in synergy with the climatic, societal and technical state of progress in Southern Europe is essential. The paper provides recommendations for actions to shift the identified gaps into opportunities for future development of climate adaptive high performance buildings. [ABSTRACT FROM AUTHOR]

Modern cities and their architectural structures undergo significant functional and physical changes. In recent years, the interventions on building envelopes have increased. Therefore, it is necessary to analyse potential remodeling of glass facades, along with applying the concept of smart technologies, in order to increase energy efficiency of the existing buildings. This paper analyses the modernization process of devastated glass façade of the tall Slavija hotel, built in 1960s in Belgrade, Serbia, taking into consideration some positive examples of transformation and reskinning of buildings, where the aspect of medialization is an active part of urban renewal. The subject of this paper is the analysis of research findings about the improved thermal comfort of this building, after performing the replacement of its glass façade and converting the hotel building into an office building. Special attention was paid to the implementation of media technologies and final effects on energy balance of the newly designed facade. The proposed solution is supposed to evaluate the improved thermal comfort that was achieved by a radical renovation of the facade and by replacing the existing facade with a new single façade (double and triple glazed units), with media elements as well as without them. The research results are presented as proposals for improving EE public buildings by implementing the latest system of curtain walls in order to increase the value of the buildings. One of the most important criteria included in the process of energy refurbishment is technological improvement of the existing buildings, along with the presentation of media facades. The case study is based on EnergyPlus simulations. [ABSTRACT FROM AUTHOR]

• Climate change's impact on retrofitting was tested on Le Corbusier's apartment. • Climate change scenarios project up to 70% increase in summer overheating. • Adaptive natural ventilation can reduce warm discomfort of 50–60%. • Adaptive setpoints can reduce total energy consumption of 20–30%. • Adaptive strategies are particularly favourable in historic buildings. Historic buildings, often exempt from retrofits to preserve originality, require retrofitting due to potential future climate-related indoor issues. For Modern Architecture constructions, there is a need to find solutions that help address the discomfort and heat losses caused by the extensive use of glazing. By analysing Le Corbusier's studio-apartment this paper aims to inspect: (i) Solutions for energy, Indoor Environmental Quality, and preservation; (ii) Climate change impact on them; (iii) Possible adaptation strategies to cope with climate change. Spectrally selective glazing reduced summer overheating by 15%; high-performance glazing lowers cold discomfort (24%) and heating (22%) but increased warm discomfort; shadings maintained energy use and reduced summer discomfort by up to 44%; thermal insulation can reduce winter discomfort and halves energy use but raised summer discomfort by up to 41%. Tests on 2050–2100 climate change scenarios reveal up to 70% more warm discomfort hours. Adaptive strategies can help, with natural ventilation cutting warm discomfort by 50–60%, and adaptive setpoints reducing cooling demand by about 35%. Adaptive strategies can complement traditional retrofitting in addressing current and future climate conditions, especially in historic buildings that require minimal interventions to preserve their historical characteristics and enhance resilience. [ABSTRACT FROM AUTHOR]

Traditional air-conditioning systems are energy intensive and contribute to higher operational costs especially in summer. This paper examines and compares the performance of two cooling systems in a room: one with a cooling tower connected thermally activated building system (TABS) combined with a fan coil unit (FCU), and the other with a conventional inverter split air-conditioner (AC). Natural ventilation adversely affected indoor air temperatures in TABS room while integrating FCU operation reduced the temperature by 5 °C and AC provided the most comfortable temperature. Thermal comfort survey of three occupants showed significant inconsistencies with Fanger model particularly for TABS with FCU and TABS without ventilation cases, as occupants felt comfortable indicating the positive effect of only sensible cooling. Energy consumption studies show that TABS in closed condition and with natural ventilation as the most energy efficient with AC being least efficient of the four systems. In terms of overall comfort and energy consumption for continuous operation throughout the day, TABS integrated with FCU was deemed the best option. [ABSTRACT FROM AUTHOR]

• An optimization algorithm is developed for determining optimal flexible workplaces. • The thermal comfort models in the objective function are learned from personal data. • The optimization allows a customized trade-off between thermal comfort and energy consumption. • The algorithm is verified using both collected data and the ASHRAE database. Due to distinct preferences across individuals, a large proportion of people are not satisfied with the thermal environments of their workplaces. Although recent studies have investigated flexible workplaces to meet the different preferences of individuals, the feasibility of adopting them to real-world environments is limited by the room capacity and potential for extra energy consumption. To address the knowledge gaps, this paper proposes a framework to jointly optimize thermal comfort and energy consumption of buildings through flexible workplaces by considering personal thermal preferences. A joint optimization algorithm that integrates building energy and personal thermal comfort models is developed based on the concept of the Large Neighborhood Search (LNS) algorithm. Analytical energy prediction models are obtained through Nonlinear Polynomial Regression (NPR) and personal thermal comfort models are established using Support Vector Machine Models (SVM). To verify the algorithm, a case study considering two scenarios (with and without existing personal thermal comfort data) is presented. The results indicate the proposed optimization algorithm can significantly improve the thermal comfort of the occupants while saving 22% and 14 % of energy consumption in the two scenarios, respectively. The proposed optimization method is valuable for building managers while adopting the concept of flexible workplaces. [ABSTRACT FROM AUTHOR]

[Display omitted] • nZEBs in Eastern Europe lack carbon neutrality metrics and targets. • Performance requirements for nZEBs in Eastern Europe are presented. • Eastern Europe needs strategy and local governance for nZEB market penetration. • EPCs require major reform, and effective monitoring of nZEB performance is needed. • The cost-optimality calculation method must be adopted to ensure cost-effective market uptake. The European Unions' ambition for the construction sector is to be carbon neutral by 2030 for new construction. Since 2021, all new buildings in the EU should have been constructed as nearly zero-energy buildings (nZEB). However, Eastern European countries struggle to implement the 2018 Energy Performance of Building Directive recast requirements. Next to the economic challenges, equally essential factors hinder renovating the existing residential building stock and adding newly constructed high-performance buildings sourced primarily from renewable energy sources. Therefore, this study provides a cross-study to identify the barriers to nZEB implementation in ten Eastern European countries, including Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia. The study was conducted between 2019 and 2021 and provides an overview of prospects for nZEB in Eastern Europe. The study examines the challenges of nZEB plans faced in those countries and provides constructive recommendations. The regulations and definitions regarding nZEB energy performance, cooling and heating energy demand, thermal comfort, onsite renewables, and construction quality were analyzed. Results show that most Eastern European countries are unprepared to comply with the EPBD guidelines and cost-optimality approach. The paper ranks each country and recommends specific measures to refine the nZEB definitions. The paper provides a thorough comparative assessment and benchmarking of select EU geography that can help shift the identified gaps into opportunities for the future development of climate-neutral high-performance buildings. [ABSTRACT FROM AUTHOR]

• Households change their heating patterns when they switch to a heat pump. • Typically, a setback temperature 2–5 °C lower than the desired thermostat setting. • We calculate the increase in heat demand with varied parameters. • The increase in heat demand is determined by heat loss and thermal mass. • This would be a useful metric for 'heat pump readiness'. Heating with air source heat pumps is an important step in the transition to Net Zero Carbon for many households. When predicting the resulting energy consumption it is frequently assumed that heating demand is unchanged from before the switch from gas heating. However, heating patterns usually change, with a net increase in heating demand to achieve the same level of thermal comfort. This paper discusses the change in pattern and uses modelling to determine the resulting increase in energy demand. It shows that the increase can be predicted with information about dwelling heat loss and thermal mass as well as weather and the pre and post switch heating pattern. The increase can be 20% or more for homes with high heat loss. It proposes that the metric for heating demand increase would be a useful measure of heat pump readiness, and that the parameters required to assess this should be provided on energy performance certificates. [ABSTRACT FROM AUTHOR]

Providing the occupants with tailored feedback on their energy consumptions can be an effective method to help the users to adopt energy-efficient behaviours. However, in specific contexts such as the social housing, this may be challenging, due to the peculiarities and the economic constraints of the end-users, which make them vulnerable and needing a proper design of the information. Nevertheless, there is a lack of detailed studies in the literature analysing the effects of personalized energy feedback on the space heating consumption and the indoor air temperatures in the social housing sector. This paper aims to evaluate the effects on space heating consumption and indoor air temperature of a personalized feedback campaign delivered in three social housing buildings consisting of 27 apartments in Mediterranean climate. To this end, a personalized feedback campaign was designed and developed, providing for the use of disaggregated energy consumption indicators to show the location of excessive thermal energy consumptions. The daily thermal energy consumptions, as well as the indoor air temperatures of the single dwellings, were monitored daily for over four heating seasons and their variations were analysed before and after the implementation of the personalized feedback. A saving in normalized natural gas consumption of the buildings was found on average equal to −14,8% after the feedback campaign, with no significant variations in the indoor air temperatures. However, some critical issues have been highlighted in the response of individual end-users to the feedback provided. A greater propensity of the occupants to regulate the indoor air temperature through the thermostatic radiator valves in the unoccupied rooms of the house was also observed after the occurrence of the feedback campaign. [ABSTRACT FROM AUTHOR]

In HVAC systems, the application of fault detection and diagnosis (FDD) for chillers has brought many benefits to building utilities, i.e., indoor thermal comfort, energy saving, and energy consumption management. Although recent studies have achieved great progress on chiller fault diagnostic problem, some serious issues have been raised in these studies and need to be resolved comprehensively. In that context, two problems are listed and studied in this paper namely outliers detection and the insufficiency of labeled data. To deal with outliers mixed in chiller data, this paper proposes a supervised multiclass deep autoencoding Gaussian mixture model (S-DAGMM) algorithm which is an ensemble model of individual unsupervised DAGMMs. This mechanism helps S-DAGMM to detect ambiguous outliers in both training and testing data. In addition, this paper proposes to use DAGMM to pretrain a deep neural network (DNN). Since DAGMM can learn the data distribution from the unlabeled data, it can prevent DNN from getting stuck on local optima. Comprehensive experimental results in this study have proved the outstanding performance of the proposed approach, compared with state-of-the-art rival methods. [ABSTRACT FROM AUTHOR]

This paper evaluates through experimental testing a prototype of switchable insulated shading (SIS) systems suitable for windows to optimize solar heat gains in order to maintain indoor thermal comfort. Specifically, the paper describes a laboratory testing procedure and measurement results for SHGC values specific to various SIS designs and operation settings using a box calorimeter set-up. The SIS prototype can modulate continuously its optical and thermal properties including U-value and SHGC using rotating insulation layers controlled through an actuator to a specific slate angle setting. The results of the experimental testing confirm that SHGC value for the SIS prototype is correlated to the slate angle of the insulated layers. This correlation remains applicable for any SIS insulation thickness. The measured data are used to assess the potential energy efficiency benefits from SIS when applied to windows for US homes. In particular, a prototypical housing unit located in three US cities is considered to evaluate the energy efficiency potential for switchable opaque insulated shading systems. The results indicate that SIS systems can achieve up to 8.3%, 11.3%, and 11.4% in annual HVAC energy consumption compared to no-shading cases for dwellings located in Golden, CO (representing a cold climate), Phoenix, AZ (representing a hot climate), and San Francisco, CA (representing a mild climate), respectively. [ABSTRACT FROM AUTHOR]

Highlights • Lack of a clear path in the fight against energy poverty across the European union. • Energy poverty related to the residential sector allows new solutions to be developed. • Current energy poverty indicators provide an incomplete analysis of vulnerability. Abstract The term energy poverty (EP), mostly used to capture problems related to an inadequate access to energy suppliers in developing countries, and that of fuel poverty (FP), commonly employed when households suffer from insufficient monetary resources to pay for their basic energy needs, are used interchangeably by many researchers. Energy poverty and/or fuel poverty are considered to be an indication of domestic energy deprivation or energy vulnerability and remain a global problem that has been accentuated in Europe due to the economic crisis. This work has made a comprehensive review of the current concepts and indicators of FP, and of current initiatives to tackle this issue, across Europe, thereby raising the discussion of how energy vulnerability factors fit FP situations: available infrastructure, energy efficiency, social and economic poverty, and wellbeing and health. In this context, the first weak spot of the FP indicators and initiatives analyzed is that most factors that influence the everyday activities of a household are not considered (comfort, health, and wellbeing), resulting in an incomplete analysis if these are used in an isolated way. This paper provides a multiple-indicator approach to understand an FP situation beyond its traditional definition, thereby establishing a starting point for the reflection of vulnerability in policy decisions and methodological implications. [ABSTRACT FROM AUTHOR]

Highlights • Non-intrusive techniques are proposed to infer occupancy from existing HVAC sensors. • Reheat energy use is reduced by more than 38% with better nighttime setback schedules. • Derived a comprehensive set of candidate anomalous zones using unsupervised learning. • Proposed approach can be readily applied to any commercial building with a BMS. Abstract The Heating Ventilation and Air Conditioning (HVAC) system of commercial buildings traditionally runs on a fixed schedule that does not take occupancy into account despite its huge variation over space and time, thereby wasting a lot of energy in conditioning empty or partially-occupied spaces. Occupancy information is essential to eliminate wasteful energy use with imperceptible impact on building operations and human comfort. This paper investigates the application of non-intrusive techniques to obtain a rough estimate of occupancy from coarse-grained measurements of sensors that are commonly available through the building management system. Various static and adaptive energy-efficient schedules are developed based on this approximate knowledge of occupancy at the level of individual zones. Our experiments in three large commercial buildings confirm that the proposed techniques can uncover the recurring occupancy pattern of the zones, and schedules that incorporate these occupancy patterns can achieve more than 38% reduction in reheat energy consumption while maintaining indoor thermal comfort. [ABSTRACT FROM AUTHOR]

The optimization of energy consumption in buildings' HVAC systems plays a crucial role in reducing greenhouse gas emissions worldwide. In new and deeply-renovated buildings, characterized by modulating terminal units and aiming at the maximum exploitation of renewables, an accurate hydraulic balance of the distribution network may become critical, resulting in a significant increase of pumping energy consumptions and a deterioration of indoor thermal comfort conditions. In the present paper, we compare the performance of traditional manual balancing valves and new pressure independent control valves (PICVs), used to balance the hydronic loop of HVAC systems. To perform this analysis, a new MATLAB-Simulink model has been specifically developed to simulate the behavior of PICVs and has been used in an application case study. The efficiency of manual and pressure independent control valves is evaluated numerically by simulating a multi-zone distribution network under variable operating conditions and considering different control strategies of the circulating pump. Results show that in off-design conditions, when some of the branches of the hydraulic network are closed, traditional manual balancing valves are not able to guarantee the nominal mass flow rate in the remaining loops. On the contrary, no significant variations of water mass flow rate are observed when PICVs are adopted, even in partial load conditions. Despite their additional cost, PICVs allow to ensure better indoor thermal comfort sensations for individuals, avoiding under/over-heating of rooms and, moreover, yield a decrease of the pump electric consumption with respect to traditional manual balancing valves. In addition, based on the obtained results, general rules concerning the adoption of PICVs are provided, depending on the extension of the hydraulic loop and the adopted pump control logic. The reported results highlight the role that PICVs can play to ensure energy savings in HVAC systems without penalizing users' indoor comfort conditions. [ABSTRACT FROM AUTHOR]

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

Thermally activated building system (TABS) is a hydronic cooling system, in which cold water is circulated through pipes embedded in the building structure to remove the heat from the indoor space. This paper proposes a hybrid passive cooling system, in which TABS is integrated with a cooling tower. The performance of this integrated system greatly depends on the climatic conditions of the geographical area. Hence, the feasibility of the proposed system to provide thermal comfort in twelve Indian cities spread over five different climatic regions is investigated using COMSOL Multiphysics. Different cooling scenarios like Roof and Floor cooled TABS (RF) and All Surfaces cooled TABS (AS) are compared. The proposed system performs well in arid and semi-arid regions, and the RF scenario is sufficient to achieve thermal comfort. The system is able to reduce the indoor operative temperature by 14 °C for the arid climatic conditions of Jaipur. In the other three regions, i.e., humid subtropical, tropical wet and dry and tropical wet regions, the performance of the proposed system is relatively low and the AS scenario is required to achieve thermal comfort. [ABSTRACT FROM AUTHOR]

In the last years, multi-objective optimization techniques became into one of the main challenges of the building energy efficiency area. The objective of this paper is to develop and validate a computational code for multi-objective building performance optimization by linking an evolutionary algorithm and a building simulation software in a powerful cluster. A sophisticated version of the multi-objective Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was implemented in Python code to determine the optimal building design, which allows working with categorical and discrete variables, and the objectives were evaluated using the building energy simulation software EnergyPlus. NSGA-II was implemented to run in a high-performance cluster for the parallel computing of the fitness of each population (set of possible designs). In this work, the strengths of the proposed method were demonstrated by its application to the optimal design of a typical single-family house, located in the Argentine Littoral region. This house has some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). The most influential design variables like roof types, external and internal wall types, solar orientation, solar absorptance, size, type, and windows shading of this house among others were studied in two complex cases of 10 8 and 10 16 possibilities to obtain the best trade-off (Pareto front) between heating and cooling performance. Finally, a decision-making method was applied to select one configuration of the Pareto front. Optimal simulation results for the study cases indicated that is possible to improve up to 95% the thermal comfort in naturally ventilated rooms and up to 82% energy performance in air-conditioned rooms of the building with respect to the original configuration by using a design that takes simultaneous advantage of passive strategies like thermal inertia and natural ventilation. The methodology was proved to give a robust and powerful tool to design efficient dwellings reducing the optimization time from almost 12 days to 4.4 h. [ABSTRACT FROM AUTHOR]

Energy consumption of the public building stock represents an important cost of the balance of a state. Moreover, public buildings, in particular schools, should be buildings with elevated comfort levels because student and teachers spend much time in these rooms. The wellness and productive capacity of students and teachers are primarily affected by the comfort inside and air quality of school rooms. Regarding energy use, school buildings waste much energy because most buildings were constructed before the 1991 and energy saving measures were only implemented in a few schools. This paper analyses the energy performance of eight different schools located in Matera city, southern Italy. The aim of this research is to analyse energy requirement utilizing dynamic analyses with a time step of one hour (using Energy-Plus method). Next, the values of the dynamic analyses were compared to the effective energy consumption. Using the results of this comparison, we validated the numerical model, and then, we analysed different energy auditing actions for these buildings. We included the energy auditing works in three categories: energy restoration of the envelope, of the plant and of both. For each of these categories, we calculated the energy savings. Ultimately, we analysed the environmental benefits of the three different categories in terms of CO 2 reduction. This research confirmed that the dynamic method is the best method to achieve a good energy analysis of these complex buildings. [ABSTRACT FROM AUTHOR]

In this paper, it has been attempted to present a temperature control method for the building and, simultaneously, reduce costs of providing energy in hybrid heating systems. In the present work, a building in Tehran city has been investigated as a sample during a single day and applying intelligent control methods in the presence of two gas and solar heat sources. Furthermore, the influence of each of these methods has been studied on reducing costs as well as regulating indoor temperature. In the next step, the utilized controllers have been redesigned for the laboratory model and their capability has been evaluated through experimental tests. Based on the acquired results, it is deduced that, compared to other methods, utilizing a PID controller optimized by genetic algorithm not only reduces 50% of energy providing costs, but also regulates the inner temperature of the Lab model with an error lower than 1%. This method is faster than the others in regulating the model temperature. However, in the real building modeling case, the efficiency of this method has been reduced relative to the laboratory model, mostly because of variable conditions such as variable solar emission intensity during different hours of the day. Yet, acceptable results have been acquired by performing MPC and correct modeling. These results show that, as the variable parameters increase, the MPC presents higher capability compared to other methods In this case, the MPC has similar costs to the genetic algorithm while it regulates the temperature faster and with lower error. [ABSTRACT FROM AUTHOR]

This paper proposes a systematic modelling and optimizing of energy consumption and indoor thermal comfort for air-conditioning and mechanical ventilation (ACMV) systems. The models of extreme learning machines (ELM) and neural networks (NN) are established and evaluated. These well-trained models are then integrated with the computational intelligence techniques of sparse firefly algorithm (sFA) and sparse augmented firefly algorithm (sAFA). The sFA and sAFA aim to locate the global optimal operating points of the ACMV systems in real-time and predict energy saving rate (ESR) with a third order polynomial regression based on minimizing the mean squared errors (MSE) of the cost functions. This study also covers different indoor scenarios, such as general offices, lecture theatres and conference rooms. Given the well trained models, the maximum prediction of potential ESR can be −30% via the sparse AFA optimizations while maintaining indoor thermal comfort in the pre-defined comfort zone. [ABSTRACT FROM AUTHOR]

[Display omitted] Reinforcement learning (RL) algorithms have shown great promise in controlling building systems to minimize energy use, operational cost, and occupant discomfort. RL agents learn a control policy by interacting with the physical or simulated environment that represents building systems, occupants, and the outside world. Yet, a large amount of data is needed to learn a near-optimal control policy in the physical building, which requires months or years to collect. Moreover, an agent's performance while training can be quite poor, causing occupant discomfort and additional costs. Learning in simulation does not have such real-world impacts, but differences between buildings, and indeed between simulation and physical buildings, potentially lead to poor performance when a policy learned in simulation is deployed in a physical building. This paper addresses part of the sim-to-real problem by training on one set of simulated (source) buildings and then deploying to a novel simulated (target) building. This approach significantly reduces the training cost of RL on the target building by 1) learning a large number of policies on prototype buildings, 2) evaluating these policies on historical data obtained from the target building's environment and selecting the best ones according to the evaluation result, and 3) using the best policies to control the target building while continuing to learn. The proposed approach involves learning a diverse population of control policies using a novel diversity-induced RL algorithm, and policy clustering, evaluation, and selection techniques. Three case studies show our approach assigns policies to the target building that outperform the default controller by 4.0–30.4%, without sacrificing thermal comfort. Similarly, they outperform policies that are learned only on the target building (i.e., without transfer) by 24.9–74.9% and 16.2–72.2% before and after 500 months of training, respectively. [ABSTRACT FROM AUTHOR]

Recent research efforts on modeling personal thermal comfort support the integration of personalized preferences in optimal building control and further implementation in real buildings. This paper presents the development and field implementation of personal preference-based thermal control (i.e., a controller that provides thermal conditions to satisfy personal preferences) in real offices, emphasizing the role of model predictive control (MPC) and low-cost local sensing. Probabilistic thermal preference profiles were developed from experiments collected in identical private offices with controllable VAV systems. A low-cost thermal sensing network and a MPC framework were integrated into a centralized building management and control system. Customized, preference-based HVAC control was then experimentally implemented in the offices to (i) quantify the personal comfort penalty when using conventional wall thermostat versus local sensing-based operation for two distinct thermal preference profiles; (ii) evaluate the impact of personalized MPC (dynamic setpoint) on energy use and personal comfort compared with personalized simple feedback control (static setpoint), using local sensing; (iii) compare the personalized MPC performance for two distinct thermal preference profiles under different weather conditions. The results indicate the comfort benefits of monitoring local thermal conditions (vs wall thermostats) for different preference profiles and showed 28–35% energy savings with personalized MPC (vs personalized static setpoint control). The overall personalized MPC performance (and energy consumption) depends on the personal thermal preference characteristics and outdoor conditions. [ABSTRACT FROM AUTHOR]

Thermal properties have significant impact on ecological footprint and life-cycle assessment of buildings. This is even more crucial aspect for glass buildings, which have been criticised as major factors in climate change around the world. Recent debates on glass facades, which culminated in plans for a "glass building ban" in New York City highlighted the importance of innovation in glass construction. The current solutions for mitigating energy consumption for glass facades are improving insulation (U-value) and solar heat gain coefficient (SHGC) with advanced glazing or using shading devices. A fourth approach is the recent technology of water-filled glass (WFG), which utilizes water layer to improve thermal comfort and energy performance of the façade. This paper introduces Smart Water-filled Glass (SWFG) control method, which enables the change of the opacity of the façade element by colouring the fluid over a year regarding seasonal changes. The impact of changing transparency of water layer on cooling and heating energy demand is evaluated by simulating and analysing the energy performance of a reference office room with large glazing facade in different climates. The significance of this energy evaluation is that a water-filled glass with switchable transparency is simulated and assessed here for the first time. The paper analyses the performance in seven cities from all relevant major climatic regions using LBNL WINDOW and TRNSYS (v.18) As a novel approach, the simulation study makes it possible to evaluate the overall performance of two proposed operational methods (insolation-based & storage-based) for adjusting water layer settings depending on climate conditions and reusability of the captured heat in water layer. Moreover, seven different base cases are presented in this study to compare the performance of proposed system, including conventional solutions (e.g. double or triple glazing with/without shading) and a state-of-the-art switchable technology (e.g. electrochromic glazing or EC). The results verify the hypothesis that the impact of SWFG compared to WFG varies depending on the climate with 0%-5.28% for hot climates and 0.25–3.39% for climates with heating demand. The discussion includes comparison with standard glass facades, where SWFG shows 47.41%-78.01% energy savings depending on climate. The climate-based approach of SWFG and WFG offers a significant shift in façade design that sees glass buildings as an opportunity for sustainability rather than liability for climate change. [ABSTRACT FROM AUTHOR]

• A dynamic setting temperature that adapts to climate change was proposed. • The method was based on clothing adjustment behavior which adapts to thermal comfort. • The dynamic setting temperature had significant energy saving potential. • The dynamic setting temperature is useful for intelligent control of air-conditioner. Saving energy consumption of air-conditioning is essential to building energy conservation while satisfying the thermal comfort requirements of indoor environment. On the basis of human clothing adjustment behavior, a dynamic setting temperature (DST) that adapts to climate change was proposed in this paper, i.e. indoor air-conditioning setting temperature changes dynamically with outdoor air temperature; furthermore. A method was established to obtain the DST. The daily mean clothing insulation was predicted according to the historical temperature at first, then indoor thermal comfort temperature was calculated based on the variable clothing insulation, and finally the DST was determined. According to the value or range of predicted mean vote (0, -0.5~0.5, -1~+1) corresponding to the thermal comfort, three levels of DST were defined. The corresponding thermal acceptability rates were 95%, 90% and 73%, respectively. A simulation of DST was conducted in a public building in Changsha, China based on meteorological data of 2017. Three levels of DST ranges were obtained, varied from 20.1 to 27.8 °C in level I, 17.8 to 28.7 °C in level II and 15.4 to 29.7 °C in level III, respectively. The simulation results of operational air-conditioning energy consumption shows that the application of DST could save up to 65.5% of energy consumption compared with the traditional fixed setting temperature (FST), and the operational energy consumption decreased by 59.1% due to the application of level-III DST compared with level-I DST. Therefore, the DST proposed in this paper has significant energy saving potential while meeting the thermal comfort requirements. [ABSTRACT FROM AUTHOR]

The use of task/ambient conditioning (TAC) systems can help improve thermal comfort and indoor air quality, and reduce the energy consumption in bedrooms in residences or guestrooms in hotels at nighttime for sleeping. However, its operational and energy saving performances would be affected by a number of factors, such as supply air flow rate and temperature, and supply vane angles. This paper reports on optimizing numerically the operating performances of a novel bed-based TAC system. Firstly, the methods on a novel bed-based TAC system are introduced, including the experimental method and the computational method. Secondly, the numerical model is validated using the experimental results at the experimental operating conditions. Thirdly, the operating performances of the novel bed-based TAC systems at non-experimental operating conditions using the validated numerical model are optimized and the results reported. Finally, the conclusion and limitations of the study are given. The numerical study results showed that by suitably controlling its supply air flow velocity and temperature, and supply vane angle, the bed-based TAC system can be operated to maintain an acceptable level of thermal comfort without the cold draft in an occupied zone at a low energy consumption. [ABSTRACT FROM AUTHOR]

The renewable generation technologies form a significant (>20%) fraction of grid capacity, however their generation capabilities remain variable in nature. Therefore, utilities will be forced to maintain a significant standby capacity to mitigate the imbalance between supply and demand. Because more than 75% of electricity consumption occurs in buildings, building loads can be used to mitigate some of the imbalance. This paper describes the development and validation of an intelligent load control (ILC) algorithm that can be used to manage loads in a building or group of buildings using both quantitative and qualitative criteria. ILC uses an analytic hierarchy process to prioritize the loads for curtailment. The ILC process was developed and tested in a simulation environment to control a group of rooftop units (RTUs) to manage a building’s peak demand while still keeping zone temperatures within acceptable deviations. The ILC algorithm can be implemented at a low cost on a supervisory controller without the need for additional sensing. By anticipating future demand, the process can be extended to add advanced control features such as precooling and preheating to alleviate comfort when operation of the RTUs is curtailed to manage the peak demand. [ABSTRACT FROM AUTHOR]

Because the building sector has become a huge energy consumer, providing useful approaches can help tackle this important issue. Windows are an important component of a building since most of the natural light inside the building is provided by passing this component. Improper design of windows and their associated components, such as shadings, overheats the space and increases energy consumption, and on the other hand, disturbs the visual and thermal comfort of the building's occupants. The present paper aims to present a new approach for multi-objective optimization of the architectural specifications and control parameters of a smart shadow curtain. The use of this proposed approach leads to a significant reduction in building energy consumption and improved thermal and visual comfort. Energy-related simulations are performed through EnergyPlus software. Afterward, 21 design variables including control strategies and setpoints, location and orientation of shading, slat dimensions and material specifications, as well as hourly slat angle are considered in JEPLUS software. These simulations are conducted in four geographical directions over seasonal and annual periods for the city of Tehran, Iran. JEPLUS + EA software is employed to perform sensitivity analysis on the outputs of JEPLUS software and data optimization. Morris sensitivity analysis is implemented to investigate the effects of input variables on the objective functions. The NSGA-II algorithm is then applied to optimize the data to extract the optimal points on a Pareto front. The optimization results indicate that the external blind performs better than the internal blind and also the smaller the angle of the blind slat is, the better the visual comfort is but increases the electricity consumption for lighting. A comparison of the results of multi-objective optimization of controlled blind characteristics with initial values demonstrates that based on geographical directions, the total energy consumption of the entire building decreases by a range of 40–50 % per year, while visual comfort and thermal comfort are improved by ranges of 70–100 % and 10–40 %, respectively. [ABSTRACT FROM AUTHOR]

High performance variable air volume (VAV) air-conditioning systems can be as energy efficient as systems based on water or refrigerant, while first and life-cycle costs of such systems are significantly lower. The paper presents experimental test results of a novel cylindrical induction VAV controller and simulation results of energy consumption and thermal comfort in an office building with such controllers. A method for estimation of the minimum induced airflow required to avoid cold air dumping and a method for induction controllers and diffusers selection and sizing are proposed. To compare the VAV system with induction controllers and two other popular air conditioning systems, in terms of energy consumption and thermal comfort in an office building, the IDA Indoor Climate and Energy simulation tool was applied. The comparison was made for moderate climate conditions of Krakow, Poland, typical of Central and East Europe. The results showed that the total consumption of the electric energy used in cooling season for cooling and media transportation was similar when using a VAV system with induction controllers, a system with air chilled beams or a fan coils system. Similar thermal conditions were also observed. [ABSTRACT FROM AUTHOR]

Current indoor thermal environment is usually automatically controlled based on a temperature set-point given by room occupants or building managers. However, investigation shows that many temperature set-points are far from the comfortable temperature range recommended by design handbooks. Such unreasonable temperature set-points will result in not only uncomfortable indoor thermal environment, but also waste of cooling or heating energy. The authors have proposed a methodology of satisfaction based control to take place of the traditional set-point based control. This paper describes the experimental comparison results between satisfaction based indoor thermal environment control and set-point based control. Two test-beds were set up and a series of experiments was conducted to compare control performances, user acceptances, user work performances and system energy consumptions of the set-point based and satisfaction based control. The comparison results show that the satisfaction based control can achieve more stable thermal environment. Both of the two control methods can get relatively high scores regarding user acceptance and work performance. There are no statistically significant differences for user acceptance and work performance between two control methods. However, satisfaction based control consumed 15.3% and 11.9% less energy at two test-beds respectively than set-point based control due to more reasonable temperature settings given by the satisfaction based control. [ABSTRACT FROM AUTHOR]

• Synthetic thermal comfort profiles were generated from ASHRAE thermal comfort databases I and II used to evaluate occupant satisfaction and to calculate the HVAC setpoints. • Corrective Power of PCS was integrated into the Comfort Profiles. • PCS with maximum-satisfaction setpoints can improve occupant satisfaction by 18%. • ASHRAE requirement of 80% occupant satisfaction is met with little increase in energy consumption. Personal Comfort Systems (PCS) are energy-efficient devices that create a microenvironment around occupants and can be controlled individually to improve personal comfort. Most studies related to PCS either focus on improving occupants' thermal satisfaction or evaluate the energy-saving potential of PCS devices but do not consider the energy and comfort consequences simultaneously. This paper investigates the impact of PCS on improving occupants' thermal satisfaction and energy consumption across different climates in the U.S. using 16 representative cities. To account for the diversity in individual preferences, 400 comfort profiles for four climatic zones for summer and winter were generated utilizing comfort votes from ASHRAE global thermal comfort database I and II. PCS devices were used to improve occupant satisfaction by integrating the Corrective Power (CP) values into the comfort profiles. CP is defined as the temperature difference between two ambient temperatures that achieve the same thermal sensation one with PCS and another without PCS (reference condition). Then we compute the zone level setpoints that maximize the number of satisfied occupants and evaluate energy consumption of those zone level setpoints using EnergyPlus. Our study includes 3 cases; Case 1: without PCS (baseline), Case 2: only fans in summer and heaters in winter, and Case 3: fans and heaters in both summers and winters as required to improve satisfaction. In each of the three cases, we evaluated the comfort consequences using the comfort profiles, and the energy consumption implications. This accounts for the change in HVAC setpoints and the power requirements of PCS devices. The results show that incorporating PCS can increase occupants' satisfaction from 68% in Case 1 to 77.8% in Case 2 and 86.6% in Case 3. Moreover, energy consumption results in Case 2 are 0–1% higher, and 0–1.3% higher in Case 3 compared to without PCS, depending on the climate. Our results demonstrate that the adoption of PCS with maximum-satisfaction setpoints can improve occupant satisfaction by 18% and meet the ASHRAE requirement of 80% occupant satisfaction with little increase in energy consumption. The comfort profiles generated in this study are also released as a dataset to support future studies. [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]

• Ownership structure of small commercial buildings makes energy retrofits challenging. • Retrofit package for Zero Net Energy small offices in Mediterranean climate. • Energy use and occupant comfort evaluated experimentally, side-by-side, in real time. • 65%-68% energy savings for cooling season; 22%-25% for heating season. • Energy savings are achieved while maintaining visual and thermal comfort. Making buildings zero-net energy (ZNE) is one of the major strategies for achieving carbon emission reduction goals. For this strategy to be successful, it entails a very significant reduction in energy use – 50% or more. In small commercial buildings, however, owners and building management teams usually have limited resources for identifying, analyzing, and procuring appropriate retrofit measures for reducing such use. An approach to overcome this limitation is the development of bundles of energy efficiency measures that can be presented to building owners/operators as a comprehensive package. The research presented in this paper focuses on an experimental evaluation of the impacts of a retrofit package developed for small office buildings in California. Performing this evaluation in a full-scale whole-building integrated systems test facility allowed a side-by-side evaluation in real time, against a reference case, of the impact of the retrofit package not only on energy use but also on visual and thermal comfort. The retrofit package evaluated is comprised of a combination of HVAC, lighting (including daylighting), and plug load measures. The evaluation occurred at different times of the year in order to account for seasonal variations in environmental conditions, including solar angles and weather. The experimental facility allowed testing for two different façade orientations: south and west. Results show that the proposed ZNE retrofit package can save significant amounts of energy for small commercial buildings. During cooling-prevalent periods, total energy savings were 65% for south orientation and 68% for west orientation; during heating-prevalent periods total energy savings were 22% for south orientation and 25% for west orientation. Measurements indicate that the ZNE retrofit package resulted in small but not very significant changes in comfort levels for building occupants. [ABSTRACT FROM AUTHOR]

Typically the effect of thermal bridges on the energy performance of buildings is taken into account by implementing an average U-value in 1D whole building energy simulation program, which is referred to as the equivalent U-value method. This treatment accounts for the effect of thermal bridges on the overall thermal transmittance of envelope details, while their thermal inertia effect is ignored. In this paper, the dynamic effect of balcony slab as thermal bridges on the energy performance of a high-rise residential building is investigated by comparing the annual space conditioning loads obtained by the equivalent U-value method to that obtained from 3D dynamic modeling of the balcony junctions implemented in WUFI Plus program. The simulation results show that the equivalent U-value method underestimates the annual heating loads by 2.8–4.4% for the building as-designed. With the increase of balcony portion and better insulated walls, the difference in annual space heating loads modeled using these two methods is increased to 8.6–15.2%. With the implementation of balcony thermal break the annual heating loads are reduced by 8.8–25.7% and the difference between these two modeling methods is also reduced to 1.9–11.5% for the cases investigated. [ABSTRACT FROM AUTHOR]

Few examples studied applicability of exergy analysis on human thermal comfort. These examples relate the human-body exergy consumption rate with subjectively obtained thermal sensation votes and had been based on steady-state calculation methods. However, humans are rarely exposed to steady-state thermal environments. Therefore, the first objective of the current paper was to compare a recently introduced unsteady-state model with previously used steady-state model using data obtained under both constant and transient temperature conditions. The second objective was to explore a relationship between the human-body exergy consumption rate and subjective assessment of thermal environment represented by thermal sensation as well as to extend the investigation towards thermal acceptability votes. Comparison of steady-state and unsteady-state model showed that results from both models were comparable when applied to data from environments with constant operative temperature. In contrast, when applied to data with temperature transients the prediction of particular models differed significantly and the unsteady-state model resulted in better prediction of mean skin temperature. The results of the present study confirmed previously indicated trends that lowest human body exergy consumption rate is associated with thermal sensation close to neutrality. Moreover, higher acceptability was in general associated with lower human body exergy consumption rate. [ABSTRACT FROM AUTHOR]

This paper assesses the energy performance and occupant comfort of a ceiling-mounted coaxial personalized ventilation (PV) system in presence of radiation asymmetry due to a large window for different glazing systems. Detailed 3-D computational fluid dynamics (CFD) simulations were performed to study the flow and thermal fields in the conditioned office space and evaluate longwave and diffuse shortwave radiation effect on the occupant seated directly below the PV nozzle. The CFD model was coupled to a bioheat model to predict the corresponding local and overall thermal comfort of human body parts subject to the asymmetrical environment. The CFD model is validated by conducting experiments in a climatic room equipped with the PV system and using a thermal manikin facing a hot surface. Predicted and measured values of segmental skin and air temperature at the vicinity of the thermal manikin are compared. Good agreement (less than 8% error) was found between the measured and predicted values. Extensive simulations were performed to evaluate the effect of different types of window glazing on the perceived thermal comfort under various PV operating parameters. For high performance window, the coaxial PV system achieved remarkable energy savings up to 36% when was compared to mixing ventilation (MV) system at the same level of thermal comfort and environmental outdoor conditions. [ABSTRACT FROM AUTHOR]

Many residents in northwest rural China use a traditional system of Kang to heat their houses during the winter. Kang as a simple and regionally cultural technique has been widely used in vast rural areas in northern China with a perpetual history. In fact, the current Kang system is inefficient and requires high levels of fuel consumption. Then, how to improve both the thermal performance and energy efficiency is of great importance to the construction and development of the new-type Kang. In this paper, the Kang widely used in northwest rural areas surrounding Xi’an of China has been taken as the test object. The tests were conducted in detail under different operating conditions of stoves (stove 1 and stove 2, separately or both combined). A series of evaluation indexes about Kang such as average surface temperature, standard deviation of surface temperature, instantaneous thermal efficiency, and indoor air temperature have been analyzed. An improved layout model for Kang flue has been developed to assist in designing and optimizing the domestic Kang heating system. Based on the numerical simulation, the improved layout model was demonstrated to lead to substantial improvement of Kang thermal environment characteristics. [ABSTRACT FROM AUTHOR]

In this paper we explore the influence of personal control over space conditioning systems on occupants’ thermal comfort perception. It aims to identify the psychological effects of perceived control as well as the physical impacts when the controllable approaches are utilized. A chamber experiment was conducted, the results from which indicate that subjects with perceived control tended to report more positive comfort perception. The severer the thermal conditions were, the more subjects wanted to use personal control approaches, thus corresponding to stronger psychological effects. When personal control approaches were utilized appropriately, even a slight improvement in thermal conditions could significantly alleviate subjects’ thermal discomfort complaints. These findings provide support to the adaptive comfort theory and can serve as reference for the design of personal environmental control systems. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a control approach for the management of a production–consumption energy system based on model predictive control (MPC). The solar absorption cooling system is seen as part of this production–consumption energy system where the solar hot water storage (SHWS) system is the producer subsystem and the chiller-building system is one of the consumer subsystems. In order to provide modularity to the control structure, the coordination between the subsystems is achieved by designing interactive local predictive controllers. The consumer controllers compute a set of energy demand profiles sent to the producer controller which selects the profile that better minimizes the global optimization cost function. In a first part, the proposed control approach is tested on a simplified linear model composed of one producer and several consumers. In a second part, a more complex case is studied. A simplified model of an absorption cooling system is evaluated using the simulation tool TRNSYS. The producer model is no longer linear, instead it is described by a nonlinear hybrid model which increases the complexity of the optimization problem. The simulations results show that the performance of the controller fulfills the control objectives. [ABSTRACT FROM AUTHOR]

Double skin glazed facades (DGF) are an actual worldwide trend in new and refurbished buildings, even in warm climates with high solar radiation levels as in the Middle East and in Mediterranean climates. In such climates, overheating of indoor spaces and therefore excessive energy consumption are the main problems to be faced. These issues are commonly addressed mostly by thermal simulation or experimental evaluations on small prototypes. However, measurements on real-scale buildings with DGFs are very unusual. This information is crucial to understand and validate the predictions of the thermal behavior of the DGF technology. In this paper, thermal measurements were carried out in an unoccupied office building with a West DGF placed in the Northwest region of Argentina during 3 months in spring/summer. The air temperature exceeded in 10 °C the outdoor air and that indoor temperatures have not exceeded the outdoor levels in the hottest hours. Two correct design decisions were the use of low-e double hermetic glazing and the addition of a screenpainting to the external DGF panel. The experimental data showed that well-designed DGFs can reduce the summer energy consumption of buildings, even using West DGFs, in sunny climates. [ABSTRACT FROM AUTHOR]

Faults in heating, ventilation and air conditioning (HVAC) systems cause increased energy consumption, degrading thermal comforts, growing operational cost and reduced system lifespan. An effective evaluation of fault effects is critical to the development of various fault diagnostics solutions, the improvement of operation maintenance and the optimization of monitoring systems. In the HVAC area, a majority of research work in evaluating fault effects was to analyze energy consumption impacts or thermal comfort impacts. However, a handful of research has been conducted on evaluating fault effects on various measurements, which are increasingly employed to monitor equipment's operation. Fault effects on various measurements may display different symptom patterns and present changed sensitivities when the equipment operates under various faults, severity levels, as well as operation conditions. However, a long-term observation of fault symptoms under various operation conditions, different fault types and severity levels to evaluate fault effects is extremely challenging. In this paper, a simulation-based framework was proposed to evaluate fault effects in fan coil units (FCUs). Two metrics namely fault symptom occurrence probability (SOP) and fault symptom daily continuous duration (SDCD) were developed to quantify fault symptoms under various FCU faults. A total of 18 common FCU faults at different severity levels were implemented on the developed HVACSIM+ simulation platform to obtain a full year fault inclusive data set for 48 fault simulation cases. The framework, as well as obtained SOP and SDCD distributions will benefit multiple folds such as the development of probability-based fault diagnostics inference approaches, optimization of sensor location, and fault prioritization. [ABSTRACT FROM AUTHOR]

[Display omitted] • Thermostat Interactive Interfaces allow real-time decision-making. • Adaptive premises offer tailored HMI that address behavioral problems on thermostats. • Serious Games applied on Thermostats provide community decisions toward saving energy. • Tailored Adaptive strategies promote energy reductions without losing thermal comfort. • Personality traits, player type, and energy consumer give insights for personalized interfaces. The residential Heating Ventilation and Air-Conditioning (HVAC) system use around 3/5 of the total energy consumption. Connected thermostats optimize the HVAC operation; however, householders have personality traits that lead into behavioral and usability problems toward the thermostat's interface usage. Thus, a serious game applied in the thermostat interface can balance entertainment and education. Therefore, thermostat interfaces must address strategies that reduce energy without losing thermal comfort. This paper proposed an interactive interface type and a predicted interface type based on an HVAC strategy and a Natural Ventilation strategy. These strategies measured the impact of adaptive thermal comfort, energy consumption, and costs. Hence, twelve energy models located in California (Concord, Riverside, Los Angeles, and San Diego) were simulated using EnergyPlus™ through LadybugTools. The first interactive interface included Serious Game elements, so the householder interacted with the date, location, and setpoint. The second interface predicted the energy consumption and thermal comfort during winter and summer in Concord by a two-layer feed-forward Artificial Neural Network structure. The proposed structure decreases the energy consumption by at least 62% without losing thermal comfort. [ABSTRACT FROM AUTHOR]

• Review identified 29 unintended impacts post residential energy retrofits. • Moisture and dampness are common issues reported in post retrofitted housing. • The indoor environment is significantly affected by airtightness and over-insulation. • Pre retrofit assessment is essential to avoid hygrothermal failure. Improving energy efficiency of existing buildings is currently among the most diverse and extensive mitigation opportunities to reduce energy consumption and CO 2 emissions worldwide. However, the implementation of energy-saving measures has caused unintended impacts, often correlated with dampness and mold growth connected to poor hygrothermal behavior in residential buildings. The focus of this paper is research on the impacts of energy efficiency measures (EEMs) in regard to the hygrothermal behavior resulting from the interaction of building's envelope, indoor environment, and occupants. The results show that dampness and mold growth are by no means exclusive to neglected houses, since the occurrence of these pathologies actually depends upon a complex set of conditions, including indoor and outdoor conditions, occupancy, maintenance, ventilation, mechanical systems, and quality of the envelope. We found that building envelope post-retrofit may suffer from higher levels of moisture and dampness, higher condensations risks, and a faster structural degradation caused by higher humidity levels. We also found that measuring hygrothermal behavior may play a role in more accurately predicting both overall energy consumption and occupant comfort. While hygrothermal behavior may be problematic, we found evidence that retrofits may moderately improve thermal comfort. [ABSTRACT FROM AUTHOR]

The world is urbanizing rapidly and under the business-as-usual scenario, energy needs in cities will also increase dramatically. Urban population is expected to double by 2030; however the global built-up area is expected to triple during the same period (Angel et al. (2005) [1] ). This building out instead of building up will dramatically increase energy requirements and costs of new infrastructure and will influence the link between cities and climate change; to this end, the timely monitoring of the built-up area features and dynamics is considered supportive for defining temporal and spatial changes in energy needs and thus facilitate changes in urban design and support adaptation and mitigation plans in cities for climate change. In this paper the capacity of indices based on Earth Observation, to support the assessment of the built-up area features and dynamics is discussed and assessed. It is found that such indices can provide timely and accurate depiction of the built-up features and dynamics, including urban sprawl. It is also found that built-up area dynamics relate to the spatial and temporal variation of the discomfort index; this is an important parameter for defining urban energy needs as the higher the discomfort index, the more demanding the energy needs for cooling. [ABSTRACT FROM AUTHOR]

The ground source heat pump (GSHP) system is one of the most energy efficient HVAC technologies in the current market. However, the heat imbalance may degrade the ability of the ground loop heat exchanger (GLHX) to absorb or reject heat. The hybrid GSHP system, which combines a geothermal well field with a supplemental boiler or cooling tower, can balance the loads imposed on the ground loop heat exchangers to minimize its size while retaining superior energy efficiency. This paper presents a recent simulation-based study with an intention to compare multiple common control strategies used in hybrid GSHP systems, including fixed setpoint, outside air reset, load reset, and wetbulb reset. A small office in Oklahoma City conditioned by a hybrid GSHP system was simulated with the latest version of eQUEST 3.7 [1] . The simulation results reveal that the hybrid GSHP system has the excellent capability to meet the cooling and heating setpoints during the occupied hours, balance thermal loads on the ground loop, as well as improve the thermal comfort of the occupants with the reduced size well field. [ABSTRACT FROM AUTHOR]

Several conflicting criteria exist in building design optimization, especially energy consumption and indoor environment thermal performance. This paper presents a novel multi-objective optimization model that can assist designers in green building design. The Pareto solution was used to obtain a set of optimal solutions for building design optimization, and uses an improved multi-objective genetic algorithm (NSGA-II) as a theoretical basis for building design multi-objective optimization model. Based on the simulation data on energy consumption and indoor thermal comfort, the study also used a simulation-based improved back-propagation (BP) network which is optimized by a genetic algorithm (GA) to characterize building behavior, and then establishes a GA–BP network model for rapidly predicting the energy consumption and indoor thermal comfort status of residential buildings; Third, the building design multi-objective optimization model was established by using the GA–BP network as a fitness function of the multi-objective Genetic Algorithm (NSGA-II); Finally, a case study is presented with the aid of the multi-objective approach in which dozens of potential designs are revealed for a typical building design in China, with a wide range of trade-offs between thermal comfort and energy consumption. [ABSTRACT FROM AUTHOR]

Underfloor air distribution (UFAD) system, which is a relative new method of providing conditioned air and ventilation to the commercial buildings and data centers, is focused by researchers and designers for its potential advantages of better indoor thermal comfort (ITC) and indoor air quality (IAQ), layout flexibility, reduced life cycle costs, and energy saving. However, the application of UFAD system are still obstructed by the gap in the fundamental understanding of some new elements, such as the cooling load calculation, control of the thermal stratification, and evaluation of energy consumption. This paper reviews the current situation of UFAD technology, and the existing problems in recent researches are summarized. To improve the performance of UFAD system, several possible directions for the further studies are suggested. [ABSTRACT FROM AUTHOR]