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Recently, demand flexibility has been highlighted as a promising distributed resource from the customer side, especially from industrial customers like commercial buildings, capable of providing grid support services. However, the quantification of demand flexibility is a complex process that requires a methodology including the requirements of both the grid operators and the customers. This paper proposes a novel approach to quantify the available demand flexibility of individual buildings, while taking into account the underlying building energy physics. The proposed approach constructs on the operational flexibility concept from the power systems, and extends it to include a comfort domain, identifying different flexibility parameters with the aim of giving a better insight into the flexibility potential of commercial buildings. This method includes a development of building energy simulations to assess the effects of weather variations, construction types, and comfort constrains on demand flexibility. The proposed quantification method has been validated using 15 different office building models and two different climate zones, i.e., the Netherlands and Texas, US. The results presented in this paper suggest that buildings located in a hot climate could offer higher flexibility potential during shorter time ranges, while buildings in a cold climate could offer lower flexibility potential but during longer time ranges. Determining these differences could potentially facilitate the dispatch of flexible demand resources, to assess their real potential, and to schedule demand flexibility between stakeholders. [ABSTRACT FROM AUTHOR]

There has been an increasing concern on thermal comfort in sleeping environments and its associated energy use in the past few years. To improve the thermal environment and to reduce energy use of air conditioning in bedrooms, applications of task/ambient air conditioning (TAC) systems were proposed and studied previously. It’s indicated that the TAC system can be well integrated with a bed. Due to the variation of the envelope heat gain in a bedroom during night, it is necessary to study the thermal environment inside a bedroom and the energy use of a TAC system for the bedroom at varying envelope thermal loads. Therefore, this paper reports on a numerical study on a TAC system applied to a bedroom with different envelope heat gains. The influences of envelope heat gain on energy consumption of the TAC system and the indoor thermal comfort were studied in this paper. The research results show that at supply air flow rate ( Q s ) of 50 l/s, energy consumption was increased from 47.78 W to 213.11 W, and the PMV value was increased from −1.69 to −1.29 with the increase in envelope heat gain from 3.11 W to 155.6 W. To make PMV equal to zero under different envelope heat gains, linear regression models between supply air parameters and PMV were built and solved. The obtained values form curves where PMV = 0 and give a guide for operation of the TAC system. It was found that the calculation of energy consumption on these curves depends only on envelope heat gain. [ABSTRACT FROM AUTHOR]

Abstract: Thermal energy storage with phase change materials (PCMs) offers a high thermal storage density with a moderate temperature variation, and has attracted growing attention due to its important role in achieving energy conservation in buildings with thermal comfort. Various methods have been investigated by previous researchers to incorporate PCMs into the building structures, and it has been found that with the help of PCMs the indoor temperature fluctuations can be reduced significantly whilst maintaining desirable thermal comfort. This paper summarises previous works on latent thermal energy storage in building applications, covering PCMs, the impregnation methods, current building applications and their thermal performance analyses, as well as numerical simulation of buildings with PCMs. Over 100 references are included in this paper. [Copyright &y& Elsevier]

• BIM-DB can effectively simulate building performance parameters. • The PSO-RF-NSGA-III hybrid method can be used to predict and optimize building performance. • NSGA can simultaneously optimize energy consumption, carbon emissions and thermal comfort. • The optimal building parameters are different in different regions. Near-zero-energy-consumption buildings (NZEBs) are of great significance for sustainable development, and their design and research have attracted increasing academic attention. To drive and realize the energy saving design and achieve carbon emission and thermal comfort optimization of NZEBs, in this paper, an intelligent optimization method integrating the BIM-DB and PSO-RF-NSGA-III method is established. Multiobjective optimization problems involving NZEBs in four typical climate regions in China are explored. With a typical office building as an example, first, simulation calculations regarding the energy consumption, carbon emissions and indoor thermal comfort in the four climatic regions are performed based on orthogonal tests and BIM-DB. Second, the nonlinear mapping relationships between building design parameters and prediction targets are constructed with the PSO-RF model, which is trained with sample data. The obtained nonlinear mapping relations are used to establish the objective function of NSGA-III, and the multiobjective Pareto-optimal solution set is obtained with the developed PSO-RF-NSGA-III algorithm. Finally, the only optimal solution is determined by using the ideal point method, and reference near-zero-energy-consumption office building parameters are calculated for different climate regions. The conclusions are as follows. (1) The PSO-RF algorithm can efficiently predict building energy consumption, carbon emissions and thermal comfort. In the four regions, the goodness of fit of the three targets is greater than 0.94. (2) Multiobjective optimization can be performed with the proposed RF-NSGA-III intelligent optimization method. After optimizing multiple groups of optimization schemes and adopting energy saving measures, the energy consumption levels in the four climate regions are reduced by 39.72 %, 32.22 %, 26.94 % and 35.37 %, and the other goals are optimized. (3) Index calculations indicate that the optimized building design parameters meet the specified standards for NZEBs, and the main influencing factors and corresponding measures vary from region to region. [ABSTRACT FROM AUTHOR]

Near-zero energy buildings (nZEBs) are considered as an effective solution to mitigating CO 2 emissions and reducing the energy usage in the building sector. A proper sizing of the nZEB systems (e.g. HVAC systems, energy supply systems, energy storage systems, etc.) is essential for achieving the desired annual energy balance, thermal comfort, and grid independence. Two significant factors affecting the sizing of nZEB systems are the uncertainties confronted by the building usage condition and weather condition, and the degradation effects in nZEB system components. The former factor has been studied by many researchers; however, the impact of degradation is still neglected in most studies. Degradation is prevalent in energy components of nZEB and inevitably leads to the deterioration of nZEB life-cycle performance. As a result, neglecting the degradation effects may lead to a system design which can only achieve the desired performance at the beginning several years. This paper, therefore, proposes a life-cycle performance analysis (LCPA) method for investigating the impact of degradation on the longitudinal performance of the nZEBs. The method not only integrates the uncertainties in predicting building thermal load and weather condition, but also considers the degradation in the nZEB systems. Based on the proposed LCPA method, a two-stage method is proposed to improve the sizing of the nZEB systems. The study can improve the designers’ understanding of the components’ degradation impacts and the proposed method is effective in the life-cycle performance analysis and improvements of nZEBs. It is the first time that the impacts of degradation and uncertainties on nZEB LCP are analysed. Case studies show that an nZEB might not fulfil its definition at all after some years due to component degradation, while the proposed two-stage design method can effectively alleviate this problem. [ABSTRACT FROM AUTHOR]

• A MPC strategy was proposed for maximizing natural ventilation in passive buildings. • Days not applicable for natural ventilation were initially filtered via GMM algorithm. • Targets of thermal comfort and air volumes are predicted based on weather forecasting. • It is verified that the MPC strategy with priority to thermal comfort is superior. • Applicable ventilation hours via MPC are increased by 56.3% in transitional season. Due to the increasing demands of energy conservation and emission reduction, passive buildings with extra-low energy consumption and near zero energy consumption have attracted more attentions as a promising sustainable building type. Due to passive techniques such as air-tightness, passive buildings have a special demand of mechanical fresh air systems after closing windows. So it is indispensable to explore elaborate control strategies for maximizing natural ventilation, for the purpose of postponing the use of fossil energy. By taking meteorological forecast parameters as the input, an hour-head model-based predictive control (MPC) strategy of natural ventilation was proposed in this paper. Specifically, simulated multi-dimensional datasets obtained by setting different control actions under the same disturbances were obtained as the database for data-driven prediction models, which take weather forecast parameters as the input and labels of thermal comfort levels and air volumes as the output. It has been verified that although both with extended working hours and more stable comfort levels, the MPC strategy with priority to thermal comfort is superior to that with priority to fresh air volume. Furthermore, when compared with the traditional control strategy, ventilation hours via this MPC strategy could be increased by 56.3% from 366 h to 572 h. With this MPC model, the self-adaptive adjustment of window openness could be achieved by taking hour-ahead weather forecasting parameters as the input, thus to facilitate the climatic self-adaptive intelligent operation of passive buildings in future. [ABSTRACT FROM AUTHOR]

In this paper, a case study of performing a reliable statistical procedure to evaluate the quality of HVAC systems in buildings using data retrieved from an ad hoc big data web energy platform is presented. The proposed methodology based on statistical quality control (SQC) is used to analyze the real state of thermal comfort and energy efficiency of the offices of the company FRIDAMA (Spain) in a reliable way. Non-conformities or alarms, and the actual assignable causes of these out of control states are detected. The capability to meet specification requirements is also analyzed. Tools and packages implemented in the open-source R software are employed to apply the different procedures. First, this study proposes to fit ARIMA time series models to CTQ variables. Then, the application of Shewhart and EWMA control charts to the time series residuals is proposed to control and monitor thermal comfort and energy consumption in buildings. Once thermal comfort and consumption variability are estimated, the implementation of capability indexes for autocorrelated variables is proposed to calculate the degree to which standards specifications are met. According with case study results, the proposed methodology has detected real anomalies in HVAC installation, helping to detect assignable causes and to make appropriate decisions. One of the goals is to perform and describe step by step this statistical procedure in order to be replicated by practitioners in a better way. [ABSTRACT FROM AUTHOR]

Sustainable building performance requires the integration of various metrics such as energy consumption, thermal comfort levels, occupants’ wellbeing, and productivity. Despite their interdependence, these metrics have been mostly evaluated independently, overlooking potential tradeoffs that can occur between them (e.g., energy conservation efforts and thermal comfort). In addition, human-related factors such as occupants’ energy consumption behaviors, schedules, and movements between buildings cannot be captured using current commercial building modeling tools. Consequently, simulating the performance of a group of buildings such as in a campus, neighborhood, or city remains very challenging. In this paper, a comprehensive agent-based modeling (ABM) framework is developed to: (1) model an urban area with several buildings along with the movements and actions of people within the environment; (2) calculate key performance metrics such as indoor/outdoor thermal comfort and energy consumption levels; and (3) test and propose strategies to optimize sustainable building operation. This study illustrates the multidisciplinary approach needed to capture various dimensions of sustainable building performance. The framework is then applied to a green campus environment, identifying an energy management strategy that can reduce energy consumption by 19% without compromising occupants’ comfort and wellbeing. [ABSTRACT FROM AUTHOR]

Considerable research efforts in Building Optimization and Control (BOC) have been directed toward the development of “plug-and-play” BOC systems that can achieve energy efficiency without compromising thermal comfort and without the need of qualified personnel engaged in a tedious and time-consuming manual fine-tuning phase. In this paper, we report on how a recently introduced Parametrized Cognitive Adaptive Optimization – abbreviated as PCAO – can be used toward the design of both model-based and model-free “plug-and-play” BOC systems, with minimum human effort required to accomplish the design. In the model-based case, PCAO assesses the performance of its control strategy via a simulation model of the building dynamics; in the model-free case, PCAO optimizes its control strategy without relying on any model of the building dynamics. Extensive simulation and real-life experiments performed on a 10-office building demonstrate the effectiveness of the PCAO–BOC system in providing significant energy efficiency and improved thermal comfort. The mechanisms embedded within PCAO render it capable of automatically and quickly learning an efficient BOC strategy either in the presence of complex nonlinear simulation models of the building dynamics (model-based) or when no model for the building dynamics is available (model-free). Comparative studies with alternative state-of-the-art BOC systems show the effectiveness of the PCAO–BOC solution. [ABSTRACT FROM AUTHOR]

Energy efficient operation of microgrids, a localized grouping of controllable loads with distributed energy resources like solar photovoltaic panels, requires the development of energy management systems (EMSs) with the capability of controlling the loads so as to optimize the aggregate performance of the microgrid. In microgrids comprising of buildings of different nature (residential, commercial, industrial, etc.), where the occupants exhibit heterogeneous occupancy schedules, the objective of an effective management strategy is to optimize the aggregate performance by intelligently exploiting the occupancy schedules and the intermittent production of solar energy. This paper presents a simulation-based optimization approach for the design of an EMS in grid-connected photovoltaic-equipped microgrids with heterogeneous occupancy schedule. The microgrid exchanges energy, buying or selling it, with the main grid and the EMS optimizes an aggregate multi-objective criterion that takes into account both the energy cost and the thermal comfort of the occupants of the microgrid. Simulative results obtained using a microgrid test case developed in EnergyPlus demonstrate the effectiveness of the proposed approach: the proposed EMS strategy is shown to take advantage of the occupancy information, intelligently and automatically changing the energy demand of each building according to the occupants’ behavior, and achieving relevant improvements with respect to alternative EMS strategies. [ABSTRACT FROM AUTHOR]

The EU regulations on energy saving have been implemented in Italy with the adoption of the North-European super-insulated model that led to the construction of buildings not much related to their climatic context. The European Directives 2010/31/EU and 2012/27/EU highlighted the importance to consider the specific climate but the development of a technical culture suitable for a temperate climate still remains an open question. The aim of the paper is to quantify the effect on energy consumptions, comfort levels, environmental sustainability of the adoption of 3 energy efficient envelopes recently introduced in Mediterranean area and characterized by different thermal inertia (masonry, wood–cement, wood). In order to achieve this goal, a multidisciplinary approach was adopted involving: the study of the energy performance in winter and summer using analytical models both in semi-stationary and dynamic conditions ( Termo and EnergyPlus programs) and the detailed analysis of thermal bridges ( Therm software); the analysis of the annual comfort through dynamic analysis with Fanger’s PMV and adaptive comfort models; the quantification of environmental–economic impacts through LCA analysis ( SimaPro software) with Eco-indicator 99, CED, EPS 2000 and IPCC 2001 GWP methods and LCC considering financial and environmental costs. The results made it possible to stress the differences between the various adopted methods and demonstrate that in such energy efficient envelopes the thermal mass has low influence on energy saving while it has a great effect on comfort levels and environmental burdens, with a conflicting incidence on these two aspects. [ABSTRACT FROM AUTHOR]

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]

• A solar chimney coupled with an EAHE system (SCEA) is proposed. • The SCEA system functionality is studied on 5 design days of 2019. • 2 sets of CFD simulations are conducted for active and passive ventilation cases. • C H C l 3 concentration decreased by 60% in the breathing zone by the SCEA system. • Up to 174% enhancement of air changes per hour is achieved in the passive scenario. Due to the 40% share of buildings in global energy consumption, shifting to energy-efficient methods in this sector can significantly decelerate energy crisis, global warming, and their consequences. Hot-arid climate regions annually receive a significant amount of solar energy, which can be used as a substitute for fossil fuel-based sources in ventilation systems. In this paper, the potential of a typical public indoor swimming pool to harness solar energy is assessed by generating separate models based on the present active ventilation system and a proposed passive one. The passive system consists of a solar chimney coupled with an earth-to-air heat exchanger. CFD analysis of flow and energy fields, validated with field measurements, is carried out through numerical simulations using the SIMPLE algorithm and solar ray tracing module on the design days of May to September 2019 based on weather data. The distribution of key parameters; including temperature, velocity, humidity, and C H C l 3 concentration; is studied. The passive system generally outperforms the active one in terms of removing airborne contaminants and excess moisture while saving energy. On the most critical design day, more than 45% of temperature data, 78% of velocity data, 93% of relative humidity data, and 100% of C H C l 3 mass fraction data lay in the standard ranges. Also, mass fractions of chloroform and water vapor averagely decreased by 60 % and 11% in the breathing zone, still in the standard range of the relative humidity, and air changes per hour increased up to 174%. [ABSTRACT FROM AUTHOR]

• A nation-wide simulation to quantify the savings of the occupant-centric controls. • Enhanced building models that support the simulation of occupant-centric controls. • A simulation infrastructure that includes different code versions, climates, and sensors. • A code that automatically creates EnergyPlus objects for occupant-centric controls. • Multiple updated zone- and system- level occupant-centric controls. The occupant-centric control (OCC) is receiving an increasing attention since it could reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CPBM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis, which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones, was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in the majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode. [ABSTRACT FROM AUTHOR]