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Abstract: In arid climates, evaporative cooling technologies are generally valued for their reduced energy consumption in comparison to compressor-based air conditioning systems. However, two concerns that are often raised with respect to evaporative cooling equipment are their on-site water use and the impact of poor water quality on their performance. While compressor-based systems do not use water on-site, they do consume water through their use of electricity, which consumes water through evaporation at hydroelectric power plants and cooling at thermal power plants. This paper defines a water-use efficiency metric and a methodology for assessing the water use of various cooling technologies. The water-use efficiencies of several example cooling technologies are compared, including direct evaporative, indirect evaporative in two different configurations, compressor-based systems, compressor-based systems with evaporative pre-cooling of condenser inlet air, and hybrid systems that consist of an indirect evaporative module combined with a compressor-based module. Designing cooling systems for arid climates is entwined in the close relationship between water and energy and the scarcity of both resources. The analyses presented in this paper suggest that evaporative systems that significantly reduce peak electricity demand and annual energy consumption need not consume any more water than conventional systems. [ABSTRACT FROM AUTHOR]

Abstract: Design engineers commonly oversize HVAC systems with the justification of needing a reasonable safety factor to manage periods more extreme than the specific design conditions. Unfortunately, the safety factor easily becomes excessive. The design engineers minimize their professional risk, and by doing so they are actually asking the building owner to pay an immediate penalty due to increased first cost of equipment and an ongoing penalty due to maintenance and energy use implications. The penalties associated with excessive safety factors are often not communicated to the client. This paper presents the results of a study of “rightsizing” rooftop HVAC systems. The study included intensive interviews with HVAC designers investigating the design process and extensive field measurement of rooftop units (RTUs) during peak cooling conditions. This paper focuses on defining the signature of oversizing, i.e. how to use the physical measurements to quantify the degree of oversizing of an RTU and how to estimate the penalty of oversizing in terms of energy consumption and peak electricity demand. Utility companies incentive programs have not yet identified mechanisms for incentivizing rightsizing of HVAC system. The methodology described in this paper can be used as the basis for such programs. [ABSTRACT FROM AUTHOR]

Abstract: As dehumidification is one of the most important tasks of environment control of the building, it is necessary to know the energy efficiency of dehumidification processes. The energy efficiency can give the energy cost of drawing moisture from indoor air to the outside environment. This paper presents analysis of the ideal cost of dehumidification process by a liquid desiccant cycle. Formulas to calculate ideal efficiency of dehumidification process are obtained, which is determined by indoor temperature, outdoor temperature, and the temperature of the intersection point of the iso-relative humidity line of indoor air and the iso-humidity ratio line of outdoor air. The ideal efficiency of the condensing dehumidification method is lower than the ideal dehumidification process, due to the fact that condensing dehumidification method must dehumidify the air at the temperature of dew point. Results from this paper can be used as theoretical foundation for the further analysis of various dehumidification methods and the development of new dehumidification processes. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to study the various parameters that affect the energy performance of commercial buildings in Singapore. The parameters are diverse, ranging from characteristics of construction of the walls and windows, to the various system settings and types within the building. Building energy performance is measured via two key indexes, namely, the Envelope Thermal Transfer Value (ETTV) and the annual cooling energy requirement (E c). Parameters related to these two indexes are identified. An additional parameter, the solar absorptance of the wall, is further incorporated to calibrate the ETTV equation. A relative ranking on the functional parameters of ETTV has been performed to evaluate their effectiveness in lowering the ETTV of buildings. In addition, the impact of using cladding on ETTV is also studied. A correlation for E c, expressed in the form of a simple linear equation, has been developed. This correlation accounts for the internal building loads, envelope loads, operating schedules and efficiency of the cooling equipment. Finally, ETTV and E c have been employed to study the effects of chiller over-sizing and ventilation rates on building cooling energy. In the pursuit for better energy-efficient buildings, the approach presented in this paper contributes to the construct of sustainable energy-efficient built-environment. [Copyright &y& Elsevier]

Abstract: An extended Gebhart–Block model for large space buildings is proposed in this paper, which is used to predict the vertical temperature distribution of hybrid ventilation. Natural ventilation coupled with air-conditioning is described with a mathematical model. The indoor thermal environment formed by the air-conditioning and the natural ventilation can also be conducted for the potential analysis and optimal use of the natural ventilation. Experiments were carried out in an atrium building in Shanghai Research Institute of Building Sciences. This paper describes aforementioned model, and it is found that the calculation results implying this model agree well with the measurement data. [Copyright &y& Elsevier]

Abstract: With the actual environmental issues of energy savings in buildings, there are more efforts to prevent any increase in energy use associated with installing air-conditioning systems. The actual standard of thermal comfort in buildings ISO 7730 is based on static model that is acceptable in air-conditioned buildings, but unreliable for the case of naturally ventilated buildings. The different field studies have shown that occupants of naturally ventilated buildings accept and prefer a significantly wider range of temperatures compared to occupants of air-conditioned buildings. The results of these field studies have contributed to develop the adaptive approach. Adaptive comfort algorithms have been integrated in EN15251 and ASHRAE standards to take into account the adaptive approach in naturally ventilated buildings. These adaptive algorithms seem to be more efficient for naturally ventilated buildings, but need to be assessed in field studies. This paper evaluates different algorithms from both static and adaptive approach in naturally ventilated buildings across a field survey that has been conducted in France in five naturally ventilated office buildings. The paper presents the methodology guidelines, and the thermal comfort algorithms considered. The results of application of different algorithms are provided with a comparative analysis to assess the applied algorithms. [Copyright &y& Elsevier]

Abstract: This paper studies air flow in an air-conditioned room containing a distributed heat source and a localised heat source, into which cool air is supplied at low momentum through openings at a low level, and from which old air is extracted from a high level. This situation may be analogous to an auditorium containing a distributed audience and a localised group of actors and lighting on a stage, into which cool air is distributed from underneath the seating, and from which old air is removed through a ceiling, for example. Using a combination of a theoretical model and laboratory experiments, the paper shows that, in such conditions, if the localised heating is sufficiently strong compared to the distributed heating, the room will become stratified into two layers at steady state. A layer of warm air lies atop a cooler layer that attains a temperature above that of the supply air. This temperature structure depends primarily on the supply air flow rate and the ratio of the distributed heating to the total heat flux. For a room with fixed heating, increasing the supply air flow rate raises the interface between the upper and lower layers, while cooling both layers. The temperature in the upper layer depends on the total heat flux, but the temperature in the lower layer depends on the flux of distributed heating. For a room with a fixed supply air flow rate and a fixed total heat flux, increasing the strength of distributed heating warms the lower layer, but does not affect the temperature in the upper layer. Such increase in the strength of distributed heating also raises the interface. To achieve sufficient ventilation and thermal comfort in an occupied lower zone while keeping any pocket of uncomfortably warm air well above it, cool air needs to be supplied within an appropriate range of flow rates, which depends on the ratio of the distributed heating to the total heat flux. The paper shows how to determine such appropriate ranges of flow rates for different heating ratios, using the model. [Copyright &y& Elsevier]

Abstract: Compared to other non-residential buildings that have been widely researched, industrial buildings have higher thermal loads, higher air-change rates, longer operating hours and greater pollution control requirements. This paper presents the results of preliminary audits carried out on a sample of 12 representative small business enterprises in Greece including food, marble, wood, paper, plastic, metallurgical and service companies. Energy intensity varied from 50 to just over 300kWh/m2 with heavier industry buildings having values up to 1300kWh/m2. The successful adoption of energy conservation measures in key energy waste areas was assessed, including: (1) building envelope, (2) artificial lighting, (3) heating, ventilating and air conditioning (HVAC) and refrigeration systems, (4) space and water heating, (5) electrical and mechanical equipment and (6) distribution and transportation. It was found that businesses were more sensitized to energy conservation in the area of air conditioning followed by electromechanical equipment (important energy waste area that may yield the biggest energy conservation results, still in need of great improvement though the cost may be very high) and space/water heating; compliance with energy conservation measures was worst in the areas of artificial lighting (least important energy waste area in the case of most businesses) and the building envelope. A more detailed modeling study on a larger sample is proposed as a next step. [Copyright &y& Elsevier]

Abstract: The paper presents the basic parameters and the energy flows of a ground source heat pump system (GSHP) used for air conditioning the New City Hall of Pylaia (Thessaloniki area—Northern Greece). The building is a typical public one, with an air-conditioned area of 1350m2. The ground source heat pump installation is the largest in Greece, and its operation is monitored with the aid of a DAQ system. The energy flows presented in the paper are based on DAQ recordings of the first 3 years of system''s operation. It is proved that the energy demand of the system is significantly lower, compared to that of conventional heating and cooling systems. The seasonal COP of the system has not yet been stabilized, gradually increasing, as it is expected due to the operation of the ground heat exchanger. [Copyright &y& Elsevier]

Abstract: This paper presents analytical and numerical predictions of heat and pressure drop characteristics of a floor with the ventilating ducts. The experimental results are used to validate the models. An acceptable accuracy between the computational simulation and measured performance data is obtained. The analytical method is implemented as the computer program, which is a useful and accurate tool in designing heating system with underfloor air distribution. The bar chart of the design process and the diagrams for sizing the specific system of underfloor ventilation ducts are presented in the paper, too. [Copyright &y& Elsevier]

Abstract: Predicting the performance of natural ventilation is difficult, especially for large scale naturally ventilated buildings, due to the lack of accurate and efficient prediction tools. This paper presents a strategy, integrating a multi-zone model and computational fluid dynamics (CFD), to improve natural ventilation prediction and design methods. Large openings and atrium configurations are broadly used in naturally ventilated buildings to promote buoyancy force and optimize air movement. How to properly deal with this typical configuration for a multi-zone model and integrated simulation is discussed and compared in this paper. In order to validate a newly developed multi-zone model program, MMPN, this paper investigated both buoyancy ventilation and wind-buoyancy combined ventilation. Integration strategies, transferring data (velocity or pressure) from a multi-zone model program to CFD as boundary conditions, are also studied. [Copyright &y& Elsevier]

In a conventional construction, the ventilation air enters the building through a combination of pathways, such as windows and vents, via cracks around external openings, joints between building materials, etc. By contrast, in a dynamic insulation construction, the ventilation air is drawn into the building through the insulation material of the building envelope. Structures with dynamic insulation incorporate porous insulating material in the envelope and air passes through the porous material.The aim of this paper is to present the experimental work carried out on a wall component that is a combination of dynamic insulation panel and a ventilated façade, tested under real weather conditions. The wall component consisted of two main sub-layers: the ventilated external envelope and the dynamic insulation (DI) sub-layer. The DI component consisted of layers of breathing materials that let the air enter the room at a reasonable pressure difference between the interior and exterior.The paper describes the experimental work carried out and the results drawn from the tests performed in the linked wall component under: (i) various differential pressure regimes between the interior and the exterior of the test cell and (ii) controlled and floating internal air temperature. In summary, the performance of the component was effective, since conduction losses were decreasing. [Copyright &y& Elsevier]

At the conclusion of a noise annoyance survey in air-conditioned offices a new parameter was proposed. The aim was to define a noise index well correlated with subjective ratings of noise annoyance and able to account for the imbalance of the noise spectrum. As the RC Mark II procedure for rating the noise of HVAC systems in buildings introduced the “quality assessment index” (QAI), which provides a measure of the spectral imbalance of a noise, the combination of this parameter with the RC criterion number (which only measures noise level) was proposed. In a previous paper, the combination factor that maximised the correlation was determined and a validation procedure was used to test the repeatability of the results. In this paper, a new procedure to calculate the mean subjective ratings has been introduced and more demanding procedures to test the repeatability of the results have been used. Finally, it was found that a combination factor varying in a range from 0.24 to 0.31 provided the highest correlation between the new parameter and the subjective sensation of annoyance. [Copyright &y& Elsevier]

[Display omitted] • A novel method is proposed to improve diagnosis performance of AHU system with multiscale signals. • The proposed model eliminates the drawbacks of complicated feature engineering requirements. • The proposed model can effectively extract highly discriminative features from multiscale signals. • The proposed model can obtain better diagnosis performance by an end-to-end learning. This paper proposes a novel fault detection and diagnosis (FDD) method using multiscale convolutional neural networks (MCNNs) for Air Handling Unit (AHU) in Heating, Ventilation, and Air conditioning (HVAC) system. In existing works, it is challenging to achieve high diagnosis performance on multiscale monitoring signals from AHU system since the feature extraction methods in these works are not powerful enough. Although the single-scale convolutional neural networks (CNNs) have been adopted to improve the ability of feature extraction in FDD, it remains difficult to extract strong discriminative feature from multiscale monitoring signals only using single-scale kernels. In this paper, a novel MCNNs-based FDD method is proposed with three different scale kernels to improve the ability of feature extraction and the end-to-end learning strategy is adopted to optimize the model of MCNNs. With strong representation ability, the proposed method can capture highly discriminative features, which can help to improve the diagnostic performance of AHU. The proposed method is compared with other five commonly used methods using the measured data from our AHU experiment platform. The comparison results demonstrate that the proposed MCNNs-based FDD method outperforms other FDD methods. [ABSTRACT FROM AUTHOR]

[Display omitted] Pre-cooling is a method to shift peak air conditioning demand to off-peak and shoulder hours by utilizing energy storage in the thermal mass of buildings. This paper evaluates the pre-cooling potential of a range of residential buildings broadly representative of the Australian housing stock. Pre-cooling in 2-, 6-, and 8-star buildings with light, medium, and heavy construction weights in the cities of Adelaide, Brisbane, Melbourne, and Sydney is simulated, and its impacts on household bills, thermal comfort and peak air-conditioning demand reduction are assessed. Star rating is the method for rating Australian buildings based on their annual heating and cooling demand. The housing assessment by both star rating and construction weight highlights the varied potential of pre-cooling. Pre-cooling sensitivity to air conditioning size is also evaluated by simulating 5 k W th , 15 k W th , and 25 k W th air conditioning sizes representing typical small, medium, and large units in the Australian air conditioning market. Using an adaptive thermal comfort model, the impact of people's thermal comfort expectations on pre-cooling is also considered. The results highlight that compared with 2-star buildings, the percentage of daily cost savings from pre-cooling is considerably higher in 6-star and 8-star buildings. Moreover, with a small air conditioner, 2-star buildings are prone to negative seasonal cost savings as the air conditioner is not able to achieve thermostat temperature settings and hence runs longer. However, pre-cooling does offer considerable discomfort reduction to household members. A maximum summer seasonal cost savings of around $260 is observed in a 6-star light-weight building in Adelaide, and a 2-star light-weight building in Brisbane. Households that accept wider temperature variations with pre-cooling may not necessarily see cost savings. These households do provide greater peak air conditioning demand reductions. In conclusion, the value of pre-cooling for households and network peak demand reduction depends significantly on the housing type and location but can be highly valuable in many cases. [ABSTRACT FROM AUTHOR]

• A new design-day hourly variation coefficient generation method. • Three-parameter coupled coefficient joint matrix and K-Means clustering are used to build representative coincident coefficients. • Evaluation of reasonableness based on different load scenarios. • Suitable for different climate zones and typical buildings. The design day is the basis for calculating the cooling load, and a reasonable design cooling load is essential for balancing economics and reliability. The coincidence among weather parameters of design day is a key means to ensure the accuracy, while the coincident design-day hourly variation coefficients are less considered in existing studies. For this reason, this paper proposes a method to establish the coincident hourly variation coefficient for design days. The method first extracts the normalized hourly variation coefficients from 30 years of historical weather data. Based on this, a three-parameter coupled coefficient joint matrix is established and K-Means clustering is used to select representative coincident coefficients. Finally, a "typical line" method based on the weighting idea is proposed, and the final coincident design-day hourly variation coefficients are selected from the actual weather. To verify the rationality of the new method, different load scenarios were constructed with three design days and five typical buildings, and the rationality index was established by the ratio of indoor to outdoor risk levels. The results show that the rationality of the new method reaches 0.81, while the original method (Chinese and ASHRAE standard) is only 0.03 and 0.25 in Tianjin; further study shows that the new method is applicable in different climate zones and between different typical buildings, which provides a basis for the improvement of the existing design day generation method. [ABSTRACT FROM AUTHOR]

• Nonlinear hybrid MPC for buildings energy systems based on Modelica. • Time-variant linearization of the nonlinear Modelica optimization problem. • Automated creation of the linearized optimization problem in every MPC iteration. • Integration of on/ off control, discrete operation states and operation modes. This paper presents a nonlinear hybrid Model Predictive Control (MPC) approach for building energy systems based on Modelica. The MPC approach takes into account two characteristics that are very common for building energy systems: nonlinearities (inherent in the building envelope and Heating, Ventilation and Air Conditioning (HVAC) systems) and discontinuities (in the form of on/ off operation, discrete operation states and operation modes). The hybrid MPC approach integrates both continuous and discrete optimization variables into the control concept and thus is capable of controlling building energy systems with binary or integer decision variables, switching dynamics or logic if-then-else constraints. By employing a time-variant linearization approach, nonlinear Modelica optimization problems are approximated with high accuracy and transformed into a linearized state-space representation. Based on the linearization output, a linearized optimization problem is generated automatically in every MPC iteration, which is extensible by various integer characteristics and is accessible for a wide range of mixed-integer solvers. A simulation study on a nonlinear Modelica building energy system demonstrates the control quality of the proposed toolchain revealing a small linearization error and successful integration of multiple integer characteristics. The benefits of the approach are manifested by comparing its performance with different reference control strategies. [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]

In practice, monthly temperature records play a major role calculating the heating and cooling degree-days of the air conditioner management in buildings. Classically, heating and cooling degree calculations are based on the comparison of outdoor temperature measurements with a standard level called the base temperature. Truncating the temperature series at a constant base temperature causes heating (deficits) and cooling (surpluses) degrees. Since outdoor temperature records are of random character, future predictions with probabilistic and statistical methods are convenient means for calculations. All previous methodologies in the literature are based on crisp logic with simple mathematical calculations. This paper proposes a new methodological approach by converting the actual temperature record probability distribution function (PDF) into a probabilistic standardized degree indicator (SDI) in normal (Gaussian) PDF form with zero mean and unit standard deviation. Furthermore, as a new evaluation methodology fuzzy logic inference calculations are provided. SDI is divided into seven classes, three for cooling, heating, and a single class for uncooled-unheated states. Heating and cooling degree changes according to SDI values are presented with crisp and fuzzy sets. The application of the methodology is made for Kadıköy urban area on the Asian side of Istanbul, Turkey. In the case of fuzzy set SDI air conditioned operation, it has been determined that there is cooling energy saving of approximately 25% compared to the crisp set. The same is true for the heating degree-day side. [ABSTRACT FROM AUTHOR]

• Building energy performance is negatively impacted by suboptimal operations. • Data-driven operations analytics may aid an operator's decision-making processes. • Insights were derived using data from interviewees' individual building portfolio. • Operators were hesitant in addressing deficiencies, specifically controls changes. • Possible barriers to effective utilization of data-driven insights were identified. Data-driven operation and maintenance analytics for improving building energy performance are prevalent in the literature and produce various visualizations and key performance indicators that identify hard and soft heating, ventilation, and air conditioning faults, occupancy patterns, and energy use deficiencies. However, an underlying assumption exists that the outputs of these analyses, some adopted from ASHRAE guidelines, can effectively impart actionable energy-saving insights to building operations personnel and augment the handling of faults, optimized operating controls, or building-level scheduling. This paper attempts to identify potential barriers to effective interpretation and utilization of data-driven, energy-saving insights by building operators and facility managers. Eleven operations professionals were interviewed and assessed regarding what initiatives or changes they would make in light of various outputs of multiple established data-driven approaches. Data from the interviewees' individual building portfolio were inputted into a multi-source data analytics web application, employing fault detection and diagnosis and inverse modelling techniques, and its outputs were presented to interviewees. Only two of the 11 interviewees expressed interest in making controls changes in response, revealing a possible knowledge gap of data-driven analytics, combined with the risk-adverse nature of building operations, which may inhibit operations personnel from effectively utilizing data-driven insights as presented. [ABSTRACT FROM AUTHOR]

• An air conditioning system with thermoelectric modules is analysed and optimised. • Cooling investment and operating costs are discussed. • Heat exchangers are optimised based on economic indicators. • The economically optimised air conditioning system can be significantly overloaded. • TEC air conditioning is expensive but quiet, compact and environmentally friendly. The paper presents simulations of an air conditioning system based on thermoelectric modules. The proposed system is of a very simple structure, easy to control, scalable, noiseless, and harmless to the environment. The most important parameters that were to be changed were the number of modules, the electric current, and the size of the heat exchangers. The analyses were carried out for a commercially available thermoelectric module whose parameters were determined experimentally. The air conditioning system was analysed in terms of its cooling capacity and COP. Furthermore, it was optimized with economic criteria to achieve the highest cooling capacity of 1 dollar of total cost (electricity and investment) in a set period of device lifetime (ETCC – economic total cooling capacity). For 2400 h of device operation, at a temperature difference of 5 K and the average electricity cost in the EU, the optimized ETCC totals about 0.58 W/$. With the possibility of altering the inner geometry of the thermoelectric modules, the factor increased to 0.64 W/$. The test results showed that the device optimized in terms of ETCC did not operate with maximum cooling power and could be overloaded by about 30% in the reference working conditions. [ABSTRACT FROM AUTHOR]

• Addressed a real-world challenge for load-shifting multiple ON/OFF staged units. • Presented a unique MPC that shifts load while eliminating undesired peak. • Presented comprehensive 2-month experimental MPC demonstration results. • Achieved significant load shifting with over 30% demand savings. • Discussed experimental charging and discharging processes of building thermal mass. Small and medium-sized commercial buildings (SMCB) are significant demand response resources, and it is important to develop grid-responsive control algorithms that exploit those resources and create financial benefits for building owners and HVAC service providers. Furthermore, unlike large-sized commercial buildings, there is an opportunity to have universally applicable control solutions for many SMCBs since those buildings have a consistent HVAC system configuration: SMCBs are commonly served by multiple-staged air conditioning units controlled by their own thermostats. Despite the demand response potential and scalability, however, very few control solutions are available for SMCBs. Typical model predictive control (MPC) and heuristic control approaches for cooling load shifting that lower thermostat setpoints before an electric price jump are suitable mainly for large-sized commercial buildings where a continuous capacity modulation is possible, e.g., via dampers in variable air volume terminal units. However, those approaches can cause undesired, high peaks for SMCBs due to the nature of ON/OFF unit staging and narrow thermostat deadbands. This could discourage the use of advanced grid-responsive controls for SMCBs due to the concern of high demand charges, and has to be resolved. This paper presents a MPC solution that overcomes this challenge. It has a hierarchical MPC structure where an upper level MPC is responsible for electrical load shifting in response to an electric price signal while a lower level MPC is responsible for coordinating compressor stages to eliminate unnecessary peaks and follows the setpoints determined by the upper level MPC. Two one-month, comprehensive laboratory tests have been carried out to demonstrate load shifting and cost savings for the algorithm. Interesting trade-offs between energy efficiency and load flexibility were observed and are discussed, and lessons learned for applying MPCs for SMCBs are also presented. [ABSTRACT FROM AUTHOR]

Housing orientation has an effect on the total heating and cooling loads that consumers pay for as part of their monthly utility bills. Often suburban developments lack consideration of the precise optimal solar orientation of each home, therefore, costing homeowners money over the life span of their tenure. This study aims to evaluate the effect of a home’s orientation at the community level evaluating energy use and annual energy costs. The scope of the paper simulates the effect of orientation for 7000 existing homes for four typical Midwestern suburban developments and the resulting annual energy costs. Appling the same housing sample to four different U.S. locations the study compares climatic differences. This analysis evaluates the cost and energy performance of existing suburban communities using optimal solar orientation. Results show that individual home orientation has minimal cost implications, whereas the aggregated suburban community house orientation has more significant total annual energy costs. In addition, results reinforce optimizing solar orientation for planning and design of suburban housing. [ABSTRACT FROM AUTHOR]

Most current building thermal codes impose upper limits to the predicted annual building energy demand for heating, ventilation and air conditioning. In the building design phase these predictions are obtained using thermal simulations with variable complexity. The simplest approach uses a single lumped thermal capacitance to model the high thermal mass building elements, combined with five thermal resistances (known as the 5R1C model proposed in EN ISO 13790 standard). This model is used by many European countries as the reference simplified methodology to assess overheating risk and calculate yearly building energy demand. This paper presents a successful extension of this model that allows for its application to the prediction of the internal air temperature of free-running buildings with double skin façades. The extension consists in an increased number of thermal resistances used to model the double skin façade zone. The extended model is validated using a set of detailed thermal measurements obtained in a free-running double skin test cell. For the case analysed the simplifications used in the RC model do not reduce the overall accuracy: the mean absolute error for room air temperature is approximately 1 °C, the same order of magnitude of more detailed EnergyPlus simulations (1.2 °C). [ABSTRACT FROM AUTHOR]

Temperature and humidity independent control (THIC) systems demonstrate promising energy-saving potential compared with the conventional air conditioning systems. One type of THIC systems is proposed to use dual cooling sources with different temperatures since they could be produced easily by traditional vapor compression refrigeration chillers. This paper investigates the applicable condition of the THIC system based on dual cooling sources (DCSTHIC system). It is found that the DCSTHIC system has limited conditions (such as scopes of the heat moisture ratio and the fresh air rate) when applied, otherwise the indoor air temperature and humidity can’t be fulfilled, and further available scope of the heat moisture ratio realized by the DCSTHIC system is disclosed for air conditioned spaces. The minimum realized heat moisture ratio depends on the temperature of low-temperature cooling sources ( t LCS ). A parametric study is also conducted to analyze effects on the energy efficiency of DCSTHIC systems. These parameters include the heat moisture ratio ( ε ) and temperatures of dual cooling sources. Results show that DCSTHIC systems show more significant energy-saving potential in the air conditioned spaces with higher ε . The system COP improvement ranges from 3.1% to 17.5% compared with conventional air conditioning systems when the heat moisture ratio changes from 8000 kJ/kg to 15,000 kJ/kg. This study helps to guide the design and optimization of DCSTHIC systems. [ABSTRACT FROM AUTHOR]

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. Exploiting the equation-based language led to 2200 times faster solution. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) has been studied in the building science realm for about three decades. However, the following two aspects of the building control have not been studied thoroughly in MPC research. One is the impact of the mixed-mode cooling system on the active heating ventilation and air conditioning (HVAC) energy consumption, and the other is the differences of individual thermal comfort preference and its impact on energy. This paper proposes an occupant-oriented mixed-mode EnergyPlus predictive control system to optimize HVAC energy consumption while meeting the individual thermal comfort preference. A web-based dashboard is implemented in the test-bed building for three months to collect individual thermal comfort preference data. The data analysis results suggest that occupants have various tolerances and preferences about thermal comfort. The simulation results show that, during one week of a typical swing season, the mixed-mode system further reduces the active HVAC energy consumption, and the diversified occupant thermal comfort preference has significant impact on HVAC energy consumption. [ABSTRACT FROM AUTHOR]

In tropical countries such as India, increasing the roof albedo helps to reduce the heat ingress through the roof. This further reduces air-conditioning energy consumption in conditioned buildings and increases comfort in unconditioned buildings. In order to help users determine the benefits of high albedo roofs under varying conditions, a simple calculator has been developed. Parameters such as location, building type, roof area, and surface properties of the roof are taken as inputs. Annual EnergyPlus simulations are performed for the given parameters and the results are displayed in both graphical and tabular formats. It also calculates the simple payback by comparing a given base case roof albedo with the proposed roof albedo. The calculator can perform comfort simulations for unconditioned buildings and simulates measures including a radiant barrier system and under deck roof insulation. The calculator also runs a parametric simulation between insulation thickness and roof albedo to find an optimum roof insulation thickness based on incremental internal rate of return. This paper presents the features of the cool roof calculator and the type of analysis that can be performed using the cached results. [ABSTRACT FROM AUTHOR]

In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO 2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 °C and 0.1–0.5 °C, respectively, and energy savings of 40–80 and 70–90 kJ/m 2 /day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO 2 /day, in the entire target study region. [ABSTRACT FROM AUTHOR]

This paper describes the development and focus in the analysis of the Brazilian metamodels used in the residential labeling system. The metamodels represent the thermal behavior of naturally ventilated and artificially air-conditioned residential buildings. A computational simulation experiment using the EnergyPlus program was conducted taking into account naturally ventilated and artificially air-conditioned residential buildings. Several parameters were considered for parametric simulations such as thermal transmittance, thermal solar absorptance, shading device, ventilation opening factor. The multi-linear regression method was used to predict the cooling degree hours and the annual energy consumption for heating and cooling for dormitories and living room. An assessment on the accuracy of the Brazilian metamodels for residential buildings was analyzed and showed that the regressions include standard errors that may influence the metamodels accuracy. Therefore, artificial neural networks (ANNs) are presented as an alternative to improve the metamodels used in the Brazilian regulation. Comparing both statistical method multi-linear regression and artificial neural network method it can be seen that ANN presented lower results for standard deviation end root mean square errors. Therefore, ANNs are recommended to improve the accuracy of the prediction in further behavior associated with the labeling system. [ABSTRACT FROM AUTHOR]

Heating, ventilating, and air-conditioning (HVAC) systems consume almost half of the total energy consumption in buildings. In order to reduce the energy consumption of HVAC systems in buildings, different passive heating and cooling strategies and thermal energy storage systems have been adopted. Water wall is an excellent short-term thermal energy storage system which can be used to maintain thermal comfort in buildings while reducing the heating and/or cooling load of the buildings. A significant amount of research work on water wall has been carried out since the 1980s. This paper presents a comprehensive review of the previous studies of water wall systems, focussing mainly on the performance of various configurations of water wall systems and the different research approaches adopted in the literature. The advantages and disadvantages of the different research approaches have been highlighted. It is revealed that the existing water wall research has been based mainly on an energy balance model and experimental modelling, but CFD (computational fluid dynamics) modelling has attracted little attention. Moreover, this review has identified several gaps in the water wall research for further attention. [ABSTRACT FROM AUTHOR]

Energy signatures for air conditioning systems can have characteristics which are not seen with heating systems. This paper explains and illustrates some of the characteristics that are specific to air conditioning systems and describes how energy signatures that take account of them can be applied to produce benchmarks, control charts and diagnostic information. It focusses on the use of energy signatures derived from measured daily system energy consumption. Daily energy signatures can generate more robust energy consumption benchmarks and provide additional insight into unusual energy demand patterns compared to monthly or weekly signatures, albeit requiring slightly more data. In particular, they distinguish between weekday and weekend consumptions. They can be used to generate benchmarks based on standardised annual consumption or standardised annual load factor. In addition they can be used to generate control charts to identify days of unusual consumption for individual systems. More sets of daily energy consumption data are needed to evaluate their diagnostic power. [ABSTRACT FROM AUTHOR]

Non-residential buildings comprise a quarter of the European Union (EU) building stock and cause approximately one-third of this stock's energy consumption. The imperative to reduce their energy consumption is widely accepted in EU countries. It is now common to upgrade both residential and non-residential buildings to increase energy efficiency, but studies indicate a significant gap between energy performance and design. In the residential sector, this gap has been extensively investigated and quantified under the heading of the ‘rebound effect’, but there do not yet appear to be studies on rebound effects in non-residential buildings. This paper develops a methodology to fill this gap. Through technical measurements in four recently retrofitted German public service case study buildings, rebound effects were estimated under two definitions: the ‘elasticity’ rebound effect and the ‘energy performance gap’ (EPG). Cross-sectional data of actual and calculated consumption in 176 comparable buildings was used to estimate typical rebound effects which could be expected in such buildings. The case study results indicated comparatively low rebound effects but high EPGs. Semi-structured interviews with building occupants and operators identified credible determinants of energy consumption. The methodology proved effective and robust, and is offered for further use and development. [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]

To date, the application of liquid desiccant air conditioning systems in built environment applications, particularly small scale, has been limited. This is primarily due to large system size and complexity, issues of desiccant solution leakage and carry-over and equipment corrosion. As a result, a novel integrated desiccant air conditioning system (IDCS) has been developed. The system combines the regenerator, dehumidifier and evaporative inter-cooler into a single membrane based heat and mass exchanger. This paper presents an evaluation, based on experimental data, of the novel IDCS operating with a potassium formate (CHKO 2 ) desiccant working fluid. A range of tests have been completed to characterise the performance of the dehumidifier, regenerator and complete IDCS. Cooling output in the range of 570 to 1362 W and dehumidifier effectiveness in the range of 30 to 47% are presented. An issue encountered has been an imbalance between moisture removal rate in the dehumidifier and moisture addition rate in the regenerator. As a result, an adjusted thermal COP (COP th,adj ) value has been calculated. COP th,adj values of 1.26 have been achieved with an average of 0.72. Electrical COP (COP el ) values of 3.67 have been achieved with an average of 2.5. The work demonstrates that the novel IDCS concept is viable and has provided progress to the field of liquid desiccant air conditioning technology for building applications. Further work is required in order to address the main issue of mass imbalance between the dehumidifier and regenerator. [ABSTRACT FROM AUTHOR]

The aims of this paper are (1) to evaluate the geothermal resources in Tunisia and (2) to test the deployment of the surface geothermal energy for cooling application. The experiment consists of installing a ground source heat pump (GSHP) system, was carried out in the ‘Centre de Recherches et des Technologies de l’Energie’ (CRTEn) at Borj Cédria, northern Tunisia. The GSHP is composed with horizontal ground heat exchanger (GHE) connected to a reversible geothermal heat pump (GHP), which is connected to a chilled ceiling panel (CCP) system installed in a climate test room. The status of geothermal energy and its utilization are pointed out, the test of the direct use of surface geothermal is examined as well as the evaluation of the GSHP system for air conditioning. The important findings of this study are: (1) Tunisia benefits from important geothermal resources, but its use remains very limited, (2) the only use of the (GHE) has reduced the average temperature inside the climate test room of about 2 °C during 1 day. (3) The test of the GSHP system proves that it is a profitable solution in Tunisia, the coefficient of the performance of the GHP and the whole system are found to be 4.46 and 3.02, respectively. [ABSTRACT FROM AUTHOR]

Conventional chilled water based air conditioning systems use low temperature chilled water to remove both sensible load and latent load in conditioned space, and reheating devices are usually installed to warm the overcooled air, which leads to energy waste. Alternatively, this paper proposes a neural network (NN) model based predictive control strategy for simultaneous control of indoor air temperature and humidity by varying the speeds of compressor and supply air fan in a chilled water based air conditioning system. Firstly, a NN model has been developed to model the system dynamics, linking the variations of indoor air temperature and humidity with the variations of compressor speed and supply air fan speed. Subsequently, the NN model is experimentally validated and used as a predictor. Based on the NN model, a neural network predictive controller is proposed to control the indoor air temperature and humidity simultaneously. The experimental results demonstrate the effectiveness of the proposed scheme compared with conventional PID controllers. Moreover, it has been proven that it is practical to simultaneously control indoor air temperature and humidity by varying the compressor speed and the supply air fan speed without adding any other devices to the chilled water based air conditioning systems. [ABSTRACT FROM AUTHOR]

This paper shows development of a simple, cheap “Building Energy Management System” (BEMS) to monitor energy consumption, and an application to measure energy consumption, including electricity and gas consumption in buildings. The system uses current transformers to measure electric consumption at each distribution box. Web cameras monitor lighting in each room, as well as air conditioning status by recognizing the movement of a ribbon at the outlet. Web cameras can also monitor gas consumption at the meter through character recognition. The data is sent via network to a computer for monitoring and analysis. As an example, key components of this BEMS were tested to measure building energy consumption of Osaka City University Sugimoto Campus in Japan for a period of 2 years (2013, 2014). The electric consumption of campus as well as the electric and gas consumption for air conditioning use was measured. Web cameras were installed in several rooms in one section of the campus to record lighting and air conditioning use data. The data was analyzed to reveal a correlation between hourly outdoor temperature and hourly electric consumption, with a stronger correlation between hourly outdoor temperature and hourly electric consumption for air conditioning. [ABSTRACT FROM AUTHOR]

This paper presents a method which combines the bilinear control technique with a set-point reset technique to control the space temperature when its cooling is provided by a GSHP equipped with an on/off capacity control, aiming to (i) improve the robustness of the space temperature control by taking account of load uncertainty; and (ii) to reduce the frequency of the GSHP on/off cycling by using the indoor space temperature set-point reset. When the GSHP is on, a smaller space temperature set point is used; while the GSHP is off, a larger set point is used. The proposed control was tested on a simulation platform, which consists of a ground source heat exchanger, a GSHP, an air-handling unit (AHU) and a middle-sized room. The test results show that the proposed control method is able to achieve a good control performance and has the potential to be applied to a real GSHP integrated air conditioning system to improve the robustness of space temperature control and simultaneously reduce the on/off frequency of the GSHP. [ABSTRACT FROM AUTHOR]

A ground-coupled heat pump (GCHP) is a clean and energy-saving approach to providing air conditioning and domestic hot water. For buildings with a dominant heating load, more heat is extracted from the soil and thermal imbalance becomes a crucial problem, in turn reducing efficiency and impeding the wide application of GCHP. Due to the disadvantages of the existing solutions, a multi-mode air-source heat compensator (AHC) integrated with a GCHP system to make a hybrid AHC-GCHP system is proposed in this paper. The principles and operating strategy of AHC-GCHP are illustrated in detail and its performance is simulated in the transient system simulation tool TRNSYS. AHC can not only compensate heat into the ground but also supply heat for space heating and domestic hot water in different modes through full use of the energy in the air with the average coefficient of performance (COP) ranging from 4.49 to 15.09. The AHC-GCHP system effectively keeps the soil thermal balance, and saves 23.86% energy compared with a traditional “boiler + split air conditioner” system, and costs less than half as much as a “hybrid GCHP assisted with solar collector” system. Consequently, the AHC-GCHP system is a potentially efficient and economic approach for buildings in cold regions. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) for building applications has been considered by many HVAC experts as an efficient tool to promote building energy efficiency and indoor thermal comfort. This paper, therefore, proposes a strategy of using WSN to monitor the temperature distribution in a large-scale indoor space, which aims to (i) improve the quality of the measurements transmitted by wireless signals, (ii) identify the temperature distribution pattern of the large-scale space, and (iii) optimize the allocation of supply air rated flow rate to multiple supply air terminals that serve the space according to the identified temperature distribution pattern. The developed strategy is illustrated by applying it to a real WSN test bed, installed in a typical large-scale space in Hong Kong. Results are presented and discussed, which shows that the phenomenon of temperature uneven distribution was commonly existent in a large-scale space and the developed strategy was able to efficiently improve the quality of measurements by WSN and improve the temperature homogeneity in the large-scale space. [ABSTRACT FROM AUTHOR]

Control strategies of building shading devices can achieve important savings in the air conditioning and lighting energy consumption of a building. Calculation procedures of the different solar control devices (overhangs, side fins, etc.) are of special interest in annual energy performance simulation programs, which have to obtain solar gains in hourly time-steps and, more recently, in five minute time-steps. A common approach used to overcome this problem in the past was to select a representative day of a certain period of time and maintain the same results of shading calculations for the rest of the period. Nowadays, the new generation computers have drastically reduced computational costs, but some programs still use the former approach. The present paper assesses the error made by the use of it. Different overhang and side fin typologies and orientations, location latitudes and simulation time-steps have been analysed. 25% of the studied cases have shown annual average relative errors of 5% or greater in the incident solar radiation over the glazing surface. Common configurations, such as south oriented overhangs, show daily deviations of incident solar energy up to 0.48 kW h/m 2 , with a relative error of 17%, having hourly errors as high as 26%. [ABSTRACT FROM AUTHOR]

• That aim is to quantify the impact of urban context on building cooling loads. • Building energy modeling is used to test 108 urban context configurations. • The configurations combine different context heights, distances, and orientations. • Savings of 26% and 24% were observed for total and peak cooling, respectively. • Implications on cooling system sizing and urban planning practices are discussed. This paper presents a systematic evaluation of the impact of the built urban context on the cooling energy performance of buildings subjected to extreme hot weather conditions. The proposed approach combines building energy modeling with an extensive parametric variation and statistical analysis scheme. It provides a direct quantification of inter-building shading on energy performance, with an emphasis on the cooling demand patterns for buildings of different types and sizes. Results show that the combined effects of urban context height, distance, and orientation can lead to significant reductions in cooling demand, reaching up to 26% for total cooling loads and 24% for peak cooling loads. The observed savings are particularly notable for residential buildings, making them an ideal target for urban development strategies that aim to leverage inter-building shading effects for energy conservation purposes. Moreover, an in-depth analysis of peak loads illustrates how the density and compactness of the urban form can be used as passive design strategies to reduce the load, and hence, the size of air conditioning systems. Finally, the paper explores how to translate the gained knowledge to design guidelines, bridging the gap between theory and practice. [ABSTRACT FROM AUTHOR]

• Nonlinear distributed MPC for multi-zone buildings based on Modelica. • Coupling of thermal and hydraulic systems using Nash optimization and ADMM. • Detailed modeling of the thermal coupling through doors based on data-driven models. • Distributed MPC on nonlinear HVAC models with thermal and hydraulic TABS coupling. This paper presents a distributed Model Predictive Control (MPC) approach for multi-zone building energy systems based on nonlinear Modelica controller models. The method considers both thermal and hydraulic coupling among different building zones. The iterative and parallel distributed optimization approach builds upon an uncooperative approach for thermal coupling using the Nash equilibrium approach and a cooperative approach for the hydraulic coupling using the Alternating Direction Method of Multipliers (ADMM). Apart from thermal coupling through walls, the modeling takes thermal coupling through doors into account using a data-driven approach, which calculates the inter-zone air exchanges based on temperature differences between door-coupled zones. The hydraulic coupling enables consideration of interactions between the zones introduced by a shared, central Heating, Ventilation and Air Conditioning (HVAC) system. The distributed MPC framework is structured in an easy-scalable, plug-and-play composition, where local systems are automatically assigned to the global coordination scheme. The distributed MPC method is applied to a simulative nonlinear case study, consisting of a six-room-building Modelica model considering both thermal and hydraulic interactions. The benefits of the proposed approach are demonstrated and compared against centralized and decentralized control concepts in terms of energy consumption, discomfort and computation time. [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]

• Heating and cooling setpoint temperature of thermostats were optimized in a residential building for different climates of Iran. • GMDH-type neural network and NSGA-II algorithm were used for multi-optimization. • XPS is the optimum insulation for all the climates in Iran. • PPD reduces with thickness of insulation for all the cities, except Bandar Abbas. Determination of the optimum setpoint temperature of thermostats in various climates is a problem in air conditioning of residential buildings. In this paper, a new method is developed to optimize the setpoint temperature of thermostats in different climates of Iran. Design variables in the optimization process are heating setpoint, cooling setpoint, thickness, and thermal conductivity of insulations in the building envelopes. The optimization goals are minimizing energy consumption and cost of insulations in addition to maximizing thermal comfort of occupants. Thus, the static payback period (SPP) and the predicted percentage dissatisfied (PPD) indices are selected as objective functions which should be minimized in the optimization process. The methods applied to attain these objectives are numerical modeling by EnergyPlus software, Grouped Method of Data Handling (GMDH) type of Artificial Neural Network (ANN), and Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Therefore in this process, first, EnergyPlus is used to train the neural network. Afterward, the GMDH-type neural network is applied to derive polynomials computing the objective functions from the design variables. Then, Pareto optimal points for the objective functions are obtained through using these polynomials and NSGA-II multi-objective optimization. Finally, the optimum design point is selected for different cities. According to the results, type and thickness of insulation integrated in the building envelopes affect the static payback period and thermal comfort of occupants. For all the climates of Iran, the most appropriate insulation is XPS and the optimum heating setpoint of thermostat is 22 °C. Also, the optimum value for the cooling setpoint pertains to the type of climate, so that this value for Bandar Abbas, Yazd, Tehran, Rasht and, Tabriz is, respectively, equal to 24.5, 24.7, 25.2, 25.3, and 25.6 °C. Moreover, thermal comfort of occupants increases with thickness of insulation, except for Bandar Abbas whose PPD is almost constant. The most value of PPD reduction with insulation thickness is related to Tehran where by increasing the insulation thickness from 1 cm to 5 cm, PPD decreases up to 53%. [ABSTRACT FROM AUTHOR]

• A multi-zone building model based on RC network two-node wall structure method for room temperature is proposed. • The multi-zone building model can accurately simulate the dynamic changes of indoor temperature. • A periodic predictive control model of time-delay system at room temperature based on RBF neural network and multi-zone building model is developed. • The stability of the static pressure of the main air supply duct in the multi-zone VAV air-conditioning system is improved. The multi-zone variable air volume (VAV) air-conditioning system is a complex thermal system with large delay and nonlinearity. Due to the complex environment of multi-zone buildings and the complicated operation process of the VAV air-conditioning system, there are many difficulties in the room temperature control. This paper firstly establishes a multi-zone building model for room temperature using resistance–capacitance method. This investigation simulates and measures the dynamic response of room temperature in a three-floor building without/with air-conditioning for validation. Then a multi-zone VAV air-conditioning system room temperature predictive control model based on radial basis function (RBF) neural network (NN) is proposed. This study sets up a multi-zone VAV air-conditioning system experimental platform in the three rooms on the first floor of the building and implements the predictive control model based on the RBF neural network. The experimental results show that the predictive control model based on RBF NN is able to meet room temperature requirements. It also has strong anti-interference performance and ensures stable static pressure of the main air supply duct. The multi-zone building model can accurately simulate the temperature changes of each room when the air supply volume varies. [ABSTRACT FROM AUTHOR]

Today, Building Energy Models (BEM) have become essential in regulatory compliance calculations, the correct assessment of it's Air Conditioning (AC) systems is critical for the reduction of the performance gap between BEMs and reality and increase the accuracy of evaluating buildings energy performance and it's systems efficiency. Given that multi-split Variable Refrigerant Flow (VRF) systems have grown in the market in recent years becoming a particular trending solution to achieve building indoor comfort; the present paper focus on technical issues when modelling such VRF systems inside EnergyPlus, a white-box simulation environment, especially regarding the effects weather conditions have on the behaviour of VRF systems and it's correlation with the AC system performance curves. The study performs an empirical validation of an optimization-based calibration methodology assessing multiple levels: average interior temperature of the different building spaces and electric energy consumption from VRF outdoor unit. It is performed using fifteen minute time-step seasonal data obtained from a fully operational building located in a typical Mediterranean climate (Greece), adjusting the parameter and curve values of the VRF system using a genetic NGSA-II algorithm (Jeplus software) for both summer and winter conditions. The generated BEM captures the building's hourly performance for summer conditions using 1717 hours to fit into international standards. Complying with the requirements of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Guidelines 14-2002 for hourly energy consumption, reaching an NMBE ⩽ ±10% ,Cv(RMSE) ⩽ 30% and R2 ⩾ 75% while keeping indoor temperatures on every room with a RMSE ⩽ 1 ° C. The resulting BEM proved stable during the 2077 hours of it's summer evaluation period, fitting into the new unseen weather and building operation conditions of 2020 which can be considered a step forward in the area of calibrating white box models. While for winter conditions the study demonstrates the value of the calibration methodology while presenting the importance of weather influence on VRF systems. Using a total of 802 hours the applied technology greatly improves the results from the baseline model, reaching a partially calibrated BEM model for winter. Which reinforces the fact that regardless of how good a baseline model is, building operating conditions and weather may will always generate a design/performance gap and therefore the calibration of a BEM is unavoidable. [ABSTRACT FROM AUTHOR]

This paper discusses the development of a model for evaluating peak load reduction and change in overall energy consumption for a residential air conditioning (AC) compressor with and without condenser-side thermal storage. Stored rainwater (or any other type of on-site water storage) could be utilized as a heat sink for the condenser during peak hours, allowing for more efficient and lower power compressor operation, then re-chilled at night during off-peak hours. The system evaluated in this manuscript is referred to as ‘integrated thermal energy and rainwater storage’ (ITHERST). The model used simulated cooling load data for a typical home in Austin, Texas, based on summer 2011 historical and typical meteorological year (TMY) datasets. The analysis suggests that the ITHERST system with 3785–18,925 l of water could reduce on-peak compressor power demand by approximately 29–53%, as compared to a traditional AC with an air-cooled condenser. However, total compressor energy consumption increases 5–15% because of the inefficiencies of re-cooling the thermal mass, but this additional energy consumption occurs during low demand off-peak hours. System performance varied depending on weather data, the individual compressor, and thermal storage volume. [ABSTRACT FROM AUTHOR]

This paper presents an investigation carried out for evaluating the dynamic thermal performance of a residential house using a multi-zone building model simulated with the help of TRNSYS 17. The building model integrates systems such as an air–air heat exchanger (AAHE), a water–air heat exchanger (WAHE) coupled with an earth–water heat exchanger (EWHE). The temperature based control strategies for these systems are recommended based on the simulation results. The AAHE and the EWHE have impact of 66% and 7% respectively on reduction of the annual heating consumption of the house. All the integrated systems together contribute significantly (72%) in reducing the annual heating consumption of the house. The annual heating consumption of the house per unit floor area is estimated as 6.9 kWh/(m 2 year) which is within the passive house standard. There is significant reduction of the overheating time above 25 °C due to the EWHE installed in the present house with annual ventilation air cooling contribution of 602.6 kWh/year. [ABSTRACT FROM AUTHOR]