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In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan , which is computed the day before the beginning of operation. In this paper, we propose a method to optimally compute the dispatch plan so as to optimize the operation of the feeder while making sure to allocate enough local reserves to absorb deviations of the realizations. Indeed, during real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan. This is achieved by modulating the power consumption of a utility-scale battery energy storage system and of the heating, ventilation and air conditioning system of a commercial controllable building. To this end, a hierarchical controller is designed to coordinate these two controllable entities while requiring a minimal communication infrastructure. Due to the inherent different response times of these systems, the power injection of the electrical battery is controlled at a sub-minute time-scale so as to absorb high-frequency tracking errors and, therefore, deliver the dispatch service. At a slower time-scale, the controllable building is controlled to maintain the state of charge for the electrical battery at a scheduled level by means of a model predictive controller. The model predictive controller is designed in order to account for both comfort and operational constraints of the controllable building, as well as power limits for the electrical storage. The effectiveness of the proposed control framework is demonstrated by means of both an extensive simulation analysis, as well as a set of 12 full day experimental results on the 20 kV distribution feeder in the campus of the Swiss institute of technology in Lausanne, that is comprised of: 1) A set of uncontrollable resources represented by five office buildings (350 kWp) and a roof-top photovoltaic installation (90 kWp), 2) a set of controllable resources, namely, a grid-connected electrical storage (720 kVA–500 kWh), and a fully-occupied multi-zone office building (45 kWp). [ABSTRACT FROM AUTHOR]

Heating Ventilation and Air Conditioning (HVAC) systems are ubiquitous. Up to 40% of energy consumption in a building goes out on account of HVAC systems and thus it becomes a vital focus area for any initiative to improve energy efficiency. This has become imperative due to the increasing focus on curtailing rising costs and reducing CO2 footprint of the industry. Thus, finding ways to decrease the energy consumption is a continuous process and one that reaps rewards in more than one way. The need to ensure the integrity of systems housed in the building, be it sensitive electronic process control panels or computer servers, while implementing energy conservation measures, adds an element of process risk and requires a thorough study before any such implementation. The paper discusses some innovative case studies, some of which were part of National Award winning energy-efficiency measures in India, where one of the (Principal) authors was directly responsible for implementation. The focus is on practical and economical solutions that can be implemented immediately without resorting to complicated concepts like networked sensors or fuzzy logics. [ABSTRACT FROM AUTHOR]

Abstract: Based on a large number of researches and engineering practices both domestic and overseas, it is shown that the building parameters to be determined during scheme phase can exert a great effect on the building energy consumption. In this paper, through a combination of the popular design method of building parameterization at present and the design goal of energy saving during the scheme phase, the author carries out researches on the design methods and tool development which are applicable to parameterization of building energy saving in this stage. In connection with the characteristics of both modeling process of parameterization and energy saving design, and by means of steady calculation as well as simulation, this paper establishes an simplified model to calculate the overall energy consumption of air-conditioning, heating, lighting and equipments, and ultimately gives suggestions on design of scheme for energy saving by optimization with the genetic algorithm (GA). On the basis of the model, a software platform is developed by computer language QT and openGL interface and is oriented to the design users and sets up the MMI (human–computer interaction) software interface for parameterization of building energy saving, which achieves automatic modeling of parameterization and promotes research on practical design cases. [Copyright &y& Elsevier]

Abstract: Globally, buildings are responsible for 40% of the total world annual energy consumption which is responsible for one-third of green house gas emissions around the world. A significant portion of this energy is used for lighting, heating, cooling, and air conditioning purposes in buildings. Increasing awareness of the environmental impact of green house gas emissions and CFCs triggered a renewed interest in environmentally friendly cooling, and heating technologies for buildings. Free cooling of buildings may be seen as an alternate to compressor based air conditioning systems used for the buildings. In free cooling, nighttime cold is accumulated in storage material and extracted when needed. Latent heat storage using phase change materials (PCMs) can be used for free-cooling purposes due to their high storage density. In free cooling, using PCM as storage material, cool air during night is used to solidify the PCM and the accumulated cold is extracted during the hot day times. In this article a detailed review of work conducted by different researchers on PCM based free cooling is presented. Major challenges being faced in the design of PCM based free cooling system such as phase change materials; their thermo-physical properties and the geometry of encapsulation are elaborated and discussed in detail. Also the parameters effecting the charging and discharging of PCM, effect of phase change temperature and climatic conditions on thermal performance of the free cooling system are also discussed. Potential reduction in CO2 emissions due to the applicability of free cooling systems in residential and commercial buildings is also discussed in this article. This paper also provides a comprehensive list of the PCMs currently being used and that can be used potentially for free cooling applications. At last, this paper also presents some current problems needed further research in this area. [Copyright &y& Elsevier]

There have always been discussions about how to use our environment and resources, to keep them for the future human generations. Using natural resources have always been the best option in any era. It is clear that ventilating, cooling, and heating the environment of the buildings are massive energy consumers which this forces the designers to take more responsibility in the matter. The interesting concept that the past generations used with minimum technology in getting advantages of the natural resources in the building designs, is easily applicable nowadays with the improved scientific knowledge. One of the best examples of this, is the ventilation Wind Towers (Wind Catchers), which were massively used in the Middle East, especially in the city of Yazd in Iran. In this paper, we describe the principles and elements used in the historic Persian Architecture for saving energy with the help of natural resources like wind catchers and domes. We will demonstrate how to use these simple but smart principles in the modern design of our buildings to save our irreversible energies [ABSTRACT FROM AUTHOR]

Aiming to utilize the flexibility of smart buildings for flexible operation of active distribution network, a combined modeling and optimal scheduling method for the active distribution network with integrated smart buildings is proposed in this paper. Based on the heat storage characteristics of a building, the energy consumption prediction model of the building considering different heating zones with different orientations is developed using the Resistor-Capacitor thermal network model. Then, different optimal control methods of the heating, ventilation and air-conditioning system in the building are developed. The energy consumption management of the heating, ventilation and air-conditioning system is achieved by adjusting the room temperature within the suitable temperature comfort range. In order to further consider the impact of the integration of smart buildings on the economic and security operation of the active distribution network, the optimal scheduling method of the active distribution network with integrated smart buildings is developed considering the load factor of the aggregation of the smart buildings. Finally, the optimal scheduling results of the aggregation of the smart buildings under different heating, ventilation and air-conditioning control methods in the winter heating scenario are analyzed. In addition, based on the branch flow model, the optimal power flow model of active distribution network with on-load tap changer is constructed by piecewise linearization and second-order cone relaxation to achieve flexible and optimal operation of the active distribution network. Thus, the impacts of the optimal schedules of the aggregation of smart buildings on the economic and security operation of the active distribution network are further evaluated. Numerical studies demonstrate that the proposed optimal scheduling method can make full use of the demand response potential of the smart buildings and further contribute to the operating costs reduction of the smart buildings. Meanwhile, the optimization of the active distribution network with the load factor of the aggregation of buildings can reduce the power loss and increase the minimum voltage magnitude of the active distribution network utilizing the flexibility of the smart buildings. [ABSTRACT FROM AUTHOR]

Recent building control models have adopted advanced algorithms to replace conventional controllers to improve the performance of plant or system levels. However, most models used to optimize fuel use or fan speed have several disadvantages to respond to, accurately and promptly, zone-scaled level. This paper proposes network-based controllers utilizing Artificial Neural Network (ANN) in space cooling and heating through the simultaneous control of the amount of supply air and its temperature. Two controllers are developed to evaluate the optimum of supply air conditions for a swing season that requires both moderate heating and cooling and they are compared to conventional thermostat on/off model by using the total control errors and energy consumption for operating damper and resistance coil. The result describes the advantage of the ANN simultaneous control that control errors reduce by 61.5% and energy consumption decreases by 3.5% in comparison with on/off controller. The ANN controller effectively optimizes the supply air conditions to reduce control errors and energy consumption, as they relate to human comfort and energy savings in a swing season. [ABSTRACT FROM AUTHOR]

Real-time optimization (RTO) has been developed to improve the cost and/or energy efficiency of complex heating, ventilation and air-conditioning (HVAC) systems. In current literature, almost all of the developed real-time optimization methods belong to the type of time-driven optimization, in which the action of optimization is triggered by “time”. As optimization should be done when the system operating conditions experience a change that is large enough to cause current operational setting not optimal any more, optimization strategies should recognize ‘significant’ changes and perform optimization when necessary. Since the time-driven optimization is a periodic mechanism in nature while those ‘significant’ changes may not be periodic, the time-driven optimization cannot capture ‘significant’ changes and do the optimization promptly. Therefore, this paper proposes an event-driven optimization (EDO) for complex HVAC systems, the key idea of which is to use “event” rather than “time” to trigger the action of optimization. A systematic event-driven optimization method is illustrated, where its main tasks, including event definition and event identification, will be discussed. The proposed method will be compared with a conventional time-driven method using case studies, through which the main advantages of the proposed method will be identified. [ABSTRACT FROM AUTHOR]

Building energy simulators such as TRNSYS, EnergyPlus, and Esp-r offer an excellent opportunity for detailed design of house thermal model and its Heating, Ventilating, and Air Conditioning (HVAC) system and provide very accurate simulation results useful for performance analysis and optimization process. In contrast, these energy simulators do not include sub-models of advanced devices/strategies for control of HVAC system operation and suffer from poor control mechanism. In addition to lack of an advance controller, they inherently offer no mechanism for estimating the future state of their process models based on forecast weather dataset. Hence, no predictive controller can be designed and implemented within these simulators. This paper discusses the development of a Matlab-TRNSYS co-simulator in order to control/manage a TRNSYS program, which was previously developed and calibrated based on the characteristics of a real case study house, with an advanced predictive controller. This co-simulator investigates the effectiveness of different predictive strategy planning models, including Load Shifting (LSH), Smart Dual Fuel Switching System (SDFSS), and LSHSDFSS, as the integration of fuel switching and load shifting strategy planning models on 24 h ahead energy cost saving of the case study house HVAC system. Simulation results of different consecutive sample days indicate that SDFSS could bring significant energy cost saving. However, LSH and LSHSDFSS effectiveness is sensitive to the outdoor temperature. [ABSTRACT FROM AUTHOR]

To date, religious facilities have received little attention in the published literature regarding energy use and efficiency. With unique operating and building characteristics, these buildings have distinct opportunities for analysis in regards to building energy use and occupant comfort. With overall lower average energy intensity, religious facilities rarely receive energy assessments or are operated by experienced personnel. Therefore, identifying common issues is critical for training church owners in energy efficiency. This paper presents an in-depth analysis of heating, ventilation and air conditioning (HVAC) systems and occupant comfort in two religious facilities. The analysis reveals that the largest opportunities for reduction in energy use come from proper maintenance and operation of HVAC equipment and schedules. Temperature setbacks are shown to be an important operational setting to reduce energy usage. An accompanying analysis on thermal comfort reveals that temperature setbacks must be coupled with sufficient preconditioning of the space to ensure occupant comfort during intermittent building occupancy. An analysis of CO 2 levels in the building during occupancy reveals the need for sufficient outside air to meet ventilation standards. [ABSTRACT FROM AUTHOR]

Roccotelli et al. (2020) [[11]] proposed an integrated method to model the behaviour of occupants in a building and employ intelligent building energy management for passive cooling techniques. While reducing the energy consumption of HVAC presents a great opportunity to curb energy demand growth rates, occupancy comfort and health must not be compromised [[4]]. A large portion of energy use in the building is due to heating, ventilation, and air-conditioning (HVAC) systems [[3]]. The built environment sector is responsible for a significant proportion of the final global energy consumption [[1]] and carbon emissions. [Extracted from the article]

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]

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]

Heat pump technology fully shows the principle of energy recycling in terms of Heating, Ventilating and Air Conditioning (HVAC). It avoids unipolarity of energy using in the conventional HVAC system. Heat pumps use high-grade energy as a driving energy, recovering and upgrading low-grade energy for avail, like a pump. Because heat source used in HVAC usually is low temperature heat, heat pump systems adopted in HVAC will help improve heating performance coefficient. Therefore, HVAC is one of ideal users of heat pump applications, and thus high-grade energy used in HVAC can be replaced with a large number of low-temperature renewable energy. Through the heat pump technology, natural low-grade energy stored in the soil, water, air or waste heat from variant industries and daily lives, is supplied for building cooling/heating and hot water serving. Therefore, vast applications and developments of heat pump technology are presented in HVAC in China, and some progresses are achieved in the system innovation, experimental research, product development and engineering application, etc. This paper reviews the progress of researches, applications and development in the field of heat pumps for building cooling/heating in China since the 21st century. [ABSTRACT FROM AUTHOR]

The operating efficiency of heating, ventilation and air conditioning (HVAC) system is critical for building energy performance. Demand-based control is an efficient HVAC operating strategy, which can provide an appropriate level of HVAC services based on the recognition of actual cooling "demand." The cooling demand primarily relies on the accurate detection of occupancy. The current researches of demand-based HVAC control tend to detect the occupant count using cameras or other sensors, which often impose high computation and costs with limited real-life applications. Instead of detecting the occupant count, this paper proposes to detect the occupancy density. The occupancy density (estimated by image foreground moving pixels) together with the indoor and outdoor information (acquired from existing sensors) are used as inputs to an artificial neural network model for cooling demand estimation. Experiments have been implemented in a university design studio. Results show that, by adding the occupancy density, the cooling demand estimation error is greatly reduced by 67.4% and the R value is improved from 0.75 to 0.96. The proposed approach also features low-cost, computationally efficient, privacy-friendly and easily implementable. It shows good application potentials and can be readily incorporated into existing building management systems for improving energy efficiency. [ABSTRACT FROM AUTHOR]

Nowadays, energy saving is considered a key issue worldwide, as it brings a variety of benefits: reducing greenhouse gas emissions and the demand for energy imports and lowering costs on a household and economy-wide level. Researchers and building designers are looking to optimize building efficiency by means of new energy technologies. Changes can also be made in existing buildings to reduce the energy consumption of air conditioning systems, even during operational conditions without dramatically modifying the system layout and have as low an impact as possible on the cost of the modification. These may include the usage of new heat transfer fluids based on nanofluids. In this work, an extended experimental campaign (from February 2020 to March 2021) has been carried out on the HVAC system of an educational building in the Campus of University of Salento, Lecce, Italy. The scope of the investigation was comparing the COP for the two HVAC systems (one with nanofluid and the other one without) operating concurrently during winter and summer: simultaneous measurements on the two HVAC systems show that the coefficient of performance (COP) with nanofluid increased on average by 9.8% in winter and 8.9% in summer, with average daily peaks of about 15%. Furthermore, the comparison between the performance of the same HVAC system, working in different comparable periods with and without nanofluids, shows a mean increase in COP equal to about 13%. [ABSTRACT FROM AUTHOR]

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This article explores regional impacts on near-surface air temperature and air conditioning (AC) electricity consumption due to projected urban expansion in a semiarid environment. In addition to the modern-day urban landscape setting, two projected urban expansion scenarios are analyzed with the Weather Research and Forecasting Model coupled to a multilayer building energy scheme. The authors simulate a 10-day extreme heat period at high spatial resolution (1-km horizontal grid spacing) over Arizona, one of the fastest-growing regions in the United States. Results show that replacement of natural land surfaces by buildings and pavement increases the local mean near-surface air temperature considerably. Furthermore, present-day waste heat emission from AC systems increases the mean nighttime 2-m air temperature by up to 1°C in some urban locations, but projected urban development aggravates the situation, increasing nighttime air temperatures by up to 1.5°-1.75°C. The contribution of anthropogenic heating due to AC systems is computed through comparison of two different types of numerical experiments: in one case, a specific urban scenario is simulated with the AC systems turned on and expelling heat into the outdoor environment, and in the second case, the same urban development (with the AC systems turned on) is simulated but with no heat expelled into the outdoor environment. The results demonstrate that projected urban expansion significantly amplifies local cooling energy demands for the Phoenix and Tucson metropolitan regions and therefore highlight the need for sustainable future energy needs to maintain thermal comfort levels. [ABSTRACT FROM AUTHOR]