Climate Control System Research Articles

Towards energy efficient operation of Heating, Ventilation and Air Conditioning systems via advanced supervisory control design

This paper presents conceptual control solution for reliable and energy efficient operation of heating, ventilation and air conditioning (HVAC) systems used in large volume building applications, e.g. warehouse facilities or exhibition centres. Advanced two-level scalable control solution, designed to extend capabilities of the existing low-level control strategies via remote internet connection, is presented. The high-level, supervisory controller is based on Model Predictive Control (MPC) architecture, which is the state-of-the-art for indoor climate control systems. The innovative approach benefits from using passive heating and cooling control strategies for reducing the HVAC system operational costs, while ensuring that required environmental conditions are met.

An automated approach to quantifying functional interactions by mining large-scale product specification data

ABSTRACTThe authors of this work hypothesise that the semantic relationship between modules' functional descriptions is correlated with the functional interaction between the modules. A deeper comprehension of the functional interactions between modules enables designers to integrate complex systems during the early stages of the product design process. Existing approaches that measure functional interactions between modules rely on the manual provision of designers' expert analyses, which may be time consuming and costly. The increased quantity and complexity of products in the twenty-first century further exacerbates these challenges. This work proposes an approach to automatically quantify the functional interactions between modules, based on their textual technical descriptions. Compared with manual analyses by design experts who use traditional design structure matrix approaches, the text-mining-driven methodology discovers similar functional interactions, while maintaining comparable accuracies. The case study presented in this work analyses an automotive climate control system and compares the functional interaction solutions achieved by a traditional design team with those achieved following the methodology outlined in this paper.

A performance assessment of an office space with displacement, personal, and natural ventilation systems

This paper presents the results of a field study concerning indoor conditions in an office space in Grieskirchen, Upper Austria. The office is equipped with a displacement ventilation (DV) as well as personal ventilation (PV) systems. The space can also be naturally ventilated through the manual operation of windows (NV). The main objective of the study was to assess the functionality of the mentioned ventilation systems with regard to indoor air quality and thermal comfort. The configuration of the indoor climate control system in this office allows for the performance evaluation of the ventilation systems through different methods. In fact, the monitored data and short-term user surveys provide a basis to document the indoor conditions and their implications for the occupants. Our study also illustrated the utility of calibrated CFD models toward a better understanding of the airflow phenomena and estimation of the airflow velocity as an input data for calculation of predicted mean vote (PMV) values. The results suggest that the combined operation of the above mentioned systems provides in general acceptable indoor environmental conditions. However, optimal operation of the systems installed requires the continuous and comprehensive monitoring of indoor conditions, systems states, and occupants’ feed-back.

Energy use and indoor climate of conservation heating, dehumidification and adaptive ventilation for the climate control of a mediaeval church in a cold climate

Mediaeval churches hold substantial historical and cultural values, organs, altars, paintings that need to be preserved. Many of these churches have no climate control systems installed. Thus the indoor climate is mainly determined by the outdoor climate. Focus in this study is on the possibilities to improve indoor climate in originally unheated churches to prevent and protect churches from mould growth and disintegration of wooden parts. A case study in the Church of the Holy Cross in Harju Risti, Estonia, was conducted to test two different indoor climate control systems: dehumidification and an air-to-air heat pump. The systems were controlled with relative humidity to prevent the indoor humidity from dropping low enough to start wood cracking and salt drying in the walls. Based on field measurements, simulation models were calibrated and used to test different climate control systems and their impact on churches’ indoor climate and energy consumption. Our study showed that the adaptive ventilation performs well in high indoor humidity conditions, annual energy consumption of conservation heating with a heat pump is the lowest, and dehumidification is most effective during the cold period.

Advice Provision for Energy Saving in an Automobile Climate‐Control System

Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. The need to save energy becomes even greater when considering an electric car, since heavy use of the climate control system may exhaust the battery. In this article we consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of their climate control unit. Our approach takes into account both the energy consumption of the climate control system and the expected comfort level of the driver. We therefore build two models, one for assessing the energy consumption of the climate control system as a function of the system’s settings, and the other, models human comfort level as a function of the climate control system’s settings. Using these models, the agent provides advice to the driver considering how to set the climate control system. The agent advises settings which try to preserve a high level of comfort while consuming as little energy as possible. We empirically show that drivers equipped with our agent which provides them with advice significantly save energy as compared to drivers not equipped with our agent.

Li-ion battery performance and degradation in electric vehicles under different usage scenarios

Summary Lithium-ion (Li-ion) batteries are well known as an efficient energy storage solution for plug-in hybrid electric vehicles (PHEVs). However, performance and state of health of these batteries strictly depends on the usage scenario including operating temperature, power demand profile, and control strategy imposed by the battery management system. Also, in PHEVs equipped with electric climate control systems, climate control loads are imposed as additional loads on the battery, which results in a reduced all-electric range (AER) and increased battery capacity degradation. In this paper, vehicle AER, and fuel economy and life degradation of an aftermarket LiFePO4 Li-ion battery cell are studied for a PHEV under several usage scenarios. Each scenario consists of a series and parallel PHEV powertrain layout developed in Autonomie software, climate condition, that is, hot and cold weather, and a daily driving and charging profile. For simulations, models of battery performance, heat generation, and degradation developed based on experimental results are integrated with a thermal vehicle cabin model. Impact of climate control loads and battery thermal preconditioning are incorporated in the simulations. It is observed that climate control loads significantly affect the AER (up to 20%), fuel economy (up to 65%), and battery degradation (up to 25%). On the other hand, thermal preconditioning could be used to reduce these impacts. Copyright © 2015 John Wiley & Sons, Ltd.

Thermal battery for portable climate control

Current technologies that provide climate control in the transportation sector are quite inefficient. In gasoline-powered vehicles, the use of air-conditioning is known to result in higher emissions of greenhouse gases and pollutants apart from decreasing the gas-mileage. On the other hand, for electric vehicles (EVs), a drain in the onboard electric battery due to the operation of heating and cooling system results in a substantial decrease in the driving range. As an alternative to the conventional climate control system, we are developing an adsorption-based thermal battery (ATB), which is capable of storing thermal energy, and delivering both heating and cooling on demand, while requiring minimal electric power supply. Analogous to an electrical battery, the ATB can be charged for reuse. Furthermore, it promises to be compact, lightweight, and deliver high performance, which is desirable for mobile applications. In this study, we describe the design and operation of the ATB-based climate control system. We present a general theoretical framework to determine the maximum achievable heating and cooling performance using the ATB. The framework is then applied to study the feasibility of ATB integration in EVs, wherein we analyze the use of NaX zeolite–water as the adsorbent–refrigerant pair. In order to deliver the necessary heating and cooling performance, exceeding 2.5 kW h thermal capacity for EVs, the analysis determines the optimal design and operating conditions. While the use of the ATB in EVs can potentially enhance its driving range, it can also be used for climate control in conventional gasoline vehicles, as well as residential and commercial buildings as a more efficient and environmentally-friendly alternative.

Thermal Model Developments for Electrified Vehicles

Argonne National Laboratory has analyzed the control behavior of advanced vehicles, such as hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), to develop simulation models and to reproduce the performance of vehicles with simulation techniques. Since many of the novel and advanced studies about transportation technologies done at Argonne use these simulation techniques, they must be well-validated to conduct and support these studies. To improve its research ability, Argonne built a new testing facility that can test vehicles under different thermal conditions (e.g., –7°C or 35°C), and it has analyzed the controls and performance of several advanced vehicles under these conditions. Further, Argonne has used the analyzed results to develop thermal component models that reproduce the thermal behavior of the vehicles. A main reason to develop thermal models is that the thermal conditions have such a significantly large impact on vehicle performance, especially with regard to advanced vehicles like HEVs or PHEVs. For instance, engine and battery efficiencies must decrease at low temperatures since the battery might not be able to provide enough power if it is very cold. Moreover, the climate control system still has a great demand for additional energy under very cold weather conditions even if the engine is not operating at all. The test data obtained from Argonne’s Advanced Powertrain Research Facility (APRF) are analyzed in order to understand the thermal impacts on controls and performance, and the thermal models are developed based on the analyzed results and validated with the test data. In comparative studies, the simulation models have been found to reproduce fuel consumption that is very close to the fuel consumption obtained from the tests.

Optimal Energy Management of Greenhouses in Smart Grids

This paper presents a novel hierarchical control approach and new mathematical optimization models of greenhouses, which can be readily incorporated into energy hub management systems (EHMSs) in the context of smart grids to optimize the operation of their energy systems. In greenhouses, artificial lighting, CO2 production, and climate control systems consume considerable energy; thus, a mathematical model of greenhouses appropriate for their optimal operation is proposed, so that it can be implemented as a supervisory control in existing greenhouse control systems. The objective is to minimize total energy costs and demand charges while considering important parameters of greenhouses; in particular, inside temperature and humidity, CO2 concentration, and lighting levels should be kept within acceptable ranges. Therefore, the proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing control systems in greenhouses. Effects of uncertainty in electricity price and weather forecast on optimal operation of the storage facilities are studied through Monte Carlo simulations. The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints.

Strategic advice provision in repeated human-agent interactions

This paper addresses the problem of automated advice provision in scenarios that involve repeated interactions between people and computer agents. This problem arises in many applications such as route selection systems, office assistants and climate control systems. To succeed in such settings agents must reason about how their advice influences people’s future actions or decisions over time. This work models such scenarios as a family of repeated bilateral interaction called “choice selection processes”, in which humans or computer agents may share certain goals, but are essentially self-interested. We propose a social agent for advice provision (SAP) for such environments that generates advice using a social utility function which weighs the sum of the individual utilities of both agent and human participants. The SAP agent models human choice selection using hyperbolic discounting and samples the model to infer the best weights for its social utility function. We demonstrate the effectiveness of SAP in two separate domains which vary in the complexity of modeling human behavior as well as the information that is available to people when they need to decide whether to accept the agent’s advice. In both of these domains, we evaluated SAP in extensive empirical studies involving hundreds of human subjects. SAP was compared to agents using alternative models of choice selection processes informed by behavioral economics and psychological models of decision-making. Our results show that in both domains, the SAP agent was able to outperform alternative models. This work demonstrates the efficacy of combining computational methods with behavioral economics to model how people reason about machine-generated advice and presents a general methodology for agent-design in such repeated advice settings.

Optimal Operation of Climate Control Systems of Produce Storage Facilities in Smart Grids

This paper presents mathematical optimization models of produce storage facilities to optimize the operation of their energy systems in the context of smart grids. In the storage facilities, climate control of the storage rooms consumes considerable energy; thus, in this paper, a mathematical model of storage facilities appropriate for their optimal operation is developed, so that it can be implemented as a supervisory control in existing climate controllers. The proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing climate control systems in storage facilities. The objective is to minimize total energy costs and demand charges while considering important parameters of storage facilities, i.e., inside temperature and humidity should be kept within acceptable ranges. The performance of the proposed model for various electricity prices and weather conditions and their variations are studied via Monte Carlo Simulations (MCS). The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints.

Evaluation of thermal behavior for an asymmetric greenhouse by means of dynamic simulations

In this paper is presented the design of an asymmetric greenhouse, with a simulation and evaluation of its microclimate by means of DesignBuilder®. Climatic and geographical conditions of the greenhouse location are processed with DesignBuilder®, which also allows to include the geometrical characteristics of the enclosure and its roofing, the properties of its building materials and a description of the climate control system. Three configurations of this asymmetric greenhouse are evaluated in order to analyze and compare their internal gains.

Phytochemical composition of onion during long-term storage

Onion cultivar “Sunpower” has growing popularity in Korea due to high storability. The present study considers changes in flavonols, sugars, and two amino acids in onion bulbs during a long-term storage in the ambient dark storage room and in glasshouse equipped with a climate control system. Flavonol and sugar contents were found to fluctuate noticeably during the storage period. Amino acid content remained relatively unchanged till the onset of inner sprouting, increasing afterward. Visible sprouts appeared at week 22 in the dark storage room and for four weeks later in the glasshouse. The bulbs lost 20–30% of their weight depending on storage conditions at the end of the storage trials. At the same time, the content of nutraceutics in study expressed on the dry weight basis remained of the same order of magnitude. The nature of observed variations in chemical composition of onions as well as relation of this phenomenon to physiological development of stored onion bulbs is discussed. A conclusion is made that the “Sunpower” onion cannot sustain overwinter storage.

Modelling of heat and moisture induced strain to assess the impact of present and historical indoor climate conditions on mechanical degradation of a wooden cabinet

To assess the risk of present and future indoor climate conditions within historic buildings on mechanical degradation of wooden art objects, it is of high importance to know the climate variations that these objects might have been exposed to in the past. Historical indoor climate data can indicate climate variations that may have caused damage to objects. Avoiding these variations in the present and future may prevent new or further degradation. However, historical indoor climate data conditions are often not available and cannot be derived from recent indoor climate data as many historic buildings nowadays have climate control systems. In this study, multi-zone hygrothermal building simulation is applied to reconstruct the historical indoor climate in a 17th-century Dutch castle based on meteorological data, building properties, and user behaviour. Furthermore, a finite element model is created to analyse heat and moisture induced strain of a historic wooden cabinet. This cabinet has been located in the castle since the 18th century and shows damage caused by movement of the wood in response to climate variations. Mechanical degradation of the cabinet could have occurred when the strain exceeded the yield strain for safe, reversible deformation. The results show that combining a hygrothermal building simulation model and a finite element model can generate an adequate prediction of the microclimate around an object; though obtaining accurate data on hygroscopic and mechanical material properties can be difficult. Although the cabinet has experienced considerable tension after a conservation heating system was installed in the castle during a recent major renovation, the predicted strain was within the limits for safe, reversible deformation. This corresponds to the observation that no further damage occurred after the renovation. Damage may not be caused by the regular present or historical indoor climate in the castle, but could be indicated if the long-term average moisture content of the wood significantly deviates from the room conditions or if the vapour concentration in the room increases because of a flooding event.

CONCEPT AND REALISATION OF AUTOMATED ROOM CLIMATE CONTROL

The paper deals with technical problems of automated decentralised indoor climate control in residential buildings. The lead value for the realisation of the control system is the objective thermal comfort. The measurement system to be designed works as a network between a large variety of different sensors and actuators. A comprehensive and flexible EIB networked instrumentation using cheap commercial and prototype sensors and actuators has been created and tested in a realistic test environment. In the paper, the conditions for a modern room climate control are discussed and the technical base for data acquisition system containing several different data collection channels is presented. Extensive measurements with the reliable, fully redundant data acquisition system showed its applicability in residential buildings. Based on the presented concept, different systems configurations can be realised. Following the results, a low­cost decentralised automated room climate control system is able to become a new standard in low­energy buildings, opening a huge market potential.

Advice Provision for Energy Saving in Automobile Climate Control Systems

Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. The need to save energy becomes even greater when considering an electric car, since heavy use of the climate control system may exhaust the battery. In this paper we consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of their climate control unit. Our approach takes into account both the energy consumption of the climate control system and the expected comfort level of the driver. We therefore build two models, one for assessing the energy consumption of the climate control system as a function of the system’s settings, and the other, models human comfort level as a function of the climate control system’s settings. Using these models, the agent provides advice to the driver considering how to set the climate control system. The agent advises settings which try to preserve a high level of comfort while consuming as little energy as possible. We empirically show that drivers equipped with our agent which provides them with advice significantly save energy as compared to drivers not equipped with our agent.

Advances on air conditioning and heat pump system in electric vehicles – A review

Abstract There is a rising interest in electric vehicle׳s climate control system including cooling and heating. Electric vehicles (EVs, including hybrid electric vehicles and full electric vehicles) have inadequate waste heat to warm up the cabin and the climate control system has a very significant effect on the energy consumption efficiency and operating mileage. Heat pump (HP) is one approach for energy consumption efficiency improvement in EVs which can supply cooling and heating capacity. A literature review was performed on the vapor compression HP cycle design, performance characteristics, and challenges for variable working fluids for electric vehicles. The non-vapor compressor HP systems were also analyzed including the applications of magnetocaloric effect and thermoelectric effect. It seems heat pump system is a reasonable and feasible option in EV׳s climate control system if some essential issues could be solved. The mobile climate control systems based on magnetocaloric effect and thermoelectric effect could be the supplementary methods in future applications.

ENVIRONMENTAL ASSESSMENT OF DEMARCATED BED-GROWN ORGANIC GREENHOUSE TOMATOES USING RENEWABLE ENERGY

The environmental impacts associated with fossil energy use, in addition to water and fertilization management continue to be major concerns for Northern greenhouse production systems. To reduce the environmental impacts of greenhouse farming under Northern climate conditions and to maintain its competitiveness, the use of renewable energy sources and suitable nutrient management are becoming essential. From this perspective, a closed-loop demarcated bed-grown organic production system that increases the efficiency of water and nutrient use and utilizes waste biomass as a source of energy was developed and tested in the province of Quebec, Canada. The goal of this study was to assess the environmental impacts of this so-called sustainable organic system compared with an open conventional growing system using fossil energy. The environmental analysis was conducted with life cycle assessment methodology as defined by the ILCD handbook (2010) and the SimaPro v.7.3.2 software. The functional unit was 1,000 kg of tomatoes and 1 ha of cultivated area. The system boundary was from raw materials extraction to the farm gate. The life cycle stages considered were infrastructure, auxiliary equipment, climate control system, farm operation, fertilizers, pesticides, waste management and packaging. For both growing systems, results from the environmental assessment indicate that high energy demand was the main contributor to all impact categories. When organic farming using wood biomass as renewable energy was applied, the CO2 footprint of 1 kg of tomatoes was 0.812 kg CO2 eq kg-1, while the impact of an open conventional growing system using fossil energy was 5.788 kg CO2 eq kg-1. The fertiliser assessment of the closed-loop organic crop had a lower environmental burden on abiotic depletion (by 12 times), acidification (by 6 times), eutrophication (by 136 times) and global warming (by 10 times) compared with the fertiliser assessment of the open conventional growing system.

Hygrothermal modelling of flooding events within historic buildings

Flooding events pose a high risk to valuable monumental buildings and their interiors. Due to higher river discharges and sea level rise, flooding events may occur more often in future. Hygrothermal building simulation models can be applied to investigate the impact of a flooding event on the environmental conditions inside a building. The objective of this study is to develop such a model that is able to evaluate the best fitting drying regime for historic buildings. A model is created based on on-site measurements of the indoor climate conditions in one building that had to cope with flooding in the recent past. The result of this study is a hygrothermal building simulation model that can predict the indoor climate conditions inside a room as a result of a flooding event. Different climate control systems can be integrated in this model to evaluate the most suitable drying regime to minimise the risk to the building, its interior and its collection. Furthermore, damage functions can be applied to analyse the risk to the collection caused by the flooding event.

USING A WIRELESS SENSOR NETWORK TO DETERMINE CLIMATE HETEROGENEITY OF A GREENHOUSE ENVIRONMENT

One of the main targets of a greenhouse control system is to generate a uniform climate environment, which has obvious economic advantages, due to homogenous crop, lesser diseases and the potential energy saving. By using a dense wireless sensor network, the spatial distribution of climate parameters and thus the uniformity of greenhouse environment can be determined. This information can be used by the growers to detect cold and wet spots in greenhouse environment and to adjust their climate control system. In this study, the horizontal climate heterogeneity of the greenhouse environment is analysed. Six experiments were performed in commercial greenhouses observing the micro-climate with 100 wireless sensors under different conditions and for different crops. From the data the spatial and temporal distribution of air temperature T and relative humidity RH was obtained. Instantaneous spatial differences varied up to ±5°C for T and ±20% for RH, depending on location, time of day and season. Significant differences of ±2°C for T and ±12.5% for RH, while averaging data over longer periods (5 days), have been observed. Further research is needed to investigate the way the information regarding the spatial and temporal distribution of climatic parameters can be integrated in the control systems and finally to quantify the energy saving potential.