Smart Heating System Research Articles

Advanced smart HVAC system utilizing borehole thermal energy storage: Detailed analysis of a Uppsala case study focused on the deep green cooling innovation

This article presents and thoroughly examines an innovative, practical, cost-effective, and energy-efficient smart heating, ventilation, and air conditioning (HVAC) system. The fundamental component of this concept is a state-of-the-art method called Deep Green Cooling technology, which uses deep drilling to utilize the ground's heating and cooling potential directly without the need for machinery or heat pumps. This method satisfies demands with the least energy use, environmental impact, and operational costs. In order to effectively oversee and regulate energy production, storage, and utilization, the system consists of an intelligent control unit with many smart controllers and valves. Renewable energy deployment is made easier, and the intelligent automation unit is more compatible with the help of a high-temperature cooling resource with a high supply temperature of 16 °C. The technical, environmental, and financial aspects of the suggested smart office building system in the southern region of Uppsala, Sweden, are evaluated using TRNSYS software. According to the results, boreholes provide more than 28.5 % of the building's energy requirements by utilizing the ground's ability to generate affordable, dependable seasonal thermal energy. The district heating network satisfies the remaining demand, amounting to 787.2 MWh, highlighting the benefits of combining conventional and renewable energy sources for increased supply security and dependability. The borehole thermal energy storage system meets the building's entire cooling need, underscoring the importance of high-temperature cooling systems. The most expensive part of the system is the borehole thermal energy storage, which accounts for over half of the total investment. The system has an appropriate payback period of ten years, proving its long-term profitability and cost-effectiveness, thanks to removing the machinery and heat pump. With 3138 MWh of ground-source heating and cooling, the system saves 17,962 USD by reducing CO2 emissions by about 143.7 t, sufficient to grow 16.3 ha of trees throughout the payback period.

Smart home technology adoption in Denmark: Diffusion, social differences, and energy consumption

Smart home technology (SHT) is increasingly entering homes to provide services such as energy management, security, comfort, and convenience. However, research shows that adoption varies across social groups and that SHT might affect energy demand. Denmark is considered a frontrunner in the uptake of SHT and offers a unique opportunity to combine administrative household information with energy consumption data and survey responses on SHT uptake. This paper studies a representative sample of 1,468 Danish households to investigate SHT diffusion, social differences in SHT adoption, and correlations between SHT and energy consumption, divided into appliance use and heating. The results indicate that entertainment and home security are the most popular SHT services in Denmark and that SHT is more widespread among younger households, especially for entertainment and robotic help. In contrast, smart heating systems are more widespread among older households. Living in a detached house seems to increase the likelihood of having SHT, while the highest income group appears more likely to have security systems, and technical education seems associated with the adoption of SHT for heating management. Finally, smart security systems were associated with higher electricity consumption, and SHT for electricity management was associated with higher heating consumption and to a lesser extent higher electricity consumption, but there was no significant correlation between having smart heating control and heating consumption.

Investigations for the development of smart trousers for paraplegic wheelchair users. Part 2 – Development of a test prototype of smart heating trousers

The main objective of this research was to develop smart trousers for paraplegic wheelchair users to improve the thermal comfort of their lower extremities when exposed to cold environments. In this part of the research, a test prototype of smart heating trousers was developed and tested on the thermal manikin. The development of the test prototype of the smart heating trousers is based on the design recommendations explored in the first part of this paper. The design recommendations relate both to the development of a trousers pattern design for the sitting posture of wheelchair users and the possibility of integrating electrical components into the trouser design, as well as the development of a smart heating system that provides safety for the wearer of the trousers. The results of this part of the research show that the developed smart heating trousers can improve the thermal insulation of the legs and the thermal comfort of the wearer. This is ensured by a carefully planned and safe algorithm that automatically regulates the temperature of the microclimate inside the trousers.

Investigations for the development of smart trousers for paraplegic wheelchair users. Part 2 – Development of a test prototype of smart heating trousers

The main objective of this research was to develop smart trousers for paraplegic wheelchair users to improve the thermal comfort of their lower extremities when exposed to cold environments. In this part of the research, a test prototype of smart heating trousers was developed and tested on the thermal manikin. The development of the test prototype of the smart heating trousers is based on the design recommendations explored in the first part of this paper. The design recommendations relate both to the development of a trousers pattern design for the sitting posture of wheelchair users and the possibility of integrating electrical components into the trouser design, as well as the development of a smart heating system that provides safety for the wearer of the trousers. The results of this part of the research show that the developed smart heating trousers can improve the thermal insulation of the legs and the thermal comfort of the wearer. This is ensured by a carefully planned and safe algorithm that automatically regulates the temperature of the microclimate inside the trousers.

Embodied competencies and smart home technology in energy use: three ways users integrate smart heating systems in everyday practices

Smart heating systems are increasingly entering the domestic sphere. Such smart home technology (SHT) intends to provide comfort, control, and convenience in the home as well as energy efficiency and energy flexibility. However, the success of these promises depends on users’ ability to implement the SHT in everyday practices. In previous research, the importance of embodied competences acquired through previous experiences has gotten little attention. In this paper, we argue that broad scale implementation of SHT requires more knowledge on the interaction between previous experience in the formation of new competences and domestic heating practices.In this paper, we explore how users integrate new smart technologies into their everyday heating practices in different ways by focusing on embodied competences. Based on 24 qualitative household interviews with SHT users, conducted through two Danish case studies, we identified three ways of approaching and integrating SHT in heating practices. First, the reluctant appears hesitant when adopting SHT and loses interest quickly. Second, the compliant follows orders and does what is expected by the new setup. Third, the committed encompasses a playful approach and shows strong interest in SHT design.From this background, we find that embodied competences and previous experience are essential for how users adopt and integrate SHT in everyday life. For example, some users’ previous experience, here younger and technically interested individuals, may match well with the logics of SHT, and for some users, here older and less tech-interested individuals, previous experience may not match well with SHT.

Smart District Heating Networks in the Era of Energy Transformation

Abstract District heating, which accounts for half of the EU’s energy consumption, still relies heavily on fossil fuels. This causes emissions of dust and greenhouse gases and into the atmosphere and leads to negative climate changes. For this reason, European Union countries have been implementing a climate and energy policy for many years, which in the area of heating is aimed at making it more efficient and sustainable. This requires the introduction of low-carbon technologies and the reduction of fossil fuel consumption by increasing the share of renewable energy sources. Modern, efficient and smart heating systems should guarantee reliable heat supply while reducing the environmental impact. The article discusses the direction of change and development of district heating systems through the introduction of innovative technologies. The new generations of 4GDH and 5 GDH district heating systems are described and the benefits of their use are indicated. The concept of smart district heating networks, their structure and the advantages of their implementation are discussed. The possibilities of creating smart energy systems using renewable energy sources and heat storage technologies were also indicated. The activities of Polish district heating companies in the introduction of smart heat networks are presented, based on research conducted.

Technological fascination and reluctance: gendered practices in the smart home

Smart home technology (SHT) is becoming more widespread, implemented to enhance convenience as well as energy flexibility and efficiency. Smart heating, lighting, security and entertainment systems are affecting social practices and the use of energy in different ways. This paper explores differences in competences, meanings and forms of knowledge involved in the performance of (gendered) household practices based on two Danish qualitative studies of different user groups: SHT frontrunner households (<em>n</em> = 15) and less tech-interested households (<em>n</em> = 12). The former had incorporated a broad range of smart technologies, <em>e.g</em>. vacuum cleaners, lighting and entertainment systems, while the latter were primarily engaged with smart heating systems. In the frontrunner households, internal differences in competences and meanings between men and women were more apparent than in households with less tech interest. A clear division between traditional and digital housekeeping is apparent that reinforces gender inequality. Evidence shows the variation in how SHT is part of gendered everyday practices; how SHT changes meanings and competences in practices and induces new ways of performing practices that can involve gendered digital inequality. Thus, it is necessary to consider competences and meanings in everyday practices as well as gendered ideas behind the technology. <em><strong>Policy relevance</strong></em> Strategies and policies for a green transition of the energy systems in Denmark and the European Union include a digitalisation of consumption in households. This transition will induce reconfigurations of everyday practices potentially entailing both digital and gendered inequality. The home has often been a contested space, relating to gender roles, inequality and division of household labour. This paper shows that SHT potentially reinforces gender inequality by creating a gendered gap between digital and traditional housekeeping. To avoid potential reinforcement of gender inequality within the home, SHT promotion and development needs to account for gender differences. Actions by industry would include differences of gendered housekeeping, showing an awareness of varying technology competences and meanings in everyday practices as well as the gendered vision of SHT and its users.

Modeling, Analysis, Design, and Simulation of a Bidirectional DC-DC Converter with Integrated Snow Removal Functionality for Solar PV Electric Vehicle Charger Applications

Different factors affect solar photovoltaic (PV) systems by decreasing input energy and reducing the conversion efficiency of the system. One of these factors is the effect of snow cover on PV panels, a subject lacking sufficient academic research. This paper reviews and compares current research for snow removal in solar PV modules. Additionally, this paper presents the design, analysis and modelling of a smart heating system for solar PV Electric Vehicle (EV) charging applications. The system is based on a bidirectional DC-DC converter that redirects the grid/EV-battery power into heating of the solar PV modules, thus removing snow cover, as well as providing the function of MPPT when required to charge the EV battery pack. A control scheme for each mode of operation was designed. Subsequently, a performance evaluation by simulating the system under various conditions is presented validating the usefulness of the proposed converter to be used in solar PV systems under extreme winter conditions.

The energy saving potential of retrofitting a smart heating system: A residence hall pilot study

Energy conservation is of increasing importance in contemporary society. A large fraction of energy end-use can be attributed to space conditioning. Therefore, intelligent control systems were devised and commercialised in the form of smart thermostats. Hereto, the availability of occupancy information is essential such that heating and/or cooling schedules can be tailored to user needs. This way energy savings can be obtained without jeopardising user satisfaction. However, preceding studies generally rely on simulations to estimate the potential reduction in energy consumption. This work aims at quantifying the potential based on a real life experiment. The development of a smart heating system is presented along with the results of an actual field test of retrofitting this system in 14 single-user student rooms of a university residence hall. An experiment was conducted in which the heating was automatically steered for 1 week (26 March 2018–01 April 2018). Total energy savings range between 26.9% and 59.5% and calculated thermal comfort was not significantly affected by the autonomous control. Furthermore, an environmental impact reduction of 3.2 to 12.9 EcoPoints is estimated for the controlled week, resulting in a reduction of 37.5 to 150.2 kgCO2eq.

Testing smarter control and feedback with users: Time, temperature and space in household heating preferences and practices in a Living Laboratory

Transitioning to more efficient and less carbon-intensive heating is a monumental policy challenge in the United Kingdom. However, very few households in the UK—and perhaps even elsewhere—have actual experience with state-of-the-art smart heating systems that may utilize enhanced control or feedback. Drawing from a unique sample of actual adopters of smart heating, this study closely examines the heating preferences, practices, and profiles of homes when they are given smarter heating systems. The study utilizes qualitative household data from the Energy System Catapult’s Living Laboratory of 100 smart homes in Birmingham (West Midlands), Bridgend (Wales), Manchester (Greater Manchester), and Newcastle (Northumberland). We examine the heating preferences and profiles of participants, with findings inductively organized around the themes of temperature, including tradeoffs between comfort, cost, and value; time, including the utility of heat scheduling; and space, including zonal heating controls. We also discuss patterns of learning, the emergence of environmental values, and issues of discomfort. We conclude by commenting on important distinctions between radiant and ambient heat, as well as between scheduled and on-demand heat. The main findings are 1) tradeoffs between comfort, value and cost occur when it comes to smart heating; 2) people want different numbers of warm hours in their homes at very different times; 3) households chose to heat different numbers of rooms; and 4) there are other non-monetary and non-functional aspects of smart heating that households value.

Digital Forensics of Internet of Things Smart Heating System Investigation

The Internet of Things (IoT) integrates the Internet and electronic devices with applicability to a large spectrum of domains, from smart home automation, industrial processes, military applications, to health and environmental monitoring. Despite the clear advantages, from a forensically sound perspective, IoT can improve the accuracy and integrity of forensic investigations, but still requires extensive scientific validation in practice. In this paper, we review selected stateof-the-art challenges corresponding to digital forensics of IoT environments, and we present an empirical method on how to investigate a security incident reported for an IoT specific case - Smart Heating system.

Digital twin of an urban-integrated hydroponic farm

AbstractThis paper presents the development process of a digital twin of a unique hydroponic underground farm in London, Growing Underground (GU). Growing 12x more per unit area than traditional greenhouse farming in the UK, the farm also consumes 4x more energy per unit area. Key to the ongoing operational success of this farm and similar enterprises is finding ways to minimize the energy use while maximizing crop growth by maintaining optimal growing conditions. As such, it belongs to the class of Controlled Environment Agriculture, where indoor environments are carefully controlled to maximize crop growth by using artificial lighting and smart heating, ventilation, and air conditioning systems. We tracked changing environmental conditions and crop growth across 89 different variables, through a wireless sensor network and unstructured manual records, and combined all the data into a database. We show how the digital twin can provide enhanced outputs for a bespoke site like GU, by creating inferred data fields, and show the limitations of data collection in a commercial environment. For example, we find that lighting is the dominant environmental factor for temperature and thus crop growth in this farm, and that the effects of external temperature and ventilation are confounded. We combine information learned from historical data interpretation to create a bespoke temperature forecasting model (root mean squared error &lt; 1.3°C), using a dynamic linear model with a data-centric lighting component. Finally, we present how the forecasting model can be integrated into the digital twin to provide feedback to the farmers for decision-making assistance.

Cost of the “Internet of Things”

Energy Networked electronic devices, often called the “Internet of Things,” play an increasing role in modern life. But will their use cause overall energy use to fall or rise? In a Perspective, Hittinger and Jaramillo explain that individual devices may lower local energy use; for example, a smart heating system in a house can optimize energy use. However, remote energy use, device production, and user behavior must also be taken into consideration. For example, if households buy more devices than in the past, then the overall energy use may go up. Research into these aspects of device use must inform policy so that society can capture the benefits of the Internet of Things while avoiding rising energy use. Science , this issue p. [326][1] [1]: /lookup/doi/10.1126/science.aau8825

Vulnerability Analysis of A Smart Heating System

Abstract The opportunities offered by the smart city and the smart home to create livelier cities and homes in cities of increasing populations. [1] Meanwhile, there may be more problems which the average user does not yet think about. Focusing on these issues will be of utmost importance for information security and IT security, as the development of technology may not be able to keep up with a society such technologies are used in. On a theoretical and practical level, I examine an intelligent heating system for IT vulnerability, as well as some cases of attacks against IoT in recent years.

Mathematical modelling of smart solar heating system with the deployment of borehole thermal energy storage to increase renewable heat share in Dundee, UK.

The chance of achieving 12% of renewable energy in heating demand by 2020 has gone, as the current RES share is almost the half of this target. The UK struggle to address this deficit, but it still needs more deployment of renewables. Solar energy has proved its viability and is going to play a significant role in increasing the share of renewable heat in domestic heating demand. What makes it more promising than before is that scientists have dealt with many challenges that weaken its growth. Namely, seasonal thermal energy storage that used to solve the mismatch between surplus solar energy in summer and high heating demand in winter. This study investigates the performance of a fully electrified smart heating system [1] that combines solar photovoltaics, borehole thermal energy storage and heat pumps, and compare the results of different sizes communities in Dundee to track the behaviour of BTES and the whole system. Different Solar Fraction and RES Percentage have been achieved with varying demands of heating and different sizes communities.

The role of knowledge about user behaviour in demand response management of domestic hot water usage

Load balancing is an important topic in smart grid systems. Dynamic pricing is a common approach to achieve a better balance between renewable energy production and energy usage. This assumes that individual households adapt their energy usage patterns based on energy prices. However, the actual behaviour of consumers in a household is an uncertain factor that might influence the effectiveness of pricing strategies. In this paper, we investigate to what extent knowledge about actual user behaviour can contribute to local optimization of energy usage. We use simulations to study whether a smart heating system that applies a pre-heating strategy for domestic water during periods of low prices can benefit from good predictions of the user behaviour, in financial terms or in terms of energy saving. Also, we use the simulations to investigate the effect of different goal temperatures for the pre-heating strategy. The results show that pre-heating does not make a difference with respect to the energy efficiency, but that during cold months, pre-heating can result in a financial benefit. In addition, we calculate what certainty about the user behaviour is needed to be able to effectively use pre-heating during the warmer summer month. These results can help to design residential energy optimization systems.

A Comfort-Based Approach to Smart Heating and Air Conditioning

In this article, we address the interrelated challenges of predicting user comfort and using this to reduce energy consumption in smart heating, ventilation, and air conditioning (HVAC) systems. At present, such systems use simple models of user comfort when deciding on a set-point temperature. Being built using broad population statistics, these models generally fail to represent individual users’ preferences, resulting in poor estimates of the users’ preferred temperatures. To address this issue, we propose the Bayesian Comfort Model (BCM). This personalised thermal comfort model uses a Bayesian network to learn from a user’s feedback, allowing it to adapt to the users’ individual preferences over time. We further propose an alternative to the ASHRAE 7-point scale used to assess user comfort. Using this model, we create an optimal HVAC control algorithm that minimizes energy consumption while preserving user comfort. Through an empirical evaluation based on the ASHRAE RP-884 dataset and data collected in a separate deployment by us, we show that our model is consistently 13.2% to 25.8% more accurate than current models and how using our alternative comfort scale can increase our model’s accuracy. Through simulations we show that using this model, our HVAC control algorithm can reduce energy consumption by 7.3% to 13.5% while decreasing user discomfort by 24.8% simultaneously.

Exploring zero-training algorithms for occupancy detection based on smart meter measurements

Detecting the occupancy in households is becoming increasingly important for enabling context-aware applications in smart homes. For example, smart heating systems, which aim at optimising the heating energy, often use the occupancy to determine when to heat the home. The occupancy schedule of a household can be inferred from the electricity consumption, as its changes indicate the presence or absence of inhabitants. As smart meters become more widespread, the real-time electricity consumption of households is often available in digital form. For such data, supervised classifiers are typically employed as occupancy detection mechanisms. However, these have to be trained on data labelled with the occupancy ground truth. Labelling occupancy data requires a high effort, sometimes it even may be impossible, making it difficult to apply these methods in real-world settings. Alternatively, one could use unsupervised classifiers, which do not require any labelled data for training. In this work, we introduce and explain several unsupervised occupancy detection algorithms. We evaluate these algorithms by applying them to three publicly available datasets with ground truth occupancy data, and compare them to one existing unsupervised classifier and several supervised classifiers. Two unsupervised algorithms perform the best and we find that the unsupervised classifiers outperform the supervised ones we compared to. Interestingly, we achieve a similar classification performance on coarse-grained aggregated datasets and their fine-grained counterparts.

Opportunity Cost Quantification for Ancillary Services Provided by Heating, Ventilating, and Air-Conditioning Systems

In ancillary service electricity markets, opportunity costs account for the profit forgone by a generator due to the use of generating capacity for ancillary service provision instead of energy sales. They are calculated for each generator providing ancillary services and are included in the determination of market-clearing prices by market operators throughout the U.S. Recent interest in the use of smart heating, ventilating, and air-conditioning systems for ancillary service provision prompts an investigation into their associated opportunity costs. This paper proposes a definition for these costs and method of accounting for them through time. This is done by recognizing the impacts intra-hour consumption modification associated with ancillary service provision have on daily energy efficiency and costs. A numeric example is presented to demonstrate the method. It is found that marginal ancillary service opportunity costs vary over time and that properly adjusting energy consumption at an hour of interest can reduce the total opportunity cost of providing ancillary services.

A novel intelligent control of HVAC system in smart microgrid

Heating systems have played an important role in building energy and comfort management. This paper set forth a novel intelligent residential heating system controller that has smart grid functionality. In smart grid, demand response systems now have the ability to not only engage commercial and industrial customers, but also the individual residential customers. Additionally, the ability exists to have automated control systems which operate on an availability of renewable energy and welfare of customers. In this paper one possible implementation of an active controller will be examined. An active controller operates by responding to a combination of internal set points and external signal from local control entity. The optimization objective of the heating systems management was to minimize the cost of smart microgrid, minimize the size of smart microgrid units, minimize import energy from distribution grid and maximize reliability of smart microgrid. This means that, smart heating system and renewable energy can work well together and their individual benefits can be added together when used in combination. Simulation studies are used to demonstrate the capability on the proposed heating system controller on the planning of a smart microgrid system.