Cellular network based Machine-to-Machine (M2M) communications have been growing rapidly in recent years, being used in a wide range of services such as security, metering, health, remote control, tracking and so on. A critical issue that needs to be considered in M2M communications is the energy efficiency, typically the machines are powered by batteries of low capacity and it is important to optimize the way the power is consumed. In search of better M2M systems, we propose a context-aware framework for M2M communications so the machine type communication (MTC) devices dynamically adapt their settings depending on a series of characteristics such as data reporting mode and quality of service (QoS) features so higher energy efficient is achieved, extending the operating lifetime of the M2M network. Simulations were performed with four commonly used M2M applications:home security, telehealth, climate and smart metering, achieving considerable energy savings and operating lifetime extension on the network. Thus, it is shown that contexts play an important role on the energy efficiency of a M2M system.

The thesis begins with a discussion of the concept of sustainability, green buildings and the traditional valuation approach. Then valuable information are extracted from the reports of IMMOVALUE project, which is aiming to improve the market impact of energy certification by introducing energy efficiency and life cycle cost into property valuation practice. A survey collecting Swedish valuers‟ opinion towards the sustainability issue is implemented and some results from early surveys are also employed for exploring this research area.Energy efficiency/Energy Performance Certificate (EPC) is a breakpoint for the integration of green issues into property valuation practice. This is the most feasible way to quantify the effects of green features into property. Some modified methodologies based on the three traditional valuation approaches are proposed and the income related approach is the most suitable one here. For a good market acceptance of green buildings, the valuation of green issues must be taken.At the very early stage of the process of integrating green features into property valuation, this thesis explores the result from IMMOVALUE project and other researches. A close review of the process has been made and this may give valuers guidance of how to take green features into account not only in a qualitative, but also in a quantitative way.

The reduction of energy demand and increased energy efficiency is believed to play a major role in tackling the global climate change. Artificial lighting systems in commercial buildings accounts for a substantial proportion of the total energy consumption. Studies shows that significant energy savings can be achieved by improving the energy efficiency with the application of control systems and daylight sensors. However, this may not come to the expense of impaired visual comfort. This study contains a comparative analysis of methods to improve the visual comfort, optimise light sensor placement for proper performance and estimate the potential energy savings for a classroom located in Umeå, Sweden. The term visual comfort and corresponding photometric properties has been evaluated in regards to international standards and recommendations. The lumen method, a lighting design technique, showed promising accuracy in determining a more optimal lighting design, this was confirmed by using the lighting simulation software Dialux evo. The results obtained by the simulation software showed improved visual comfort in terms of illuminance-based metrics that fulfilled the international requirements EN12464-1.  A sensor positioning method denoted as "Point-by-point" has been evaluated for two different lighting designs. The current lighting design is based on the existing lighting arrangement in the classroom, denoted as "current design". The other lighting design is based on improved positioning attained by the lumen method, denoted "Test design 2". The point-by-point method showed considerate accuracy in comparison to reference values obtained by simulations, however the credibility of the method is dependent on the lighting design. The average deviation for the current design were determined to be 23.7 lx (15.16 \%), whilst the improved Test design 2 attained an lower average deviation of 8.3 lx (9.20 \%). Lighting characteristics of the luminaries also has an impact on the credibility of this method, as uniform lighting proves to be more suitable than non-uniform lighting.  The integration of daylight data in the simulations showed different optimal position for light sensors due to the natural changes in illuminance. Thus, the positions with the most established linear relationships between the light levels on the workplane and ceiling throughout the year were consider to be the most suitable. The point-by-point method for Test design 2 acquired an average deviation of 13.1 lx (16.40 \%) in comparison to the daylight simulations. The results showcased that this method may be applied in similar studies in the future. The daylight simulations indicated significant energy savings throughout the lifetime of the lamp. The most substantial savings were obtained in the month of May during the first year (63.4 \%). This study demonstrates that daylight harvesting is beneficial despite the latitude of the location with proper dimensioning of the fluorescent lighting system.

<p>Current global efforts in building information research include the development of low-cost, high reliability sensing systems capable of quantifying metrics such as human occupancy, indoor environmental quality, and building system dynamics. Such information is of high value for model development, building energy management, and improving occupant comfort. Further, indoor air quality (IAQ) has been a growing concern in recent years, only to be exacerbated by the COVID-19 pandemic. A common provisional measure for IAQ is carbon dioxide (CO2), which is regularly used to inform the ventilation control of buildings. However, few commercially available sensors exist that can reliably measure CO2 while being low cost, exhibiting low power consumption, and being easily deployable for use in applications such as occupancy monitoring. </p> <p><br></p> <p>This work presents research related to the initial development and evaluation of low-cost, stable, and easily deployable sensors for monitoring indoor CO2 levels in buildings. Two different types of sensors are presented that have the potential to perform as well as current commercially available CO2 sensing technologies, at significantly lower costs. The first is a chemiresistive sensor that is fabricated using a carbon nanotube thin film in conjunction with a blend of branched poly(ethylenimine) (PEI) and poly(ethylene glycol) (PEG), which serve as a CO2 absorbing layer. The second is a resonant mass sensor, functionalized with similar polymer-based materials including a blend of PEI and poly(ethylene oxide) (PEO). Prototype sensors were assessed in a bench-top environmental test chamber which varied temperatures, relative humidity levels, CO2 concentrations, as well as other gas constituents to simulate typical and extreme indoor conditions. The results indicate that the proposed system could ultimately serve as an attractive alternative to commercial CO2 sensors that are currently available.</p>

Efficient use of resources and utility is the key to reduce the price of the commodities produced in any industry. This in turn would lead to reduced price of the commodity which is the key to success. Sustainability involves integration of all the three dimensions: environmental, economic and social. Sustainable manufacturing involves the use of sustainable processes and systems to produce better sustainable products. These products will be more attractive, and the industry will know more about the climate impact from their production. Manufacturing companies use a considerable amount of energy in their production processes. One important area to understand the sustainability level at these types of industries is to study this energy use. The present work studies energy use in a large-scale tool manufacturing company in Sweden. Value Stream Mapping method is implemented for the purpose of mapping the energy use in the different operations. To complement this, an energy audit has been conducted, which is a method that include a study and analysis of a facility, indicating possible areas of improvements by reducing energy use and saving energy costs. This presents an opportunity for the company to implement energy efficiency measures, thus generating positive impacts through budget savings. Less energy use is also good for the environment resulting in less greenhouse gas emissions level. This also helps in long-term strategic planning and initiatives to assess the required needs and stabilize energy use for the long run. Social sustainability completes the triad along with environmental and economic sustainability. In this study, the social sustainability is reflected with the company’s relationship with its working professionals by conducting a survey. The sustainable manufacturing potential found in the case study indicates that significant progress can be made in the three sustainability dimensions. Although, the scope of the thesis is limited to a tool manufacturing company, several of the findings could be implemented in other tool companies as well as industries belonging to other sectors. / <p>The thesis is a joint report between Linköping and Uppsala University. My thesis teammate has published it before at UU Diva Portal. The URL is: https://uu.diva-portal.org/smash/record.jsf?dswid=8179&amp;pid=diva2%3A1449223&amp;c=1&amp;searchType=SIMPLE&amp;language=en&amp;query=sustainable+manufacturing&amp;af=%5B%22dateIssued%3A2020%22%5D&amp;aq=%5B%5B%5D%5D&amp;aq2=%5B%5B%5D%5D&amp;aqe=%5B%5D&amp;noOfRows=50&amp;sortOrder=author_sort_asc&amp;sortOrder2=title_sort_asc&amp;onlyFullText=false&amp;sf=undergraduate</p><p> </p> / Green Factory project, AB Sandvik Coromant

Indiana University-Purdue University Indianapolis (IUPUI) / Air handling unit systems are the series of mechanical systems that regulate and circulate the air through the ducts inside the buildings. In a commercial setting, air handling units accounted for more than 50% of the total energy cost of the building in 2013. To make the system more energy efficient and reduce amount of CO₂ gases and energy waste, it is very important for building energy management systems to have an accurate model to help predict and optimize the energy usage and eliminate the energy waste. In this work, two models are described to focus on the energy usage for heating/cooling coils as well as fans for the air handling unit. Enthalpy based effectiveness and Dry Wet coil methods were identified and compared for the system performance. Two different types of control systems were modeled for this research, and the results are shown based on occupancy reflected by the collected CO₂ data. Discrete On/O and fuzzy logic controller techniques were simulated using Simulink MATLAB software and compared based on energy reduction and system performance. Air handling unit located in the basement of one campus building is used for the test case of this study. The data for model inputs is collected wirelessly from the building using fully function device (FFD) and pan coordinator to send/receive the data wirelessly. The air handling unit modeling also is done using Engineering Equation Solver EES Software for the coils and AHU subsystems. Current building management system Metasys software was used to get additional data as model inputs. Moving Average technique was utilized to make the model results more readable and less noisy. Simulation results show that in humid regions where there is more than 45% of relative humidity, the dry wet coil method is the effective way to provide more accurate details of the heat transfer and energy usage of the air handling unit comparing to the other method enthalpy-based effectiveness. Also, fuzzy logic controller results show that 62% of the current return fan energy can be reduced weekly using this method without sacrificing the occupant comfort level comparing to the ON/OFF method. Air quality can be optimized inside the building using fuzzy logic controller. At the same time, system performance can be increased by taking the appropriate steps to prevent the loss of static pressure in the ducts. The implementation of the method developed in this study will improve the energy efficiency of the AHU.

This master thesis work is aimed to investigate the possibilities of achieving more efficient industrial lighting. The study is divided in four parts: 1) Industrial lighting energy efficiency measures, 2) Added value of lighting, 3) Drivers and barriers for adopting lighting efficiency measures, and 4) Applications of AI in industrial lighting.The first part of the study explores various energy efficiency measures that could be applied in industrial lighting. The results show that using energy-efficient lighting fixtures, optimizing lighting controls, and adopting smart lighting solutions that integrate daylight in the illumination strategy and design are the most effective measures for reducing energy consumption and increasing efficiency.In the second part, the study examines the added values or non-energy benefitsof efficient industrial lighting. The findings indicate that apart from cost savings, efficient lighting leads to improvements on the quality of work environments, enhances workers health and safety conditions and improves environmental performance. Moreover, the study suggests that in many cases, the added values of lighting are not given the importance they should have and are not considered when an energy efficiency investment is planned to be done.The third part of the study identifies the drivers and barriers for adopting lighting efficiency measures in industrial settings. The study found that factors such as cost and energy savings, energy efficiency regulations are the main drivers for implementing efficient lighting solutions. However, barriers such as lack of awareness, perceived high initial costs, technology adoption and insufficient government incentives are the main obstacles to adoption.Finally, the study investigates the potential of artificial intelligence (AI) in industrial lighting. The results show that AI-based solutions, such as predictive maintenance and intelligent lighting control could significantly improve energy efficiency and reduce maintenance costs. Moreover, AI can bring the work environment to another level by the application of human centred and personalized lighting.Overall, this master thesis work provides valuable insights into achieving more efficient industrial lighting by highlighting effective energy efficiency measures, identifying the added value of efficient lighting, and examining the drivers and barriers to adoption. Moreover, the study sheds light on the potential of AI in industrial lighting and its potential benefits and future challenges.

Energy efficiency and renewable energy become more attractive in smart grid. In order to efficiently reduce global energy usage in building energy systems and to improve local environmental sustainability, it is essential to optimize the operation and the performance of combined heat and power (CHP) systems. In addition, intermittent renewable energy and imprecisely predicted customer loads have introduced great challenges in energy-efficient buildings' optimal operation. In the deterministic optimal operation, we study the modeling of components in energy-efficient building systems, including the power grid interface, CHP and boiler units, energy storage devices, and building appliances. The mixed energy resources are applied to collaboratively supply both electric and thermal loads. The results show that CHP can effectively improve overall energy efficiency by coordinating electric and thermal power supplies. Through the coordinated operation of all power sources, the daily operation cost of building energy system for generating energy can be significantly reduced. In order to address the risk from energy consumption forecast errors and renewable energy production volatility, we utilize the approach of stochastic programming and robust optimizations to operate energy-efficient building systems under uncertainty. The multi-stage stochastic programming model is introduced so that the reliable operation of building energy systems would be probabilistically guaranteed with stochastic decisions. The simulation results show that the stochastic operation of building energy systems is a promising strategy to account for the impact of the uncertainty on power dispatch decisions of energy-efficient building systems. In order to provide absolute guarantee for the reliable operation of building energy systems, a robust energy supply to electric and thermal loads is studied by exploring the effectiveness of energy storage on energy supply against the uncertainty. The robustness can be adjusted to control the conservativeness of the proposed robust operation model. For the purpose of achieving adaptability in the robust optimal operation and attaining robustness in the stochastic optimal operation of building energy systems, we also develop an innovative robust stochastic optimization (RSO) model. The proposed RSO model not only overcomes the conservativeness in the robust operation model, but also circumvents the curse of dimensionality in the stochastic operation model.

The increasing world energy demand has become the need of achieving energy efficiency and sustainable practices a key element in order to ensure the future of the societies. In Sweden, buildings accounts for 40% of total energy consumption. Within a sector that consumes almost half of the energy in the country it is possible to identify a group of buildings which generally presents a higher consumption and bigger problems, the historic and protected buildings. There is big room for improvement in the field of achieving sustainability in historic building although most of this improvements are constrained by limitations and protections due to their condition. Studying this limitations and needs for improvement of these buildings it is possible to come up with energy efficient solutions according with the regulations. The aim of this report will be achieving sustainability in Swedish historic/protected buildings, while respecting the applicable law to ensure that heritage and cultural value is respected, by proposing energy efficiency improvement measures that requires a feasible investment with a reasonable pay-back time.

Chilled water systems constitute a major portion of energy consumption in air conditioning systems of commercial buildings and process cooling of manufacturing plants. These systems do not operate optimally in most of the cases because of the operating parameters set and/or the components used. A Chilled water system analysis tool software (CWSAT) is developed as a primary screening tool for energy evaluation. This tool quantifies the energy usage of the various chilled water systems and typical measures that can be applied to these systems to conserve energy. The tool requires minimum number of inputs to analyze the component-wise energy consumption and incurred overall cost. This thesis also examines various energy conservation measures that are available for chilled water systems. The components, arrangements, and the common energy conservation opportunities for chilled water systems are presented. The new version of the tool is developed in Object Oriented Programming Language Microsoft Visual Basic.Net© to maintain the tool latest with current technology, add and expand capabilities and avoid obsolescence. Many Improvements to the previous tool are made to improve quality and the types of the systems the tool can handle. The development of the new routines and interfaces is also accommodated in the new version to make the tool universal. In order to determine the accuracy of the new version of the tool, a comparison is made between the results from the previous and new version of the tool. The results of the comparisons are presented.