Comparative Analysis of Thermal Unit Control Methods for Sustainable Housing Applications

This study aims to develop different control strategies for application to nonlinear model of a thermal unit and compare their performances as an advanced thermal control methods for HVAC applications of sustainable buildings. The mathematical description of thermal unit was obtained exploiting a data-driven and physically meaningful nonlinear continuous-time model, which represents a test-bed used in passive air conditioning for sustainable housing applications. The presented controller strategies use both inside temperature and air flow control in the thermal unit. The proposed control schemes were assessed with extensive simulations and Monte-Carlo analysis in the presence of modelling and measurement errors. The contribution of this work consists of providing an application example of the design and testing through simulations, of a data-driven thermal unit control. Furthermore, this study provides an insight into different control strategies in air conditioning systems and helps the practitioners and HVAC learners to design proper controller solutions

FEASIBILITY OF NEARLY-ZERO ENERGY BUILDING RETROFITS BY USING RENEWABLE ENERGY SOURCES IN AN EDUCATIONAL BUILDING

Dissemination of education is vital especially in developing countries like Turkey. Besides, proper use of energy resources is required while dissemination of education is ensured. Considering the regions where energy is limited, renewable energy sources should be used to achieve the goal of a zero-energy building. Moreover, an increase of smart technologies has potantial in order to decrease energy consumption in educational buildings. This paper aims to investigate renewable energy sources to decrease energy consumption to achieve nearly-zero energy building goal by implementing different energy efficient retrofitting scenarios. The retroffitting scenarios are based on renewable energy sources and are presented for an educational building located in Ankara-Turkey, through a Building Energy Simulation Tool, Design Builder Software. In order to develop an accurate model, educational building is monitored and the model is calibrated. Then, various energy efficient retrofitting scenarios are defined such as implementing PV panels, solar collectors and adding wind turbines for electricity generation

Performance Analysis of Data-Driven and Model-Based Control Strategies Applied to a Thermal Unit Model

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data-driven grey-box identification approach provided the physically–meaningful nonlinear continuous-time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important, since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte Carlo (MC) analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application of the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model-based and data-driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems

Kişiselleştirilmiş enerji etkin ısıl konfor bazlı HVAC kontrol sistemlerinin geliştirilmesi

Thesis (Doctoral)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2018Includes bibliographical references (leaves. 97-111)Text in English; Abstract: Turkish and EnglishIncreasing thermal comfort and reducing energy consumption are two main objectives of advanced HVAC control systems. Studies conducted in the last decade show that intelligent HVAC systems can geatly affect thermal comfort, health, satisfaction, and productivity of building occupants while decreasing the energey consumption. Also, personelized thermal comfort driven control of the HVAC systems is the most effective way of saving energy and maintaining thermal comfort. In this thesis, an energy-efficient personalized thermal comfort control algorithm is developed to improve HVAC control systems. The thesis presents a complete system to control algorithm which includes the deployment of wireless sensor network. First a novel control algorithm is developed to perceived comfort conditions of occupants and to save energy. Then, a prototype of the personalized thermal comfort driven controller (PTC-DC) is manufactured an tested in a case building at İzmir Institute of Technology Campus, İzmir/Turkey. The proposed control strategy is tested betwen July 3rd, 2017 and November 1st, 2018, and compared with conventional controller in terms of energey saving and boath energetic and exergetic approaches of thermal comfort. The results showed that PTC-DC satisfies neutral thermal comfort for 92% of total measurements days while AM=0 for only 6% of total measurement days for conventional controller. From energy consumption point of wiev, PTC-DC decreased energy consumption by 13.2% compared to conventional controller

VISUAL AND TEXTUAL FEATURE FUSION FOR AUTOMATIC CUSTOMS TARIFF CLASSIFICATION

The Harmonized Tariff Schedule for the classification of goods is a major determinant of customs duties and taxes. The basic HS Code is 6 digits long but can be extended according to the needs of the countries such as application of custom duties based on details of the product. Finding the correct, consistent, legally defensible HS Code is at the heart of Import Compliance. However finding the best code can be complicated, especially in the case of specialized products. In this paper, we propose an automatic HS code detection system based on visual properties of the product together with textual analysis of its labels/explanations. The proposed system first uses morphological parsing in order to extract roots of the words occurring in the textual phrases. Processed text information is further processed by the topic modeling module of the system to find the best matching HS Code definitions within the system. The result of the topic modeling is used to trigger visual search based on quantized local features. The proposed algorithm is evaluated using a database of 4494 Binding Tariffs published in 2014 by the European Union. The results show that accuracy rate above 80 % can be achieved for 4-digit HS Codes

Assessment of thermal comfort preferences in mediterranean climate: A university office building case

12th International Scientific Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES); OCT 04-08, 2017 -- Dubrovnik, CroatiaThis study aims at evaluating the perceived thermal sensation of occupants with respect to thermal comfort standards, ASHRAE 55 and ISO 7730, for office buildings located in Mediterranean climate. A small office building in Izmir Institute of Technology Campus Area, Izmir, Turkey, was chosen as a case building and equipped with measurement devices to assess thermal comfort of occupants with respect to predicted mean vote and actual mean vote. Both objective and subjective measurements were conducted. The former included indoor and outdoor air temperature, mean radiant temperature, relative humidity and air velocity that were used for evaluating the thermal comfort of occupants. Oxygen concentration which can play an additional role in thermal comfort/discomfort, health and productivity of the office occupants, was also measured. Furthermore, occupants were subjected to a survey via a mobile application to obtain subjective measurements to calculate actual mean vote values. Based on objective and subjective measurements, the relationships among the parameters were derived by using simple regression analysis technique while a new combined mean vote correlation was also derived but this time by using multiple linear regression model. Neutral and comfort temperatures were obtained using indoor air temperature and actual mean vote values which were calculated from subjective measurements. The results showed that neutral temperature in the university office building was 20.9 degrees C whilst the comfort temperature range was between 19.4 and 22.4 degrees C for the heating season. By applying new comfort temperatures, energy consumption of the case building located in Mediterranean climate, can be reduced

Fuzzy Modelling for Sustainable Control of Wind Park Systems

In order to improve the safety, the reliability, and the efficiency of offshore wind park installations, thus avoiding expensive unplanned maintenance, the accommodation of faults in their earlier occurrence is fundamental. Therefore, the main contribution of this paper consists of the development of a fault tolerant control scheme by means of a viable approach. In particular, a data-driven strategy based on fuzzy logic is exploited for deriving the model of the required controller. Fuzzy theory is exploited here since it is able to approximate easily unknown nonlinear models and manage noisy measurements. Moreover, the controller fuzzy prototype is directly identified from the wind farm measurements, and it provides the straightforward achievement of the fault tolerant control scheme. In general, an analytic approach, where the system nonlinearity is explicitly taken into account, could require more complex design methodologies. This aspect of the work, followed by the simpler solution relying on fuzzy rules, represents the key point when on-line implementations are considered of the proposed control scheme. To highlight the potential of the proposed fault tolerant control algorithm in realistic applications, a high--fidelity simulator representing a real offshore wind farm installation is considered to analyse the realibility and robustness features of the designed solutions. The results have shown that the developed scheme maintains desired performances, thus validating its reliability also in real--time implementations

Investigation of the Relationship between Tension Level and Thermal Sensation. A Case Study of University Study Hall

The adaptive thermal comfort model steps forth against Fanger's Predicted Mean Vote/ Percentage of Dissatisfied model because of considering the psychological and behavioural adjustments in addition to environmental and personal parameters in mixed-mode and non-air-conditioned buildings. Among behavioural and psychological adjustments, human behaviour is more investigated than psychological adjustments in aspects of thermal sensation and comfort in the studies. To meet the deficit in the literature on how psychological adjustments affect thermal sensation, an experimental investigation was conducted to explore the effects of tension level on the Thermal Sensation Votes (TSV) of the students. Profile of Mood States (POMS) questionnaire was used to determine the tension level of the students. Experiments were conducted in a university study hall which is in the warm-summer Mediterranean climate (Csb) zone according to Köppen-Geiger Climate Classification. A total of 1159 students participated in the study, and the relation between the tension level and TSVs of the students were investigated for each gender. To test the associations between the nine quantitative subscales of tension level and the TSV, Pearson’s correlation coefficient was computed. Based on results, “anxious” were considerable for the TSVs of both genders where the p-values were <0,001 for male and 0,044 for female students. In addition, while “shaky” (p=0,001) and “uneasy” (p<0,001) were found significant for the TSVs of male, “nervous” (p=0,013) were discovered noteworthy for the TSVs of the female students

Performance indices of soft computing models to predict the heat load of buildings in terms of architectural indicators

This study estimates the heat load of buildings in Izmir/Turkey by three soft computing (SC) methods; Artificial Neural Networks (ANNs), Fuzzy Logic (FL) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) and compares their prediction indices. Obtaining knowledge about what the heat load of buildings would be in architectural design stage is necessary to forecast the building performance and take precautions against any possible failure. The best accuracy and prediction power of novel soft computing techniques would assist the practical way of this process. For this purpose, four inputs, namely, wall overall heat transfer coefficient, building area/ volume ratio, total external surface area and total window area/total external surface area ratio were employed in each model of this study. The predicted heat load is evaluated comparatively using simulation outputs. The ANN model estimated the heat load of the case apartments with a rate of 97.7% and the MAPE of 5.06%; while these ratios are 98.6% and 3.56% in Mamdani fuzzy inference systems (FL); 99.0% and 2.43% in ANFIS. When these values were compared, it was found that the ANFIS model has become the best learning technique among the others and can be applicable in building energy performance studies.Scientific and Technological Research Council of Turkey (TUBITAK -- 109M450)