Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 33Citation - Scopus: 41Development of a Personalized Thermal Comfort Driven Controller for Hvac Systems(Elsevier Ltd., 2021) Turhan, Cihan; Simani, Silvio; Gökçen Akkurt, GüldenIncreasing thermal comfort and reducing energy consumption are two main objectives of advanced HVAC control systems. In this study, a thermal comfort driven control (PTC-DC) algorithm was developed to improve HVAC control systems with no need of retrofitting HVAC system components. A case building located in Izmir Institute of Technology Campus-Izmir-Turkey was selected to test the developed system. First, wireless sensors were installed to the building and a mobile application was developed to monitor/collect temperature, relative humidity and thermal comfort data of an occupant. Then, the PTC-DC algorithm was developed to meet the highest occupant thermal comfort as well as saving energy. The prototypes of the controller were tested on the case building from July 3rd, 2017 to November 1st, 2018 and compared with a conventional PID controller. The results showed that the developed control algorithm and conventional controller satisfy neutral thermal comfort for 92 % and 6 % of total measurement days, respectively. From energy consumption point of view, the PTC-DC decreased energy consumption by 13.2 % compared to the conventional controller. Consequently, the PTC-DC differs from other works in the literature that the prototype of PTC-DC can be easily deployed in real environments. Moreover, the PTC-DC is low-cost and user-friendly.Article Citation - WoS: 12Citation - Scopus: 13Assessment of Thermal Comfort Preferences in Mediterranean Climate a University Office Building Case(Vinca Inst Nuclear Sci, 2018) Turhan, Cihan; Gökçen Akkurt, GüldenThis 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.Conference Object Citation - WoS: 1Citation - Scopus: 3Green Smart Cities: Living Healthily With Every Breath(Institute of Electrical and Electronics Engineers Inc., 2019) Turhan, Cihan; Atalay, Ali Serdar; Gökçen Akkurt, GüldenFifty-four percent of the world's population lives in big cities and it is projected to increase to nearly 70% by 2050s. Rapid and dense urbanization leads to smart cities which improve the quality of lives of the citizens. Therefore, development of smart cities is becoming vital. The quality of the citizens is affected by many factors including poor air quality, increased pollutants and microclimates called urban heat islands. The URBAN GreenUP project, initiated in June 2017, is a project funded under the European Union's Horizon 2020 programme. The main objective of the project is the development, application and replication of re-naturing Urban Plans in a number of European cities. In this study, measurement of nature-based solutions for mitigation of urban heat island effect and improvement of air quality for Urban GreenUP project in Izmir, will be introduced.Article Citation - WoS: 6Citation - Scopus: 9Impact of Climate Change on Indoor Environment of Historic Libraries in Mediterranean Climate Zone(Inderscience Enterprises, 2019) Turhan, Cihan; Durmuş Arsan, Zeynep; Gökçen Akkurt, GüldenMost historic library buildings house valuable paper-based collections that are kept in unconditioned environments. This vulnerable cultural heritage is expected to be highly affected by climate change in the future. In this study, indoor microclimate of an unconditioned historic library, Necip Pasa Library (Izmir, Turkey) is analysed for existing conditions and future climate data. The measured and predicted indoor microclimate data from 'present' till 2080s are used to determine possible chemical degredation risk on library collection and human comfort. Comparison of periodic results of future climate data indicates an increase in temperature that could cause both an increase in chemical degredation risk on the library collection and a decline in thermal comfort conditions. Mitigation of climate change effects on library collection and human comfort requires taking some actions such as adding light and adaptive mechanical solutions.Article Citation - WoS: 15Citation - Scopus: 11The Relation Between Thermal Comfort and Human-Body Exergy Consumption in a Temperate Climate Zone(Elsevier, 2019) Turhan, Cihan; Gökçen Akkurt, GüldenHuman body exergy balance calculation method gives minimum human body exergy consumption rates at thermal neutrality (TSV = 0) providing more information on human thermal responses than other methods. The literature is lacking the verification of this method in various climatic zones. The aim of this study is to investigate the relationship between thermal comfort and human body exergy consumption in a temperate climate zone. A small office building in Izmir Institute of Technology campus, Izmir/Turkey, was chosen as a case building and equipped with measurement devices. The occupant was subjected to a survey via a mobile application to obtain his Thermal Sensation Votes. Objective data were collected via sensors and used for predicting occupant thermal comfort and for exergy balance calculations. Under given conditions, the results show that Thermal Sensation Votes are generally zero at a T-i range of 21-23 degrees C and, are mostly lower than Predicted Mean Votes in summer while the opposite is observed in winter. Predicted Mean Votes at minimum Human Body Exergy Consumption rates were on slightly warm side while Thermal Sensation Votes are zero. It means that for given case, the HBexC rate calculation gave a better prediction of the environmental parameters for the best thermal comfort. (C) 2019 Elsevier B.V. All rights reserved.Article Citation - WoS: 4Citation - Scopus: 8Fault Diagnosis of a Wind Turbine Simulated Model Via Neural Networks(IFAC Secretariat, 2018) Simani, Silvio; Turhan, CihanThe fault diagnosis of wind turbine systems has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of wind turbines, and it proposes viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves a data-driven approach, as it represents an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the data-driven proposed solution relies on neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the nonlinear autoregressive with exogenous input topology, as it can represent a dynamic evolution of the system along time. The developed fault diagnosis scheme is tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed solutions against the typical parameter uncertainties and disturbances.Article Active Fault Tolerant Control of a Wind Farm System(IFAC Secretariat, 2018) Simani, Silvio; Turhan, CihanIn order to enhance the 'sustainability’ of offshore wind farms, thus skipping unplanned maintenance operations and costs, that can be important for offshore systems, the earlier management of faults represents the key point. Therefore, this work studies the development of an adaptive sustainable control scheme with application to a wind farm benchmark consisting of nine wind turbine systems. They are described via their nonlinear models, as well as the wind and wake effects among the wind turbines of the wind park. The fault tolerant control strategy uses the recursive estimation of the faults provided by nonlinear estimators designed via a nonlinear differential algebraic tool. This aspect of the study, together with the more straightforward solution based on a data-driven scheme, is the key issue when on-line applications are proposed for a viable implementation of the proposed solutions.Conference Object Citation - WoS: 1Citation - Scopus: 1Adaptive Signal Processing Strategy for a Wind Farm System Fault Accommodation(Institute of Electrical and Electronics Engineers, 2018) Simani, Silvio; Turhan, CihanIn order to enhance the 'sustainability' of offshore wind farms, thus skipping unplanned maintenance operations and costs, that can be important for offshore systems, the earlier management of faults represents the key point. Therefore, this work studies the development of an adaptive sustainable control scheme with application to a wind farm benchmark consisting of nine wind turbine systems. They are described via their nonlinear models, as well as the wind and wake effects among the wind turbines of the wind park. The fault tolerant (i.e., sustainable) control strategy uses the recursive estimation of the faults provided by nonlinear estimators designed via a nonlinear differential algebraic tool. These estimators are not affected by the model uncertainty and the wake effects among the wind turbines. This work exploits also a data-driven method used for estimating the analytical form of these disturbance functions, which are employed for obtaining the nonlinear fault reconstructors. Note that purely analytic approaches, where the model nonlinearity and the disturbance decoupling features are directly taken into account, may lead to more complex design tools. This aspect of the study, together with the more straightforward solution based on a data-driven scheme, is the issue when online applications are proposed for a viable implementation of the proposed solutions. The benchmark is exploited to verify the features of the developed strategies with respect to various fault situations and unavoidable model-reality mismatch.Article Citation - WoS: 7Citation - Scopus: 8Performance Indices of Soft Computing Models To Predict the Heat Load of Buildings in Terms of Architectural Indicators(Yıldız Teknik Üniversitesi, 2017) Turhan, Cihan; Kazanasmaz, Zehra Tuğçe; Gökçen Akkurt, GüldenThis 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.Article Citation - WoS: 7Citation - Scopus: 7The Importance of Internal Heat Gains for Building Cooling Design(Yıldız Teknik Üniversitesi, 2017) Coşkun, Turgay; Turhan, Cihan; Durmuş Arsan, Zeynep; Gökçen Akkurt, GüldenThis paper aims to investigate the effect of internal heat gains on the cooling load of a building. The house occupied by three adult men is selected as the case study for paper. The house is in the third floor of the apartment. The apartment has four flats and it has no insulation around the external walls. The heat dissipation from lighting devices, electrical equipment and the occupants are calculated by using the DesignBuilder v4 Beta release simulation program. The temperature of the house is observed during three weeks by using hobo data loggers and calibration of the measurements is made with respect to weather data file of the flat. Detailed schedule based on time of operation and occupancy is prepared to get more accurate results. Annual energy consumption and cooling load of the house is determined by using the dynamic simulation program.