Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Simani, SilvioInstitution Author: search.filters.institutionAuthor.Turhan, Cihan

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Now showing 1 - 6 of 6
  • Article
    Citation - WoS: 33
    Citation - Scopus: 41
    Development of a Personalized Thermal Comfort Driven Controller for Hvac Systems
    (Elsevier Ltd., 2021) Turhan, Cihan; Simani, Silvio; Gökçen Akkurt, Gülden
    Increasing 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: 4
    Citation - Scopus: 8
    Fault Diagnosis of a Wind Turbine Simulated Model Via Neural Networks
    (IFAC Secretariat, 2018) Simani, Silvio; Turhan, Cihan
    The 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, Cihan
    In 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: 1
    Citation - Scopus: 1
    Adaptive Signal Processing Strategy for a Wind Farm System Fault Accommodation
    (Institute of Electrical and Electronics Engineers, 2018) Simani, Silvio; Turhan, Cihan
    In 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.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    Analysis and Application of Advanced Control Strategies To a Heating Element Nonlinear Model
    (IOP Publishing Ltd., 2017) Turhan, Cihan; Simani, Silvio; Zajic, Ivan; Gökçen Akkurt, Gülden
    This paper presents the design of different control strategies applied to a heating element nonlinear model. The description of this heating element 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. This model has low complexity while achieving high simulation performance. The physical meaningfulness of the model provides an enhanced insight into the performance and functionality of the system. In return, this information can be used during the system simulation and improved model- based and data-driven control designs for tight temperature regulation. The main purpose of this study is thus to give several examples of viable and practical designs of control schemes with application to this heating element model. Moreover, extensive simulations and Monte- Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared in order to evaluate advantages and drawbacks of the considered solutions. Finally, the exploited simulation tools can serve to highlight the potential application of the proposed control strategies to real air conditioning systems.
  • Article
    Citation - WoS: 6
    Citation - Scopus: 9
    Performance Analysis of Data-Driven and Model-Based Control Strategies Applied To a Thermal Unit Model
    (MDPI Multidisciplinary Digital Publishing Institute, 2017) Turhan, Cihan; Simani, Silvio; Zajic, Ivan; Gökçen Akkurt, Gülden
    The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinearmodel 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.