Yazar "Kilic, Heybet" seçeneğine göre listele

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    Active Fault Tolerant Control of Grid-Connected DER: Diagnosis and Reconfiguration
    (Ieee, 2019) Khaki, Behnam; Kilic, Heybet; Yilmaz, Musa; Shafie-khah, Miadreza; Lotfi, Mohamed; Catalao, Joao P. S.
    In this paper, we propose an active fault tolerant control (FTC) to regulate the active and reactive output powers of a voltage source converter (VSC) in the case of actuator failure. The active fault tolerant controller of the VSC which connects a distributed energy resource to the distribution power grid is achieved through the fault diagnostic and controller reconfiguration units. The diagnostic unit reveals the actuator failure by comparing the known inputs and measured outputs of VSC with those of the faultless model of the system and testing their consistency. In the case of actuator failure, the reconfiguration unit adapts the controller to the faulty system which enables the VSC to track the desired active and reactive output powers. The reconfiguration unit is designed using the virtual actuator which does not interfere with the regular controller of the VSC. The effectiveness of the proposed active FTC is evaluated by the numerical simulation of a VSC connected to the AC distribution grid.
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    Case studies from selected countries - the USA
    (Inst Engineering Tech-Iet, 2018) Yilmaz, Musa; Kilic, Heybet
    [Abstract Not Available]
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    Chaotic Analysis of the Gloabal Solar Irradiance
    (Ieee, 2017) Ytlmaz, Musa; Gumus, Bilal; Kilic, Heybet; Asker, M. Emin
    The use of solar energy is increasing for power generation and other uses. In order to meet these demands and make better predictions, it is necessary to understand and explain the dynamics of the solar parameters. Nonlinear dynamics and associated tools can provide better results in the analysis. The meteorological events are based time series and has a dynamic chacteristic therefore this paper proposes a different approach to analysis of solar parameter that is called chaotic analysis of the solar parameters such as global solar irradiance(GSI) based on times series approach. The chaotic behavior of global solar irradiation and sunshine duration are tested by phase spaces and Lyapunov Exponents. It is crucial to measure and analysis with a high accuracy solar parameters to benefit maximally form a specific region solar energy potential. In the application, four solar irradiation sites are considered from different solar energy potential locations in Turkey, namely, at Diyarbakir, Gaziantep, Batman and Mardin cities.
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    DC-link voltage stability enhancement in intermittent microgrids using coordinated reserve energy management strategy
    (2025) Imtiaz, Saqif; Yang, Lijun; Munir, Hafiz Mudassir; Memon, Zulfiqar Ali; Kilic, Heybet; Naz, Muhammad Naveed
    In recent years, due to its cost effectiveness and environmental advantages, demand for renewable energy resources has grown and their contributions to grid power has therefore increased while requiring effective frequency and voltage regulation. DC link voltage instability is a potential problem in solar energy microgrids, especially during an intermittency, where the system reliability degrades and DC link capacitor is under higher stress. In this article, a novel reserve energy management scheme based on battery and super capacitor storage is presented to stabilize the DC link voltage and reduce capacitor stress, while enhancing the system reliability. The scheme is tested in four different scenarios: Inverter connected DC-microgrid with irradiance intermittencies, standalone DC-microgrid without inverter and irradiance intermittencies, standalone DC-microgrid without inverter and load intermittencies, and standalone DC-microgrid with inverter under irradiance intermittencies. Simulation results indicate that the proposed control strategy stabilizes DC link voltage over all scenarios, even subject to large instances of irradiance or load changes. During low solar irradiance, the battery and super-capacitor promote voltage stability by compensating power deficits from the utility grid in the inverter connected grid case. In stand alone mode, the battery provides power during intermittencies and the supercapacitor provides fast transient voltage compensation. The strategy is notable in reducing stress on DClink capacitors and mitigating inverter voltage fluctuations, ultimately enhancing inverter longevity. The results show that the proposed control scheme can improve voltage stability, mitigate the transient effects and guarantee the reliable operation of solar microgrids in variable conditions.
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    Fault detection in photovoltaic arrays: a robust regularized machine learning approach
    (Federacion Asociaciones Ingenieros Industriales Espana, 2020) Kilic, Heybet; Gumus, Bilal; Yilmaz, Musa
    In this paper, a robust data-driven method for fault detection in photovoltaic (PV) arrays is proposed. Our method is based on the random vector functional link networks (RVFLN) which has the advantage of randomly assigning hidden layer parameters with no tuning. To eliminate the effect of measurement noise and overfitting in the training process which reduce the fault detection accuracy, the sparse-regularization method is utilized which uses l2-norm with loss weighting factor to compute the output weights. To attain strong robustness against the outlier samples, the non-parametric kernel density estimation is employed to assign a loss weighting factor. Through rigorous simulation and experimental studies, we validate the performance of our proposed method in detecting the short and open circuit faults based on only the output current and voltage measurements of PV arrays. In addition to stronger robustness comparing with the least square-support vector machine, we also show that our proposed method provides 80% and 100% average detection accuracy for short circuit and open circuit, respectively.
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    Fault ride-through capability improvement in hydrogen energy-based distributed generators using STATCOM and deep-Q learning
    (Elsevier Ltd, 2024) Shahzad, Sulman; Alsenani, Theyab R.; Alrumayh, Ahmed Nasser; Almutairi, Abdulaziz; Kilic, Heybet
    This study explores the enhancement of Fault Ride-Through (FRT) capabilities in hydrogen energy-based distributed generators (HEDGs) by integrating Static Synchronous Compensators (STATCOM) with a novel Deep Q-Learning (DQL) control technique. Hydrogen energy systems face challenges like voltage instability during grid disturbances, which conventional Proportional-Integral (PI) controllers fail to address due to their linear operation constraints. Advanced controllers, such as Adaptive Neuro-Fuzzy Inference Systems (ANFIS), offer better adaptability but lack real-time optimization capabilities. The proposed DQL framework leverages reinforcement learning, achieving superior results by dynamically optimizing reactive power compensation and minimizing system instability. Simulation results demonstrate that the DQL-based STATCOM achieves a 35% faster settling time and reduces overshoot by 50% compared to ANFIS and PI controllers. Additionally, the DQL system maintains voltage stability within ±5% during critical faults, improving energy efficiency by 8%. This innovative approach ensures cost-effective, sustainable integration of HEDGs into modern power grids, significantly advancing intelligent control strategies for renewable energy systems. © 2024 Hydrogen Energy Publications LLC
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    Harnessing nuclear power for sustainable electricity generation and achieving zero emissions
    (Sage Publications Inc, 2025) Khaleel, Mohamed; Yusupov, Ziyodulla; Rekik, Sassi; Kilic, Heybet; Nassar, Yasser F.; El-Khozondar, Hala J.; Ahmed, Abdussalam Ali
    Nuclear power plays a pivotal role in sustainable electricity generation and global net zero emissions, contributing significantly to this secure pathway. Nuclear power capacity is expected to double, escalating from 413 gigawatts (GW) in early 2022 to 812 GW by 2050 within the net zero emissions (NZE) paradigm. The global energy landscape is undergoing significant transformation as nations strive to transition to more sustainable energy systems. Amidst this shift, nuclear power has emerged as a crucial component in the pursuit of a sustainable energy transition. This study examines nuclear power's multifaceted role in shaping sustainable energy transition. It delves into nuclear energy's contributions toward decarbonization efforts, highlighting its capacity to provide low-carbon electricity and its potential role in mitigating climate change. Furthermore, the study explores the challenges and opportunities associated with integrating nuclear power into energy transition strategies, addressing issues such as safety, waste management, and public perception. In conclusion, the global nuclear power capacity is anticipated to reach approximately 530 GW by 2050, representing a substantial shortfall of 35% compared with the trajectory outlined in the NZE pathway. Under the NZE scenario, nuclear power demonstrates exceptional expansion, nearly doubling from 413 GW in early 2022 to 812 GW by 2050. Concurrently, the trajectory highlights a transformative shift in renewable energy investments, with annual expenditures surging from an average of US$325 billion during 2016-2020 to an impressive US$1.3 trillion between 2031 and 2035. These projections underscore the critical role of nuclear and renewable energy investments in achieving global sustainability and emission reduction goals.
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    Stability Analysis of Islanded Microgrid with EVs
    (Ieee, 2018) Kilic, Heybet; Khaki, Behnam; Gumus, Bilal; Yilmaz, Musa; Asker, M. Emin
    Renewable energy resources (RESs) and electric vehicles (EVs) have emerged as powerful concepts which can replace the conventional energy and transportation systems with more flexibility and efficiency. Due to low inertia of microgrid and intermittent nature of RESs, the rapid increase in the penetration level of RESs and EVs in smart grids may lead to frequency stability issue. However, EVs, as the mobile energy storage system, can contribute to the improvement of the frequency fluctuation and stability. This paper proposes a method to control the EVs integrated in an islanded microgrid so that they participate in load frequency control (LFC). On the contrary to the approaches proposed in the literature, the proposed control method enables the investigation of time delay effect on LFC and considers the communication latency on the LFC stability. The delay-dependent stability criterion of the proposed method is derived based on Lyapunov theory in the form of linear matrix inequality (LMI). The LMI is solved to find the parameters impacting the maximum allowable delay (MAD) and to obtain the MAD by which the stability of the LFC system is guaranteed. The effectiveness of the proposed method is validated through numerical simulation of a case study.
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    Techno-economic analysis of green hydrogen integration in smart grids: Pathways to sustainable energy systems
    (Elsevier Ltd, 2024) Shahzad, Sulman; Alsenani, Theyab R.; Kilic, Heybet; Wheeler, Patrick
    This study conducts a comprehensive techno-economic analysis of green hydrogen integration in smart grids, highlighting its potential to transform energy systems. Green hydrogen, produced via water electrolysis using renewable sources like wind and solar, offers a carbon-neutral alternative to traditional hydrogen production. The paper evaluates electrolysis technologies' efficiency and cost dynamics, including PEM and alkaline systems, and integrates advanced smart grid technologies for real-time monitoring and energy management. Our findings reveal that while green hydrogen reduces carbon emissions and enhances grid flexibility, challenges remain in terms of infrastructure and cost reductions. Policy support through incentives, such as feed-in tariffs for green hydrogen production, and regulatory frameworks, like emission reduction targets, will be crucial to scale the adoption of green hydrogen and make it a viable component of future sustainable energy strategies. © 2024 Hydrogen Energy Publications LLC
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    A unified robust hybrid optimized Takagi–Sugeno fuzzy control for hydrogen fuel cell-integrated microgrids
    (Elsevier Ltd, 2025) Ozcan, Omer Faruk; Kilic, Heybet; Ozguven, Omerul Faruk
    Microgrids integrating renewable energy sources, hydrogen fuel cells, battery-based energy storage systems (ESS), and various loads have become essential for the seamless incorporation of distributed energy into the grid. Hydrogen fuel cells, in particular, are crucial for providing reliable, clean electricity, especially during periods of reduced renewable energy availability. This paper presents a unified control solution for converters and inverters, utilizing a hybrid optimized Takagi–Sugeno–Kang (TSK) fuzzy-based approach to manage ESS operation, with a strong focus on hydrogen fuel cells. The strategy dynamically controls the power generated or stored in the ESS, prioritizing hydrogen fuel cells based on grid demand, available renewable power, and the battery's state of charge (SOC). This method reduces active power exchange at the point of common coupling during grid-connected mode and supports frequency regulation during island mode operations, thereby improving system stability and efficiency. To enhance Fuzzy System (FS) design, a hybrid genetic algorithm (GA) and grey wolf optimizer (GWO) approach is applied, accelerating rule generation and optimizing system performance. Simulation results demonstrated that the proposed hybrid GGWO-TSK control strategy achieved 97.58% PV and 98.56% wind tracking efficiency, while optimizing hydrogen fuel cell utilization to maintain a 98.88% fuel cell tracking efficiency. This method effectively minimized power exchange, improved frequency regulation, and enhanced microgrid stability, ensuring efficient energy management in both grid-connected and islanded modes. The proposed framework proves to be a robust and scalable solution for hydrogen fuel cell-integrated microgrids, contributing to a more resilient and sustainable energy system under diverse operating scenarios. © 2025 Hydrogen Energy Publications LLC
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    Voltage and Frequency Control of a PV-Battery-Diesel Generator based Standalone Hybrid System
    (Ieee, 2022) Lakshmi, M. Bhagya; Saravanan, S.; Duzdag, Muhammet Serhat; Kilic, Heybet; Anuradha, T.; Deepak, Karanam; Malla, Jagan Mohana Rao
    An effective controller is proposed for the Photovoltaic(PV) - Battery - Diesel Generator(DG) based hybrid standalone system in this article. A bidirectional DC to DC device which can allow power in both directions is integrated among the DC-link and battery bank to maintain contact voltage by maintaining power balance in the system. Further, a bidirectional inverter is also considered between point of common coupling (PCC) and DC-link for providing supply to AC loads as well as charging the battery from diesel generator based on requirement. However, the phenomenon of partial shading condition (PSC) commonly occurring on PV modules and also generated power from PV always fluctuates according to changes in weather. To achieve a superior performance of the system, a Takagi-Sugeno Fuzzy (TSF) based controllers are implemented in proposed control schemes. The novel control schemes are implemented on a bidirectional DC to DC converter as well as three phase bidirectional inverter. However, the proper deloading process of the PV system should be incorporated into the controller of the DC to DC converter to achieve power balance during light load conditions. Balanced quality voltages (3-phase) at PCC are achieved by inverter control which forces to maintain balanced currents generated by DG during the operation of unbalanced loads. Maintaining balanced DG currents can help to reduce the oscillations on the torque of the shaft which increases the fatigue life. Further the reactive power demanded at PCC is compensated by the inverter control, hence DG need not to provide it which results can reduce the consumption of diesel. Various case studies are examined by using MATLAB to present results and Real Time Digital Simulator (RTDS) based results are also provided in this paper.