Yazar "Basaran, Kivanc" seçeneğine göre listele

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    A new intelligent power quality disturbance classification in renewable and decentralized hydrogen-based energy systems using SwResNET hybrid model
    (Pergamon-Elsevier Science Ltd, 2025) Kucuker, Ahmet; Barakli, Burhan; Bayrak, Gokay; Basaran, Kivanc; Balaban, Georgiana
    In this study, a scalogram image-based Swin-Residual Network (SwResNET) hybrid method is proposed for the identification of power quality disturbances (PQDs) in a hydrogen energy-based distributed generator (HEBDGs). The proposed approach involves the creation of PQD scalogram images by applying spectrogram analysis to power signal data. This process generates a two-dimensional image that represents the frequency and time characteristics of the signal. These spectrogram images are then input into a SwResNET hybrid model for learning. The SwResNET hybrid model extracts features from the scalogram images and classifies the input signal based on the presence or absence of power quality disturbances. This paper used 21 different PQD events in HEBDGs for classification purposes. Furthermore, the proposed method was tested under noisy conditions. The data achieved from simulated results of the HEBDG system in Matlab/Simulink and empirical data collected in the laboratory collectively demonstrate that the proposed methodology exhibits exceptional performance in terms of 98.22 % accuracy and resistance to noise, surpassing existing state-of-the-art approaches.
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    Effectiveness of un-decimated wavelet transform in time-series forecasting: A PV power calculation case study in BTU
    (Pergamon-Elsevier Science Ltd, 2026) Albayram, Mehmet; Yilmaz, Alper; Bayrak, Gokay; Basaran, Kivanc; Popescu, Luminita Georgeta
    This study explored the effectiveness of Un-Decimated Wavelet Transform (UWT) in time-series applications, using photovoltaic (PV) calculation as a case study. Real-time measurements of irradiance, ambient temperature, module temperature, and humidity were collected at 5-min intervals from a 1.2 kW rooftop PV system at Bursa Technical University. Wavelet-based features extracted with both UWT and the conventional Discrete Wavelet Transform (DWT) were combined with regression and tree-based learners to build 16 hybrid models. The results show that the shift-invariant UWT significantly improves both feature extraction and prediction accuracy compared to the DWT approach. The UWT-DT model achieved the highest accuracy, with the lowest MSE (0.0001), the lowest RMSE (0.0118) and the highest R-2 coefficient (0.9986). A Wilcoxon signed-rank test applied to paired RMSE values confirmed that these improvements were statistically significant (p value < 0.05 for UWTDT vs DWT-DT). In terms of computational complexity, the 'a` trous' algorithm used in UWT requires convolution operations at every level, resulting in higher processing costs than DWT (12 ms feature extraction per 1024-sample input). However, the full-resolution features provided by UWT significantly reduced the error rates of treebased models, raising R-2 above 0.99.
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    Integrating hydrogen-powered fuel cell electric buses into grid-forming microgrids: A solution for emergency energy needs
    (Pergamon-Elsevier Science Ltd, 2025) Bayrak, Gokay; Basaran, Kivanc; Lazaroiu, Alexandra Catalina
    Fuel cell electric (FCE) buses have high-capacity batteries reaching up to 250-300 kW and high energy densities with hydrogen, so they can be used as a Mobile Microgrid (MoMG) by being supported by renewables. In this study, an FCE bus comprising a SOFC fuel cell stack and a battery is modeled as a Mobile Microgrid (MoMG) using MATLAB/Simulink to deliver mobile electrical energy support to regions inaccessible during disaster situations. To develop the V2L, V2V, and V2G functions of the MoMG, an Enhanced Grid Forming Control (EGFC) method is proposed, considering the IEEE 2800-2022 standards to ensure inverter-grid synchronization. In the proposed model, sudden changes in hydrogen power, evaluation of battery energy storage system (BESS) response during sudden load change, islanding conditions, and temporary and permanent faults are investigated. EGFC enables the FCE bus to maintain operation under both steady-state and transient conditions, achieving +1.5 % in grid voltage and current, +3 % grid active power and reactive power, and +0.01 Hz in frequency. The obtained results show that the proposed EGFC provides a reliable and stable grid integration of an FCE bus, providing the MoMG with low-voltage ride-through (LVRT) and fault ride-through (FRT) capabilities.
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    Sizing and Techno-Economic Analysis of Utility-Scale PV Systems with Energy Storage Systems in Factory Buildings: An Application Study
    (Mdpi, 2025) Basaran, Kivanc; Ozdemir, Mahmut Temel; Bayrak, Gokay
    In recent years, PV power plants have been widely used on the roofs of commercial buildings with grid connections, primarily to enhance self-consumption in distributed energy systems. In addition, installing PV plants on commercial buildings' roofs is becoming increasingly important, especially in crowded cities where land is limited. Since the Sun is an intermittent energy source, PV power plants cause frequency and voltage fluctuations in the grid. The way to avoid this problem is to install PV plants together with battery storage systems. Battery storage systems prevent frequency and voltage fluctuations in the grid and provide economic benefits. This article presents the sizing and techno-economic analysis of a factory building's rooftop PV system with a battery. The amount of energy produced by the PV plant, PV temperature, and irradiation were recorded in a data logger obtained by various sensors. These real-time measurements were continuously collected and analyzed to evaluate system performance and assess seasonal variations.Load demand data were collected through an automatic meter reading system. The installed capacity of the PV power plant is 645 kW. The optimum battery capacity determined for this factory is 130 kW for 5 h. Techno-economic analysis was carried out using metrics such as the payback period, net present value, and levelized cost of energy. As a result of the analysis using various input variables, LCOE, NPV, and PBP were determined as 0.1467 $/kWh, 4918.3 $, and 7.03 years, respectively.