Browsing by Author "Tozak, M"

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    Modeling, simulation, and experimental verification of a smart grid system
    Tozak, M; Taskin, S; Sengor, I
    Due to the concern over the depletion of conventional fuels and increasing environmental awareness, creating a smarter grid has gained more significance and has been alluring a wide range of industrial and academic stakeholders. One of the main features of a smart grid (SG) system is being a fully observable and controllable infrastructure from generation to the consumption of electricity among other features. A SG didactic system developed by the De Lorenzo company is utilized for this study. The didactic system is used as it serves measurements at all buses and includes diverse power grid units and devices to be used for the analysis of the system. A MATLAB/Simulink model is obtained pertaining to a SG system with generation units, transformers, transmission lines, loads, measurement devices, compensation units, and so on. Along with the modeling of each subsystem of the SG, the developed model is validated by the experiments on the real system, and also the system performance is analyzed. The SG model is validated step by step on the real test system with errors ranging from 0 to 10.03%. Hence, it has been proven that the model is able to be applied to an enlarged system and to be used for test and experimental studies of new types of equipment and educational purposes without depending on the physical system.
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    Performance Analysis of Grid Forming Converters for a Didactic Smart Grid System
    Tozak, M; Taskin, S; Sengor, I
    Grid forming control for inverter-dominated power systems of the future is crucial as it enables more renewable penetration and provides enhanced stability. In this paper, a power system that consists of both Synchronous Machines (SM) and Grid Forming Controlled PV system is modeled and simulated in MATLAB((R))/ Simulink((R)). Moreover, the real parameters of laboratory pieces of equipment in Manisa Celal Bayar University Smart Grid Laboratory (MCBUSGLab) are used throughout the study. In addition, various Grid Forming Converter control methods such as droop control, matching control, and dispatchable virtual oscillator control are compared in terms of frequency stability under different conditions.
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    Modeling and Control of Grid Forming Converters: A Systematic Review
    Tozak, M; Taskin, S; Sengor, I; Hayes, BP
    In electrical power systems where the proportion of synchronous generators (SG) is gradually decreasing, grid-forming (GFM) converters need to be installed and controlled to meet all the system requirements that SGs have provided to date. Modeling, control, and implementation of GFM converters have been the subject of numerous studies in recent years, particularly in the context of ensuring grid stability during the transition to non-synchronous renewable energy sources. This paper provides a comprehensive literature review on the modeling and control of grid-connected converters. In particular, the focus is placed on GFM-type control structures, objectives, and applications. Both grid-following (GFL) and GFM control structures are detailed. Then, the objectives of controlling GFM converters in power systems are discussed in detail. Finally, some completed and ongoing GFM installation projects around the world are summarized under the subheadings of battery energy storage system (BESS), GFM wind, hybrid, and high voltage direct current (HVDC).
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    Development of a control algorithm and conditioning monitoring for peak load balancing in smart grids with battery energy storage system
    Atici, T; Taskin, S; Sengör, I; Tozak, M; Demirci, O
    As the traditional electricity grid transitions to the smart grid (SG), some emerging issues such as increased renewable energy penetration in the power system that cause load unbalances require new control methods. Storage of energy seems to be the best option to struggle with such issues. In this manner, energy storage technologies ensure the operating flexibility of the distribution system operator in the power system in terms of both sustainability of energy and peak load balancing. In this study, a grid condition monitoring user-interface and control algorithm is developed for the peak load reduction and supply-demand balancing in a SG system by using an energy storage unit. For this purpose, a battery energy storage system (BESS) is designed, scaled and integrated into the SG didactic test system, designed by the De Lorenzo Company. Online grid condition monitoring and control software is developed for grid connected photovoltaic (PV) system and the BESS in the LabVIEWTM program. Moreover, an algorithm is developed that provides the conditions for the integration of the BESS into the system. The proposed algorithm is tested with real daily load data of the Manisa province in Turkey. Also, various case studies are performed to validate the effectiveness of the algorithm. Consequently, the proposed algorithm provides an average load factor improvement of 8.46% and the algorithm-controlled BESS increases the revenue of the system by 3.51% compared to the grid-connected PV system alone.
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    Stability Analysis of Virtual Power Plant with Grid Forming Converters
    Tozak, M; Taskin, S; Sengor, I; Hayes, BP
    A virtual power plant is a system containing multiple distributed generators aggregated and flexibly coordinated to act as a single power source. This study investigates the active power, reactive power, frequency, and voltage support provided by a virtual power plant interconnected with the grid. The investigation encompasses the analysis of grid-forming (GFM)controlled wind and solar power plant units, considering the fluctuating power generation from solar and wind sources. The real hourly wind and solar generation profiles from currently operational plants are used as the active power set points. The stability and power reference tracking of grid-connected converters are analyzed using dispatchable virtual oscillator control (dVOC) and droop control-based methods. The results show that both control strategies substantially improve the virtual power plant's ability to ensure grid stability and accurately track power references, despite the inherent variability of wind and solar energy generation.