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Artykuły w czasopismach na temat "PI-RES CONTROLLER"
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Gayathri Devi, K. S., and P. Sujatha Therese. "Optimized PI controller for 7-level inverter to aid grid interactive RES controller." Journal of Central South University 28, no. 1 (2021): 153–67. http://dx.doi.org/10.1007/s11771-021-4593-1.
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Vijayan, Maya, Ramanjaneya Reddy Udumula, Tarkeshwar Mahto, et al. "Optimal PI-Controller-Based Hybrid Energy Storage System in DC Microgrid." Sustainability 14, no. 22 (2022): 14666. http://dx.doi.org/10.3390/su142214666.
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Power availability from renewable energy sources (RES) is unpredictable, and must be managed effectively for better utilization. The role that a hybrid energy storage system (HESS) plays is vital in this context. Renewable energy sources along with hybrid energy storage systems can provide better power management in a DC microgrid environment. In this paper, the optimal PI-controller-based hybrid energy storage system for a DC microgrid is proposed for the effective utilization of renewable power. In this model, the proposed optimal PI controller is developed using the particle swarm optimization (PSO) approach. A 72 W DC microgrid system is considered in order to validate the effectiveness of the proposed optimal PI controller. The proposed model is implemented using the MATLAB/SIMULINK platform. To show the effectiveness of the proposed model, the results are validated with a conventional PI-controller-based hybrid energy storage system.
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Yousef, Ali Mohamed, Farag K. Abo-Elyousr, Ahmed Elnozohy, Moayed Mohamed, and Saad A. Mohamed Abdelwahab. "Fractional Order PI Control in Hybrid Renewable Power Generation System to Three Phase Grid Connection." International Journal on Electrical Engineering and Informatics 12, no. 3 (2020): 470–93. http://dx.doi.org/10.15676/ijeei.2020.12.3.5.
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The main objective of this paper is to allow renewable energy sources (RES) to actively participate within hybrid microgrid by proposing a new control system based on fractional order proportional integral (FOPI) controller. Fractional order proportional integral controller is a classical proportional integral (PI) in which the integral part is a fraction instead of integer numbers. The paper introduces a hybrid photovoltaic (PV), wind turbine and battery storage system connected to a three-phase grid. Three types of controller are considered and compared for a hybrid renewable energy system (HRES), namely, FOPI, PI, and the fractional order integral control (FIC). For the PV resource, maximum power point tracking (MPPT) controller was designed using the incremental conductance plus integral regulator technique. A DC/DC boost converter was utilized to connect the renewable energy resources to a point of common coupling. MATLAB/Simulink is adopted to perform the simulation results of the developed HRES. The results show that the FOPI controller outperforms other controllers under several operating conditions. The paper also includes experimental results from a prototype real scale.
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Firouzjahi, M., and A. Shokri. "Optimal design and control for UPFC using the evolutionary algorithms." Bangladesh Journal of Scientific and Industrial Research 51, no. 3 (2016): 231–38. http://dx.doi.org/10.3329/bjsir.v51i3.29435.
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Among the Unified Power Flow Controller (UPFC) tools, Flexible Alternating Current Transmission Systems (FACTS) have ability to control the transmitted power, improve transient and dynamic stability and improve the profile of the voltage and damping of the oscillations in the power system. Using the proportional-integral (PI) and proportional-integral-derivative (PID) controllers is a custom method. Selecting the PI and PID coefficients is through different methods. Also designing a resistant controller which can control the system in different points of work has been continuously considered by researchers. In this regard, in order to improve the performance of UPFC controllers, adjusting its parameters is required optimally which this matter itself would facilitate accessing to control objectives. In this project, UPFC is used for damping the oscillations of the power system. Also, in order to adjust the controller parameters optimally, evolutionary algorithms like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (HPSO) and other algorithms are used.Bangladesh J. Sci. Ind. Res. 51(3), 231-238, 2016
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Kumar, Kailash, Suyog Vinayak Pande, T. Ch Anil Kumar, et al. "Intelligent Controller Design and Fault Prediction Using Machine Learning Model." International Transactions on Electrical Energy Systems 2023 (April 29, 2023): 1–9. http://dx.doi.org/10.1155/2023/1056387.
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In a solar power plant, a solid phase transformer and an optimization coordinated controller are utilized to improve transient responsiveness. Transient stability issues in a contemporary electrical power system represent one of the difficult tasks for an electrical engineer due to the rise in uncertain renewable energy sources (RESs) as a result of the need for green energy. The potential for terminal voltage to be adversely impacted by this greater RES raises the possibility of electrical device damage. It is possible to use a solid state transformer (SST) or smart transformer to address a transient response issue. These devices are frequently employed to interact between RES and a power grid. SST features a variety of regulated converters to maintain the necessary voltage levels. This method can therefore simultaneously lessen power fluctuations and transient responsiveness. In order to improve the quality of RES power injections and the electrical system’s transient stability, this work provides a controller design for a solar photovoltaic (SPV) system that is connected to the grid by SST. The optimization of a controller model is proposed by modifying a PI controller taken from a commercial one. With the use of IEEE 39 standard buses, the proposed controller is tested. When evaluating the effectiveness of a suggested controller, it is important to take into account a variety of solar radiation patterns as well as a time delay uncertainty that can range from 425 ms to 525 ms. According to simulation results, the proposed controller can be employed to lessen power fluctuation brought on by unpredictable RES. Additionally, the proposed coordinated regulation of SPV and SST can prevent catastrophic damage in the event of substantial disturbances like a circuit breaker collapsing to expand a power line due to a fault by inhibiting significant voltage cycles within an electronic appliance’s rated voltage limit. The results indicate that a transitory stability issue in a modern power system caused by an unforeseen increase in RES may be addressed utilizing the suggested controllers as alternatives.
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Zhang, Guoqiang, Irfan Ahmed Khan, Amil Daraz, Abdul Basit, and Muhammad Irshad Khan. "Load Frequency Control of Marine Microgrid System Integrated with Renewable Energy Sources." Journal of Marine Science and Engineering 11, no. 4 (2023): 844. http://dx.doi.org/10.3390/jmse11040844.
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In seaports, low-carbon energy systems and energy efficiency have become increasingly important as a result of the evolution of environmental and climate change challenges. In order to ensure the continued success of seaports, technological advancements must be introduced to a number of systems, such as seaport vehicles, harbor cranes, and the power sources of berthed ships. Harbor areas might need a microgrid to handle these aspects. Typically, microgrids that substitute conventional generator units with renewable energy sources (RES) suffer from system inertia problems, which adversely affect microgrid frequency stability. A load frequency controller (LFC) based on a novel modified proportional integral derivative with filter (MPIDF) is presented in this paper for enhancing the performance of marine microgrid system (MMS). The serval optimization algorithm (SOA), a recent bio-inspired optimization algorithm, is used to optimize the MPIDF controller coefficients. This controller is tested on a marine microgrid containing a number of RES such as wind turbine generators, sea wave energy, and solar generation. The efficacy of the proposed MPIDF controller is verified with respect to other controllers such as PIDF and PI. Similarly, the proposed meta-heuristic algorithm is validated as compared to other algorithms including particle swarm optimization (PSO), ant colony optimization (ACO), and jellyfish swarm optimization (JSO). This study also evaluates the robustness of the proposed controller to different perturbations in step load, changes in system parameters, and other parameter variations.
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Et.al, N. Pooja. "Energy Management System Designed for Residential Grid connected Micro Grid." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 4627–34. http://dx.doi.org/10.17762/turcomat.v12i3.1867.
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This paper presents an energy management system supported by PI Controller for a residential grid connected micro grid with renewable hybrid generation (wind and photo voltaic) and battery system. Modeling hybrid system includes non conventional energy sources given at sporadic supply conditions and dynamic energy demand, and to make conceptual energy storage with the help of battery system . Designing an appropriate scheme that dynamically changes modes of renewable integrated system based on the availability of RES power and changes in load. Wind,PV are the primary power supply of the system; battery is going to be act as a substitute.The PI controller is developed and carried out for the aimed hybrid(Wind and PV) energy system to integrate the non conventional energy sources to the serviceability either to grid or to Residential loads.main objective is improvement of transients during switching periods by using an efficient PI controller.maximum power point tracking is also other objective is energy management system designed for the residential grid connected Micro Grid. Simulations are carried out on the proposed Hybrid energy system using MATLAB/ SIMULINK.
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Saleh, Amr, Hany M. Hasanien, Rania A. Turky, et al. "Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids." Sustainability 15, no. 6 (2023): 5009. http://dx.doi.org/10.3390/su15065009.
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For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly in microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects the microgrid dynamics under uncertainties, lowering the microgrid frequency stability, specifically in the islanded mode of operation. Therefore, this work aims to enhance the islanded microgrid frequency resilience using the virtual inertia frequency control concept. Additionally, optimal model predictive control (MPC) is employed in the virtual inertial control model. The optimum design of the MPC is attained using an optimization algorithm, the African Vultures Optimization Algorithm (AVOA). To certify the efficacy of the proposed controller, the AVOA-based MPC is compared with a conventional proportional–integral (PI) controller that is optimally designed using various optimization techniques. The actual data of RES is utilized, and a random load power pattern is applied to achieve practical simulation outcomes. Additionally, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability. The simulation findings show the effectiveness of AVOA-based MPC in improving the microgrid frequency resilience. Furthermore, the results secure the role of BES in improving transient responses in the time domain simulations. The simulation outcomes are obtained using MATLAB software.
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Valluri, Ashok Babu. "Novel Control Approach with FRT capability for Grid connected HYBRID distributed generation system using ANN controller based DVR." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (2021): 2002–21. http://dx.doi.org/10.22214/ijraset.2021.39684.
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Abstract: For ever increasing power demand and depletion of conventional energy resources, Renewable Energy Systems (RES) became an alternative source of electricity to reduce the load stress on the Power Grid. Although several control & design modifications are presented in past literature to improve reliability & performance of through Distribution Generation (DG) technologies, they always fall short in some aspects of voltage stability and Fault Ride Through (FRT) capabilities. The main aim of the project is Protecting Critical load from Grid side altercations which occur due to harmonics generated by DG’s and Short circuit faults near to load center. This project proposes the application of a Dynamic Voltage Restorer (DVR) to enhance the power quality and improve the Fault Ride Through (FRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation (DG) system. In this hybrid farm, the Photo Voltaic (PV) plant via single-stage energy conversion (DC-AC inverter) & DFIG (Doubly-Fed Induction Generator) based Wind power plant are connected to the same Point of Common Coupling (PCC). For MPPT of wind power plant, we use Pitch Angle Control (PAC) technique. This topology allows Perturb and observe (P&O) based MPPT algorithm for PV plant through connection of the DG (Distribution generation) system to the public grid through a step-up transformer. In addition, the DVR based on Artificial Neural Network (ANN) controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the sensitive Load. The efficiency of this control technique is that it enhances restoration and harmonics suppression capabilities of DVR which are far superior than that of PI controller used in existing model. Keywords: RES, DG, LVRT, FRT, PV, DFIG, PCC, MPPT, P&O, DVR, PI, ANN, THD, Voltage stability.
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Reddy, Ch Rami, B. Srikanth Goud, Flah Aymen, Gundala Srinivasa Rao, and Edson C. Bortoni. "Power Quality Improvement in HRES Grid Connected System with FOPID Based Atom Search Optimization Technique." Energies 14, no. 18 (2021): 5812. http://dx.doi.org/10.3390/en14185812.
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An intelligent control strategy is proposed in this paper which suggests the Optimum Power Quality Enhancement (OPQE) of grid-connected hybrid power systems with solar photovoltaic, wind turbines, and battery storage. Unified Power Quality Conditioner with Active and Reactive power (UPQC-PQ) is designed with Atom Search Optimization (ASO) based Fractional-order Proportional Integral Derivative (FOPID) controller in the proposed Hybrid Renewable Energy Sources (HRES) system. The main aim is to regulate voltage while reducing power loss and reducing Total Harmonic Distortion (THD). UPQC-PQ is used to mitigate the Power Quality (PQ) problems such as sag, swell, interruptions, real power, reactive power and THD reductions related to voltage/current by using ASO based FOPID controller. The developed technique is demonstrated in various modes: simultaneous to improve PQ reinforcement and RES power injection, PRES > 0, PRES = 0. The results are then compared to those obtained using previous literature methods such as PI controller, GSA, BBO, GWO, ESA, RFA, and GA and found the proposed approach is efficient. The MATLAB/Simulink work framework is used to create the model.