What is a wind power generation system (WPGS)?This scholarly paper offers a wind power generation system (WPGS) that utilizes a configuration of parallel five-phase permanent magnet synchronous generators (PMSGs). The control mechanism for this system is based on a fifteen-switch rectifier (FSR) topology, which is specifically designed for grid-connected applications.
Can deep reinforcement learning improve wind farms' power-generation efficiency?Wind farms’ power-generation efficiency is constrained by the high system complexity. A novel deep reinforcement learning (RL)-based wind farm control scheme is proposed to handle this challenge and achieve power generation optimization.
Can a wind farm control system improve power production?Simulation results show that our method can significantly improve the wind farm’s total power production by 15% on average compared with the benchmark. The proposed control scheme is application-oriented. (1) The training and learning data (power output and yaw angle of each turbine) are easy to collect.
Can a hybrid controller improve the performance of a PMSG-based wind turbine?In this paper, the proposed WTPGS system is designed in MATLAB/Simulink software where a hybrid controller (ANFIS-PI) is implemented in the machine-side converter (MSC) and grid-side converter (GSC) of a variable speed PMSG-based wind turbine to enhance its performance subjected to wind variations.
Can deep RL-based wind farm control improve power generation optimization?The following results will show that our deep RL-based wind farm control method can achieve power generation optimization under such a sparse dataset collected by SOWFA. These results indicate that our method can use limited sets of actual wind farm data for algorithm training and learning purposes, and has strong applicability to real wind farms.
How does the Integrated wind power system work?The integrated WPS operates in both motor and generator modes, depending on the excess or shortfall of generated wind energy relative to load demand. In generator mode, the WPS supplements power when wind speeds are insufficient, while in motor mode, it stores excess energy by pumping water to an upper reservo
The paper concentrates on performance benefits of adding energy storage system with the wind generator in order to regulate the electric power
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This paper introduces a novel hybrid controller designed for a wind turbine power generation system (WTPGS) that utilizes a permanent magnet synchronous generator (PMSG).
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Wind turbines are used in wind energy to convert the energy of the wind into mechanical power [11]. The electric generator comes next in the generation system after the turbine. The latter
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This paper introduces a novel hybrid controller designed for a wind turbine power generation system (WTPGS) that utilizes a permanent magnet synchronous generator (PMSG).
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In the variable-speed generation system, the wind turbine can be operated at the maximum power operating point for various wind speeds by adjusting the shaft speed. These
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This scholarly paper offers a wind power generation system (WPGS) that utilizes a configuration of parallel five-phase permanent magnet synchronous generators (PMSGs).
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A high-performance on-line training radial basis function network-sliding mode (RBFNSM) algorithm is designed to derive the turbine speed to extract maximum power from
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In order to improve the intelligence and production efficiency of the wind power generation control system, a wind power generation control system based on artificial
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As the use of wind power turbines increases worldwide, there is a rising interest on their impacts on power system operation and control. Frequency regulation in interconnected networks is
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Control system services for power generation Whether wind, solar, gas or steam power plant: the control system plays a decisive role in the reliability of your plant. We provide tailor-made
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This scholarly paper offers a wind power generation system (WPGS) that utilizes a configuration of parallel five-phase permanent magnet synchronous generators (PMSGs).
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Innovative contributions: * Developed an autonomous model using intelligent control approaches. * Established a dynamic framework for a hybrid renewable energy system
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The performance of a wind turbine (WT) relies heavily on the control systems implemented on both the turbine side and the generator side. These systems deal with highly
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Abstract This scholarly paper offers a wind power generation system (WPGS) that utilizes a configuration of parallel five-phase permanent magnet synchronous generators (PMSGs). The
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Wind farms'' power-generation efficiency is constrained by the high system complexity. A novel deep reinforcement learning (RL)-based wind farm control scheme is proposed to handle this
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To overcome the drawbacks of the existing literature, an in-depth overview of ML and AI in wind turbine systems is presented in this paper.
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This study introduces the design, modeling, and control mechanisms of a self-sufficient wind energy conversion system (WECS) that utilizes a Permanent magnet
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This study designed and implemented an intelligent wind-powered water pumping and electricity generation system based on a microcontroller. The system utilizes optimized
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Concerning the current research on the maximum power point tracking (MPPT) algorithm, this paper studies the principle, characteristics,
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Intelligent Control for Increasing Maximum Extracted Power of a Wind Generation System. In: Hagras, H., Bennani, Y., Nemiche, M. (eds) Intelligent Systems and Advanced
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This chapter presents a sensorless control technique of wind speed for controlling wind-driven doubly fed induction generators (DFIGs) energy systems. A concept behind this
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Turbine control retrofits and green-energy solutions platforms are transforming the way operations teams manage wind-energy generation.
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Next-generation wind turbine control systems are evolving with intelligent automation, predictive monitoring, and grid-aware design to drive efficiency, resilience, and
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This review presents a state-of-the-art literature review of Automatic Generation Control (AGC) control strategies for power systems containing renewable energy sources. The
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In this paper, an intelligent control strategy for a grid connected hybrid energy generation system consisting of Photovoltaic (PV) panels, Fuel Cell (FC) stack and Battery
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Next-generation wind turbine control systems are evolving with intelligent automation, predictive monitoring, and grid-aware design to drive efficiency, resilience, and
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This scholarly paper offers a wind power generation system (WPGS) that utilizes a configuration of parallel five-phase permanent magnet synchronous generators (PMSGs). The control mechanism for this system is based on a fifteen-switch rectifier (FSR) topology, which is specifically designed for grid-connected applications.
Wind farms’ power-generation efficiency is constrained by the high system complexity. A novel deep reinforcement learning (RL)-based wind farm control scheme is proposed to handle this challenge and achieve power generation optimization.
Simulation results show that our method can significantly improve the wind farm’s total power production by 15% on average compared with the benchmark. The proposed control scheme is application-oriented. (1) The training and learning data (power output and yaw angle of each turbine) are easy to collect.
In this paper, the proposed WTPGS system is designed in MATLAB/Simulink software where a hybrid controller (ANFIS-PI) is implemented in the machine-side converter (MSC) and grid-side converter (GSC) of a variable speed PMSG-based wind turbine to enhance its performance subjected to wind variations.
The following results will show that our deep RL-based wind farm control method can achieve power generation optimization under such a sparse dataset collected by SOWFA. These results indicate that our method can use limited sets of actual wind farm data for algorithm training and learning purposes, and has strong applicability to real wind farms.
The integrated WPS operates in both motor and generator modes, depending on the excess or shortfall of generated wind energy relative to load demand. In generator mode, the WPS supplements power when wind speeds are insufficient, while in motor mode, it stores excess energy by pumping water to an upper reservoir.
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