Abstract:Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain param… Show more
“…The objective function is determined in advance for the design of optimization techniques based on the desired specifications and constraints [72]. The objective function used to optimize the controller parameters is typically chosen based on performance criteria that are dependent on system response [73]. The desired specification in a time domain system is the value of overshoot, rise time, settling time, and steady-state error [74].…”
Frequency dynamics is one of the important aspects of power system stability. From the frequency dynamics, the operator could plan how is the reliability of the electricity. The frequency can be maintained by controlling the balance between load demand and generation. To maintain the balance of the generation, the governor is playing an important role to increase the speed of the turbine and enhance the generating capacity of the generator (ramp-up). However, as the speed of the governor is slower than the increasing load demand, in the sub-transient area, the frequency may experience higher overshoot. Hence, it is important to add additional devices such as battery energy storage systems to enhance the frequency dynamics response in the sub-transient area. One of the important parts of storage is the controller. The controller must make sure the storage charges and discharge energy are in the sub-transient area. Hence PID controller can be the solution to make the storage operate optimally This paper proposed a novel PID controller on battery energy storage systems (BESS) to enhance the dynamics performance of frequencies. The five-area power system is used as the test system to investigate the efficacy of the proposed novel idea. Time domain simulation is investigated to see the improvement of the frequency dynamics response. From the simulation results, it is found that adding a PID controller on BESS could enhance the BESS response and result in frequency dynamics response improvement.
“…The objective function is determined in advance for the design of optimization techniques based on the desired specifications and constraints [72]. The objective function used to optimize the controller parameters is typically chosen based on performance criteria that are dependent on system response [73]. The desired specification in a time domain system is the value of overshoot, rise time, settling time, and steady-state error [74].…”
Frequency dynamics is one of the important aspects of power system stability. From the frequency dynamics, the operator could plan how is the reliability of the electricity. The frequency can be maintained by controlling the balance between load demand and generation. To maintain the balance of the generation, the governor is playing an important role to increase the speed of the turbine and enhance the generating capacity of the generator (ramp-up). However, as the speed of the governor is slower than the increasing load demand, in the sub-transient area, the frequency may experience higher overshoot. Hence, it is important to add additional devices such as battery energy storage systems to enhance the frequency dynamics response in the sub-transient area. One of the important parts of storage is the controller. The controller must make sure the storage charges and discharge energy are in the sub-transient area. Hence PID controller can be the solution to make the storage operate optimally This paper proposed a novel PID controller on battery energy storage systems (BESS) to enhance the dynamics performance of frequencies. The five-area power system is used as the test system to investigate the efficacy of the proposed novel idea. Time domain simulation is investigated to see the improvement of the frequency dynamics response. From the simulation results, it is found that adding a PID controller on BESS could enhance the BESS response and result in frequency dynamics response improvement.
“…The accuracy and efficiency of SM is closely related to the quality and quantity of the dataset used for training [12][13][14]. For optimal design, the training dataset must be representative of the entire input space to avoid bias and allow the surrogate model to generalize well [15][16][17]. Despite the critical role of dataset selection, comprehensive discussions on optimizing the data selection strategy for efficiency and fast convergence are lacking in past literature on electric machine design.…”
The efficient design optimization of electric machines for electric power steering (EPS) applications poses challenges in meeting demanding performance criteria, including high power density, efficiency, and low vibration. Traditional optimization approaches often fail to find a global solution or suffer from excessive computation time. In response to the limitations of traditional approaches, this paper introduces a novel methodology by incorporating a Gaussian process-based adaptive sampling technique into a surrogate-assisted optimization process using a metaheuristic algorithm. Validation on a 72-slot/8-pole interior permanent magnet (IPM) machine demonstrates the superiority of the proposed approach, showcasing improved exploitation–exploration balance, faster convergence, and enhanced repeatability compared to conventional optimization methods. The proposed design process is then applied to two surface PM (SPM) machine configurations with 9-slot/6-pole and 12-slot/10-pole combinations for EPS applications. The results indicate that the 12-slot/10-pole SPM design surpasses the alternative design in torque density, efficiency, cogging torque, torque ripple, and manufacturability.
“…From a control point of view, the researcher implemented classical and advanced controllers to control the levitated position. BP neural network-based control strategy is used to control the six-pole machine [16], flux density feedback control is used for the flywheel energy storage application [17], and metaheuristic optimization techniques are used to control the AMB for high-speed applications [18]. In comparison to these, control strategies proposed two loop-control that is simple and efficient in controlling the desired stable position and is cost-effective.…”
In the rotating machinery sector, active magnetic bearing (AMB) has drawn great attention due to its benefits over the conventional bearing system. The high-speed technology is enhanced by AMBs, which also reduce maintenance costs and eliminate friction loss. This paper presents a unique, simpler, efficient design and hardware implementation for high-speed applications using two-coil I-type active magnetic bearings. To maintain the 10 mm air gap between the actuator and the rotor, two categories of controllers have been designed for the proposed system to control the position and another for detecting the coil current through the power amplifier. The AMB system is incorporated into a 3D finite element model for determining magnetic properties. The magnetic analysis is then carried out under various situations, and the attractive force characteristics have been evaluated for this suggested system to check the performance of the multicoil AMB system along with the stability analysis. The system is designed and simulated in MATLAB Simulink and implemented in hardware to validate the different outputs viz. position response and current response. Finally, an AC magnet is designed to rotate the rotor after the levitation, and a higher speed of 19,643 rpm is achieved in comparison to conventional bearings, which can be utilized in different industrial applications.
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