Load Frequency Control Method by Charge Control for Plug-in Hybrid Electric Vehicles with LFC Signal

2009 ◽  
Vol 129 (11) ◽  
pp. 1342-1348 ◽  
Author(s):  
Masaaki Takagi ◽  
Hiromi Yamamoto ◽  
Kenji Yamaji ◽  
Kunihiko Okano ◽  
Ryouji Hiwatari ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Control Method ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Charge Control ◽  
Load Frequency ◽  
Hybrid Electric

scholarly journals Optimization Technique Inspired Load Frequency Controller for Multi Area Power System with Renewable Energy Source

2021 ◽  
Vol 850 (1) ◽  
pp. 012017
Author(s):  
J Shri Saranyaa ◽  
A Peer Fathima ◽  
Asutosh Mishra ◽  
Rushali Ghosh ◽  
Shalmali Das
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Control Method ◽  
Frequency Control ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Optimization Method ◽  
Load Frequency Control ◽  
Load Frequency ◽  
The Individual

Abstract Modern day scenario has an increasing power demand due to the growing development which indeed increases the load on the generation which might cause turbulence in the system and may bounce out of stability. The governor itself can’t handle such frequent load changes and adjust the generation amount to keep the frequency between the margins. This paper proposes an approach towards such predicament to incorporate an optimization method in order to ensure stability of the system despite the drastic changes in demand. Load frequency control is a control method for maintaining the frequency of the system during the change in demand. Use of controllers has proven to be effective in controlling the frequency deviations in the power systems and the response of the controller is further improved using optimization technique for better stability. The PID controller tuned by Particle Swarm Optimization is employed in multi-area system which reduces the time response by a considerable amount and the deviation settles much quicker despite the rapid load changes. The proposed controller is executed further for renewable energy sources connected to the individual areas and demonstration proves that the optimized controller is efficient enough in handling the frequency deviations when wind and solar with sunlight penetration is incorporated.

A Decentralized Load Frequency Control Method by Means of Frequency Measurement of Adjacent Power Systems

1988 ◽  
Vol 21 (11) ◽  
pp. 387-393 ◽  
Author(s):  
H. Sasaki ◽  
H. Yorino ◽  
T. Suizu ◽  
S. Yurino ◽  
R. Yokoyama ◽  
...  
Keyword(s):  
Power Systems ◽  
Control Method ◽  
Frequency Control ◽  
Frequency Measurement ◽  
Load Frequency Control ◽  
Load Frequency

scholarly journals A Novel Control Method of Clutch During Mode Transition of Single-Shaft Parallel Hybrid Electric Vehicles

Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 54 ◽  
Author(s):  
Jingang Ding ◽  
Xiaohong Jiao
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Control Method ◽  
Transition Process ◽  
Operating Mode ◽  
Mode Transition ◽  
Control Approach ◽  
Proportional Integral ◽  
Parallel Hybrid ◽  
Hybrid Electric

The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor starting engine and the clutch control problem have an important influence on driving quality, and solutions have a bit of room for improving dynamic performance. In this paper, a novel mode transition control method is proposed to guarantee a fast and smooth mode transition process in this regard. First, an adaptive sliding mode control (A-SMC) strategy is presented to obtain the desired torque trajectory of the clutch transmission. Second, a proportional-integral (PI) observer is designed to estimate the actual transmission torque of the clutch. Meanwhile, a fractional order proportional-integral-differential (FOPID) controller with the optimized control parameters by particle swarm optimization (PSO) is employed to realize the accurate position tracking of the direct current (DC) motor clutch so as to ensure clutch transmission torque tracking. Finally, the effectiveness and adaptability to system parameter perturbation of the proposed control approach are verified by comparison with the traditional control strategy in a MATLAB environment. The simulation results show that the driving quality of the closed-loop system using the proposed control approach is obviously improved due to fast and smooth mode transition process and better adaptability.

scholarly journals Model Predictive Control for Connected Hybrid Electric Vehicles

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Kaijiang Yu ◽  
Xiaozhuo Xu ◽  
Qing Liang ◽  
Zhiguo Hu ◽  
Junqi Yang ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Control Method ◽  
Fuel Efficiency ◽  
Computation Method ◽  
Hybrid Electric

This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV forPbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

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