Sampled-data based discrete and fast load frequency control for power systems with wind power

Shangguan, Xing-Chen; He, Yong; Zhang, Chuan‐Ke; Spencer, J. W.; Wu, Min

doi:10.1016/j.apenergy.2019.114202

Cited by 95 publications

(31 citation statements)

References 38 publications

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“…Thirdly, communication systems, currently used in a number of applications related to monitoring, control and protection [162][163][164], have a great prospect for improving the operation of modern power systems. Moreover, the load frequency control based on the sampled-data control is implemented to reduce the communication burden [165]. For a power system with reduced system inertia, the grid frequency is more likely to violate the statutory frequency limits due to the increased RoCoF.…”

Section: Discussion On Future Challengesmentioning

confidence: 99%

Smart frequency control in low inertia energy systems based on frequency response techniques: A review

Cheng

Azizipanah‐Abarghooee

Azizi

et al. 2020

Applied Energy

132

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Section: Discussion On Future Challengesmentioning

confidence: 99%

Smart frequency control in low inertia energy systems based on frequency response techniques: A review

Cheng

Azizipanah‐Abarghooee

Azizi

et al. 2020

Applied Energy

132

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“…fuzzy logic control [9], fuzzyproportional integral (PI) controller [10], the adaptive neuro-fuzzy logic controller [11], artificial neural networks (ANN) [12], layered recurrent ANN [13]) have been implemented to regulate the system frequency. Also, several digital control techniques have been implemented for frequency regulation of power systems in [14], [15]. Furthermore, optimal control techniques such as; linear quadratic regulator (LQR) [16] and linear quadratic Gaussian (LQG) [17], have been applied for enhancing the frequency stability of the system.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…FIGURE15. The single-area power system performance relied on various control techniques for case C, scenario 2.…”

mentioning

confidence: 99%

Optimal Model Predictive and Linear Quadratic Gaussian Control for Frequency Stability of Power Systems Considering Wind Energy

et al. 2021

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This work presents a new robust control technique which combines a model predictive control (MPC) and linear quadratic gaussian (LQG) approach to support the frequency stability of modern power systems. Moreover, the constraints of the proposed robust controller (MPC-LQG) are fine-tuned based on a new technique titled Chimp optimization algorithm (ChOA). The effectiveness of the proposed robust controller is tested and verified through a multi-area power system (i.e., single-area and two-area power systems). Each area contains a thermal power plant as a conventional generation source considering physical constraints (i.e. generation rate constraint, and governor dead band) in addition to a wind power plant as a renewable resource. The superiority of the proposed robust controller is confirmed by contrasting its performance to that of other controllers which were used in load frequency control studies (e.g., conventional integral and MPC). Also, the ChOA's ingenuity is verified over several other powerful optimization techniques; particle swarm optimization, gray wolf optimization, and ant lion optimizer). The simulation outcomes reveal the effectiveness as well as the robustness of the proposed MPC-LQG controller based on the ChOA under different operating conditions considering different load disturbances and several penetration levels of the wind power.

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“…Meanwhile, as the wind rotates the blades of the turbine, a rotor then grabs the kinetic energy positively existing in the wind. Mechanical output power trapped from the wind power system can be depicted as [30]:…”

Section: Investigated System Modelingmentioning

confidence: 99%

Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid

et al. 2021

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It is known that keeping the power balance between generation and demand is crucial in containing the system frequency within acceptable limits. This is especially important for renewable based distributed hybrid microgrid (DHμG) systems where deviations are more likely to occur. In order to address these issues, this article develops a prominent dual-level “proportional-integral-one plus double derivative {PI−(1 + DD)} controller” as a new controller for frequency control (FC) of DHμG system. The proposed control approach has been tested in DHμG system that consists of wind, tide and biodiesel generators as well as hybrid plug-in electric vehicle and an electric heater. The performance of the modified controller is tested by comparing it with standard proportional-integral (PI) and classical PID (CPID) controllers considering two test scenarios. Further, a recently developed mine blast technique (MBA) is utilized to optimize the parameters of the newly designed {PI − (1 + DD)} controller. The controller’s performance results are compared with cases where particle swarm optimization (PSO) and firefly (FF) techniques are used as benchmarks. The superiority of the MBA-{PI − (1 + DD)} controller in comparison to other two strategies is illustrated by comparing performance parameters such as maximum frequency overshoot, maximum frequency undershoot and stabilization time. The displayed comparative objective function (J) and JFOD index also shows the supremacy of the proposed controller. With this MBA optimized {PI − (1 + DD)} controller, frequency deviations can be kept within acceptable limits even with high renewable energy penetration.

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Sampled-data based discrete and fast load frequency control for power systems with wind power

Cited by 95 publications

References 38 publications

Smart frequency control in low inertia energy systems based on frequency response techniques: A review

Smart frequency control in low inertia energy systems based on frequency response techniques: A review

Optimal Model Predictive and Linear Quadratic Gaussian Control for Frequency Stability of Power Systems Considering Wind Energy

Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid

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