A comparative study of LQR, LQG, and integral LQG controller for frequency control of interconnected smart grid

Rahman, Mizanur; Sarkar, Subroto K.; Das, Sajal K.; Miao, Yuan

doi:10.1109/eict.2017.8275216

Cited by 21 publications

(8 citation statements)

References 7 publications

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“…The design of LQG controller without the action of integral part has lack of ability to make the system robust against different uncertainties produced by the environment [125]. The Integral controller alone is used to track the reference signal by reducing error [126]. Though this controller has large gain at low frequency, it provides a low performance against plant dynamics.…”

Section: Integral Linear Quadratic Gaussian Controllermentioning

confidence: 99%

A survey on control issues in renewable energy integration and microgrid

Badal

Das

Sarker

et al. 2019

Prot Control Mod Power Syst

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245

112

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This paper describes the usefulness of renewable energy throughout the world to generate power. Renewable energy adds a remarkable scope in power system. Renewable energy sources act as the prime mover of a microgrid. The Microgrid is a small network of power system with distributed generation (DG) units connected in parallel. The integration challenges of renewable energy sources and the control of microgrid are described in this paper. The varied nature of DG system produces voltage and frequency deviation. The unknown nature of the load produces un-modeled dynamics. This un-modeled dynamic introduces measurable effects on the performance of the microgrid. This paper investigates the performance of the microgrid against different scenarios. The voltage of the microgrid is controlled by using different controllers and their results are also investigated. The performance of controllers is investigated using MATLAB/Simulink SimPowerSystems.

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Section: Integral Linear Quadratic Gaussian Controllermentioning

confidence: 99%

A survey on control issues in renewable energy integration and microgrid

Badal

Das

Sarker

et al. 2019

Prot Control Mod Power Syst

Self Cite

245

112

View full text Add to dashboard Cite

show abstract

“…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. On the other hand, researchers have preferred to use the proportional-integral-derivative (PID) controller owing to its advantages (i.e.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…On the other side, the LQG technique is attached with the integral gain for diminishing any oscillations in frequency response in an integrated power grid. Besides, this strategy gives better performance than using the LQG controller alone [17]. However, different studies considered different optimization techniques to determine the optimum constraints of the LQR, and LQG [4], [44].…”

Section: A Literature Reviewmentioning

confidence: 99%

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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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“…Power fluctuation occurs due to the unknown loads and faults [8] [9]. The inertia and synchronising force may be hampered and system outages may be increased while operating the power system with renewable energies [10].…”

Section: Introductionmentioning

confidence: 99%

Transient Stabilization Improvement of Induction Generator Based Power System using Robust Integral Linear Quadratic Gaussian Approach

Badal¹,

Sarker²,

Das³

2019

ijSmartGrid

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Interconnected power system consisting of a number of power generation units are able to fulfil the demand of electricity throughout the world. A safe and reliable operation of interconnected power system is possible when all the generators remain at synchronism state. Stability problem arises when the damping torque of these generators is reduced due to the effect of different uncertainties, faults and dynamic loads. The result of insufficient damping torque may deviate the speed of the generators and produce unsafe operation of power system due to the loss of stability and robustness of terminal voltage and rotor angle. In this paper, a novel integral linear-quadratic Gaussian (ILQG) controller is designed to regulate the oscillation of the power system for increasing stability and robustness. The better performance of the proposed controller is ensured by comparing it with the linear-quadratic regulator (LQR) and the linear-quadratic Gaussian (LQG) controllers. The comparison results ensure the optimum performance of the proposed controller against uncertainties and fault as compared to the LQR and LQG controller.

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A comparative study of LQR, LQG, and integral LQG controller for frequency control of interconnected smart grid

Cited by 21 publications

References 7 publications

A survey on control issues in renewable energy integration and microgrid

A survey on control issues in renewable energy integration and microgrid

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

Transient Stabilization Improvement of Induction Generator Based Power System using Robust Integral Linear Quadratic Gaussian Approach

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