A Two-Layer Active Disturbance Rejection Controller Design for Load Frequency Control of Interconnected Power System

Liu, Fang; Li, Yong; Cao, Yijia; She, Jinhua; Wu, Min

doi:10.1109/tpwrs.2015.2480005

Cited by 120 publications

(56 citation statements)

References 7 publications

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“…where the parametersα i , (i = 1, 2, · · · , n α ),β j , (j = 1, 2, · · · , n β ) andγ l (l = 1, 2, · · · , n γ ) of HNN are associated weights in (8) and (9), respectively. In this section, negative gradient training method applied for adjusting the weights of HNN is executed to identify the Hammerstein model.…”

Section: B Hammerstein-type Neural Network Identificationmentioning

confidence: 99%

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

Liu

Yan

et al. 2018

IEEE Trans. Ind. Electron.

152

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Abstract-This paper concentrates on the problem of control of a hybrid energy storage system (HESS) for an improved and optimized operation of load-frequency control (LFC) applications. The HESS consists of a supercapacitor served as the main power source, and a fuel cell served as the auxiliary power source. Firstly, a Hammerstein-type neural network (HNN) is proposed to identify the HESS system, which formulates the Hammerstein model with a nonlinear static gain in cascade with a linear dynamic block. It provides the model information for the controller to achieve the adaptive performance. Secondly, a feedforward neural network based on back-propagation training algorithm is designed to formulate the PID-type neural network (PIDNN), which is used for the adaptive control of HESS system. Meanwhile, a dynamic anti-windup signal is designed to solve the operational constraint of the HESS system. Then, an appropriate power reference signal for HESS can be generated. Thirdly, the stability and the convergence of the whole system are proved based on the Lyapunov stability theory. Finally, simulation experiments are followed through on a four-area interconnected power system to demonstrate the effectiveness of the proposed control scheme.Index Terms-Load-frequency control (LFC), hybrid energy storage system (HESS), Hammerstein network identification, PIDtype neural network (PIDNN), dynamic anti-windup, adaptive control

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Section: B Hammerstein-type Neural Network Identificationmentioning

confidence: 99%

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

Liu

Yan

et al. 2018

IEEE Trans. Ind. Electron.

152

View full text Add to dashboard Cite

show abstract

“…The basis for attaining the regulation function is the tie line bias control concept that is introduced over 50 years ago [18] and widely used to model the power flow between two or more buses [2][3][4][5][6][9][10][11]19,20]. Tie line power deviation ∆P tie i is defined as the deviation power exported to the ith area and is equal to the sum of all outflowing line power changes in the line that connects to the ith area with its neighboring areas:…”

Section: Dynamic Model Of Power Systems With Multiple Areasmentioning

confidence: 99%

“…Despite the promising concept of adaptive controllers, the control algorithm is too complicated to implement in large scale systems and can show poor transient performance which can be critical in power systems. Several papers propose an observer for dealing with uncertain load changing in power systems with multiple areas [6][7][8][9][10][11][12][13][14][15][16]. In [6][7][8], a disturbance observer is considered to handle large-scale wind power in power systems.…”

Section: Introductionmentioning

confidence: 99%

“…In [6][7][8], a disturbance observer is considered to handle large-scale wind power in power systems. In these applications, the uncertainty and external disturbance are viewed as a total disturbance and rejected by an active disturbance observer proposed by [9][10][11][12][13]. The disturbance is estimated using an extended state observer (ESO) in [15].…”

Section: Introductionmentioning

confidence: 99%

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High-Gain Disturbance Observer-Based Robust Load Frequency Control of Power Systems with Multiple Areas

2017

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This paper proposes a high-gain disturbance observer (HDOB)-based controller for load frequency control (LFC) of power systems with multiple areas. The main goal of LFC problem is to maintain the frequency to its nominal value. The objective of this paper is to reject frequency variations due to abrupt load changes and diverse uncertainties (e.g., inertia and damping parameters, and interconnection topology, etc.) by employing the HDOB for the LFC. The simulation results demonstrate the effectiveness of the proposed HDOB-based LFC by showing that it successfully rejects frequency variations owing to load changes and frequency variations occurring in various locations in interconnected power systems. Besides, it is shown that the proposed LFC can eliminate frequency deviations although there are delays in transmission among the power systems with multiple areas.

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“…With such a novel concept, the ADRC technology has been successfully used in motion control areas, such as aircraft control. In addition, the ADRC controllers also work well in some areas of process control . In the USA, the ADRC solution was deployed at a Parker Hannifin extrusion plant, bringing about over 50 % energy savings per line across ten production lines, together with enormous improvements in product quality.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive decoupling control strategy for a gas flow facility based on active disturbance rejection generalized predictive control

Chen

Zhao

et al. 2018

Can J Chem Eng

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A comprehensive decoupling control (CDC) method, based on the active disturbance rejection generalized predictive control (ADRC-GPC) technology, is proposed in this paper for square multi-input multi-output (MIMO) systems. The central idea of this approach is that the total disturbance, which includes the partial coupling information among loops, the internal uncertainties, and the external disturbance, can be estimated by output through the extended state observer (ESO) and compensated in the feedback loop by feedback control law. Such estimating and cancelling can readily decouple the primal coupling system into multiple single-input single output (SISO) subsystems with the form of cascade integrators. Then the generalized predictive controller is designed for each subsystem. The proposed design is effectively used in the gas flow facility. Mathematical simulations and experiments show that compared with the proportional integral derivative (PID) method, the ADRC-GPC controller can achieve better dynamic performance, decoupling ability, disturbance rejection capability, and performance robustness.

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A Two-Layer Active Disturbance Rejection Controller Design for Load Frequency Control of Interconnected Power System

Cited by 120 publications

References 7 publications

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

High-Gain Disturbance Observer-Based Robust Load Frequency Control of Power Systems with Multiple Areas

A comprehensive decoupling control strategy for a gas flow facility based on active disturbance rejection generalized predictive control

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