Optimal automatic generation control of two-area power systems with energy storage units under deregulated environment

Arya, Yogendra; Kumar, Narendra; Gupta, Kunal

doi:10.1063/1.5018338

Cited by 49 publications

(49 citation statements)

References 19 publications

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“…If the closed-loop transfer function is unknown, the closed-loop frequency response can be measured experimentally. (iv) Obtain the frequency model of the feedforward compensator by using Equations (22) and (27), and compute the frequency response according to Equation (10). (v) Fit the frequency response (10) with the minimum-phase transfer function F(s) of appropriate order.…”

Section: Robust Design Proceduresmentioning

confidence: 99%

“…Many controllers have been designed based on the optimization techniques including model‐matching method, performance index minimization, state‐feedback control strategy, reinforcement learning algorithm, genetic algorithm, and honey‐bee mating optimization…”

Section: Introductionmentioning

confidence: 99%

“…It can be achieved by optimizing both the gain and phase indices of control system. Many controllers have been designed based on the optimization techniques including model-matching method, 2-7 performance index minimization, 8 state-feedback control strategy, 9,10 reinforcement learning algorithm, 11 genetic algorithm, 12 and honey-bee mating optimization. 13,14 Especially many researchers have used the model-matching method in the design of feedforward compensator to improve reference tracking.…”

Section: Introductionmentioning

confidence: 99%

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Optimal design of robust feedforward compensator with gain and phase specifications

Jon¹,

Pak²

2019

Optim Control Appl Methods

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Summary This paper deals with the design of the robust feedforward compensator for improving the tracking performance of control systems with gain and phase specifications. The feedforward compensator is designed for single‐input–single‐output continuous‐time linear systems with constrained input and model uncertainty. The design objective is to make the transfer characteristic from command to output be one in the presence of the input saturation and the model uncertainty. To do that, the design of the feedforward compensator is formulated as a new gain‐phase optimization problem with both the gain and phase specifications. Then, the design procedures are proposed by using frequency‐matching method based on the closed‐loop frequency response. The proposed method provides a good trade‐off between system performance and control input to overcome performance reduction due to input saturation, and guarantees the robustness of the overall system in the presence of the model uncertainty. Two design examples illustrate that the frequency characteristics and the transient response of the control system are improved by the proposed method.

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Section: Robust Design Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal design of robust feedforward compensator with gain and phase specifications

Jon¹,

Pak²

2019

Optim Control Appl Methods

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“…Nowadays, the conventional power system has been transformed to restructured domain. In the past, various researchers investigated ALFC problem in deregulated environment . The basic framework for ALFC in deregulated electricity market with price‐based operation had been demonstrated in previous literature .…”

Section: Introductionmentioning

confidence: 99%

“…Donde et al studied the two‐area thermal system and established the basic concept of distribution company (DISCO) participation matrix (DPM). Authors investigated two‐area thermal, hydrothermal, and thermal‐gas system in deregulated environment. But, authors did not consider any system nonlinearities for the analyses .…”

Section: Introductionmentioning

confidence: 99%

Performance of coordinated interline power flow controller and power system stabilizer in combined multiarea restructured ALFC and AVR system

Rajbongshi

Saikia

2019

Int Trans Electr Energ Syst

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Summary This article analyzed the performance of coordinated interline power flow controller (IPFC) and power system stabilizer (PSS) in the combined two‐area restructured automatic load frequency control (ALFC) and automatic voltage regulator (AVR) system. Each area of the system has three generating companies as reheat thermal, wind, and diesel and three distribution companies (DISCOs). Appropriate physical constraints are included in thermal plant. Proportional plus fractional integral plus derivative with filter (PIλDF) controller is introduced as secondary controller for both ALFC and AVR loop. Lightning search algorithm is employed for optimization of the parameters of controller as well as PSS. The control performance of the proposed controller is compared with some classical integer‐order controllers and reflects the dominance of the former over others with less peak deviation, settling time, and figure of demerit in all three transactions of restructured power system. The investigation of the impact of combined controlling action of IPFC and PSS reveals that the integration of the same improves the system dynamics effectively than the individual inclusion of IPFC and PSS. The coordinated IPFC‐PSS provides less peak deviation, oscillation, as well as faster settling time and enhances the system performance. The sensitivity analysis of PIλDF controller and PSS parameters for different DISCO participation matrix and amount of contract violation derived the robustness of the same.

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PID‐ / FOPID ‐based frequency control of zero‐carbon multisources‐based interconnected power systems underderegulated scenarios

Ebrahim

Becherif

Abdelaziz

2020

Int Trans Electr Energ Syst

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Summary Zero‐carbon multienergy sources (ZCESs) integration into a power system becomes mandatory to reduce energy production costs and fuel‐burning emissions. Although, the energy mix of ZCESs with high penetration levels arises at moderated frequency as well as voltage response deterioration of the interconnected power systems. These response deteriorations stem from the fluctuation nature of ZCESs. Therefore, the necessity for overcoming these performance degradations is not an option for power system planners and operators. Thanks to fractional order (FO) mathematics in conjunction with metaheuristic optimization algorithms (MOAs) as they can be employed to enhance the damping of ZCESs oscillations under energy mix uncertainties. Three‐area solar thermal‐wind‐hydro (STWH) power system, including system's uncertainties such as data telemetry delays and governor dead bandsand generation rate constraints, is considered to accomplish this study. The performance of STWH system equipped with FOPID‐based load frequency controllers tuned by various modern MOAs (FOPID‐based LFCs) has been compared to the classical PID‐LFC controllers governed by the same MOAs, to demonstrate the superior efficiency of the FOPID‐based LFCs. The efficacy of FOPID‐based LFCs and their effectiveness compared to the predecessors are verified during simulation results.

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Optimal automatic generation control of two-area power systems with energy storage units under deregulated environment

Cited by 49 publications

References 19 publications

Optimal design of robust feedforward compensator with gain and phase specifications

Optimal design of robust feedforward compensator with gain and phase specifications

Performance of coordinated interline power flow controller and power system stabilizer in combined multiarea restructured ALFC and AVR system

PID‐ / FOPID ‐based frequency control of zero‐carbon multisources‐based interconnected power systems underderegulated scenarios

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