Optimal design of probabilistically robust PID controller to improve small signal stability of PV integrated power system

Shahsavari, Hossein; Nateghi, Alireza

doi:10.1016/j.jfranklin.2019.03.035

Cited by 9 publications

(2 citation statements)

References 35 publications

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“…Lastly, the technique improved the frequency/ DC voltage nadir along with the device's powerful performance, which could be seen through the simulation and investigational outcomes. Te optimal values of those parameters were not considered by the adaptive virtual inertia along with a virtual governor gain CS, and so, good performance was not assured [23].…”

Section: Related Workmentioning

confidence: 99%

An FRLQG Controller-Based Small-Signal Stability Enhancement of Hybrid Microgrid Using the BCSSO Algorithm

Ensermu

Santhi

Merugu

et al. 2023

Journal of Electrical and Computer Engineering

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The development of a network termed microgrid (MG) has been motivated owing to augmentation in renewable energy source (RES) infiltration along with the utilization of enhanced power electronic technologies. Recently, more popularity has been gained by the hybrid MG (HMG). Maintaining the power system’s (PS) small-signal stability (SSS) is highly complicated during the energy enhancement of RES. The enhancement of the SSS has been focused on by numerous existing methodologies; however, the optimal solution was not obtained by those methodologies. A new controller with the assistance of bell-curved squirrel search optimization (BCSSO) is proposed to address the aforementioned issue. Initially, for PSs such as photovoltaic (PV), wind turbines, along with fuel cells, a mathematical model is ascertained. Then, in this, the converter design has been developed. The PV’s maximum power flow is recognized by maximum power point tracking (MPPT) in the bidirectional switched buck-boost converter (BSBBC), which is utilized in this research, and by utilizing the fuzzy ruled linear quadratic Gaussian (FRLQG), the converters are controlled to assure safe operation along with soft dynamics. By employing the BCSSO, the parameters are modified in this controller which in turn ameliorates the SSS. The experiential evaluation of the proposed system’s performance is analogized with the existing methodologies. Consequently, the outcomes confirmed that a better performance was attained by the proposed methodology than the prevailing works.

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Section: Related Workmentioning

confidence: 99%

An FRLQG Controller-Based Small-Signal Stability Enhancement of Hybrid Microgrid Using the BCSSO Algorithm

Ensermu

Santhi

Merugu

et al. 2023

Journal of Electrical and Computer Engineering

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show abstract

“…Shahsavari et al [22] rendered a mathematical strategy for examining the high infiltration effects induced by the PV power plant on the SSS of a power network and for ameliorating the probabilistic SSS of the PS, utilizing the optimal Fractional Order (FO) PIDC. In this strategy, a Non-dominated Sorting GA (NSGA-II) type multi-objective optimization approach was employed for ascertaining the FO-PID stabilizer-centric parameters on the basis of two performance indices, such as Integral Square Error (ISE) and Integral Absolute Error (IAE).…”

Section: Literature Surveymentioning

confidence: 99%

Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Rojin¹,

Linda²

2022

Intelligent Automation &Amp; Soft Computing

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Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate such issues. The power is extracted from Renewable Energy Resources (RER), such as Photovoltaic (PV), Micro-Hydro (MH), and Wind Energy Conversation System (WECS). For tracking the power more efficiently, Maximum Power Point Tracking (MPPT) techniques are employed. Boost Converters (BC) are used and inverters are employed to convert DC to the AC. Here, the power flow is managed by the PIDC. If the Firing Angle (FA) is not properly determined, it results in instability and steady-state stability issues. To address this, the optimum tuning parameters are chosen for PIDC, by utilizing the MPSO. Finally, through experimentation analysis, the proposed system's performance is analyzed and compared with the existing algorithms and validated.

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Genetic Algorithm-Based Analysis of the Effects of an Additional Damping Controller for a Doubly Fed Induction Generator

Tan¹,

Tang

Sun³

et al. 2020

J. Electr. Eng. Technol.

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Optimal design of probabilistically robust PID controller to improve small signal stability of PV integrated power system

Cited by 9 publications

References 35 publications

An FRLQG Controller-Based Small-Signal Stability Enhancement of Hybrid Microgrid Using the BCSSO Algorithm

An FRLQG Controller-Based Small-Signal Stability Enhancement of Hybrid Microgrid Using the BCSSO Algorithm

Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Genetic Algorithm-Based Analysis of the Effects of an Additional Damping Controller for a Doubly Fed Induction Generator

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