Analysis of LFC in PV‐thermal‐thermal interconnected power system using fuzzy gain scheduling

Revathi, D.; Kumar, G. Mohan

doi:10.1002/2050-7038.12336

Cited by 23 publications

(8 citation statements)

References 24 publications

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“…Then the cluster center formed from the real part of "g" pairs is calculated from Equation (10) and the imaginary part is calculated from Equation (11). The newly obtained real and imaginary parts of the complex reduced-order pole are combined to form the reduced-order denominator as shown by Equation (12).…”

Section: Obtaining Rommentioning

confidence: 99%

“…But due to frequent repetitions to find the optimized solution, these techniques were seen to exhibit large computation time, stagnation and more sensitive nature for its parameters. The robust fuzzy controllers [10][11][12] regulated the frequency and tie line of the power system in a more efficient manner by eliminating all complexities, because the fuzzy controllers do not depend on the system structure. The design of fuzzy controller depends on the design engineer completely.…”

Section: Introductionmentioning

confidence: 99%

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Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Gupta

Manocha

2021

Int Trans Electr Energ Syst

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Section: Obtaining Rommentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Gupta

Manocha

2021

Int Trans Electr Energ Syst

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“…The governor of the generators provides necessary adjustments of frequency. The area control error (ACE) as a linear combination of tie‐line power interchange and frequency deviation is continuously measured and regulated to be near zero 3 . Due to the practical limitations on the governors, supplementary regulators in the form of PIDs are used to obtain a safe frequency regulation.…”

Section: Introductionmentioning

confidence: 99%

Improving frequency regulation of wind‐integrated multi‐area systems using LFA‐fuzzy PID control

Kheshti

Ding

Abyaneh

et al. 2021

Int Trans Electr Energ Syst

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Summary Due to the complexity and importance of the electricity grid stability, sophisticated control systems and computational approaches are essentially required to solve dynamical system frequency problems in multi‐area systems. Participation of wind turbines in power system frequency control in the form of stepwise inertial control in the presence of a proposed adequately tuned fuzzy‐PID load‐frequency control is investigated in this paper. A two‐area power system is studied in which it is linked through tie‐line and equipped with fuzzy‐PID control systems. To increase the energy transition and flexibility of the entire system against frequency events and parameters uncertainties, the fuzzy‐PID controllers are first tuned using lightning flash algorithm (LFA). The tuned controllers are then used in each area to optimally counterbalance the frequency deviations and the tie‐line power of the interconnected areas against varying load disturbances, wind power fluctuations, and to keep the renewable integrated system in a stable state. The sensitivity analysis is also conducted with a wide range of system parameter variations, uncertainties, and disturbances. Furthermore, the LFA‐tuned fuzzy‐PID load‐frequency control is also tested in a two‐area isolated microgrid, comprising wind turbine, PV panels, fuel cells, micro‐turbine, and diesel engine generator. The results obtained using the proposed approach are compared with other state‐of‐the‐arts algorithms and control systems in the literature. The compared results show the efficiency and robustness of the proposed optimization‐based controller for better frequency control in multi‐area power systems and isolated microgrids. The results also demonstrate that a finely tuned automatic generation controller gives a significant boost to grid frequency control when wind turbines participate in the inertial control, suggesting migration from conventional PID‐based automatic generation control to more adaptive control approaches.

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“…In addition, the superiority of FLC-PI over GA-based PI (GA-PI) and firefly-based PI (FA-PI) was demonstrated by comparison of results. In Revathi and Mohan Kumar (2020), fuzzy logic-based PI controller was proposed for load frequency control of PV-thermal-thermal interconnected power system. The fuzzy-PI (F-PI) control performance on power system was compared with the conventional PI controller and the superiority of the F-PI was observed.…”

Section: Introductionmentioning

confidence: 99%

Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energy sources based on multi-objective grasshopper optimization algorithm

Tabak

2021

Transactions of the Institute of Measurement and Control

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In recent years, fractional order proportional-integral-derivative (FOPID) controllers have been applied in different areas in the academy due to their superior performance over conventional proportional-integral-derivative (PID) controllers. When the literature is reviewed, it has been observed that lack of studies that use swarm-based and multi-objective optimization algorithms together with FOPID controllers in frequency control of micro-grid. The load frequency control (LFC) problem is considered as two objectives in order to eliminate the complications that occur when only the frequency deviation is minimized. In our study, a method called MOGOA-FOPID in which both the frequency deviation and the control signal are minimized together for the frequency control in the microgrid is proposed. By using the multi-objective grasshopper optimization algorithm (MOGOA), both the frequency deviation and the control signal are minimized together, and thus, it is aimed to limit the battery capacity, reduce the flywheel jerk and avoid high diesel fuel consumption as well as an effective frequency control. In order to obtain a more realistic system, not only the photovoltaic (PV) solar and wind power but also the load demand is taken in a stochastic structure. Then, the results of the proposed MOGOA-FOPID are compared with the results of multi-objective genetic algorithm (MOGA)-based PID/FOPID and MOGOA-PID and its superiority is demonstrated. Finally, robustness tests of the system are performed under the perturbed parameters and outperform of MOGOA-FOPID over other methods is seen.

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Analysis of LFC in PV‐thermal‐thermal interconnected power system using fuzzy gain scheduling

Cited by 23 publications

References 24 publications

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Designing of 2‐degree of freedom load frequency controller for power system using novel improved pole clustering and genetic method of reduced‐order modelling

Improving frequency regulation of wind‐integrated multi‐area systems using LFA‐fuzzy PID control

Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energy sources based on multi-objective grasshopper optimization algorithm

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