Tuning of Controllers in Power Systems Using a Heuristic-Stochastic Approach

Verdejo, Humberto; Torres, Rodrigo; Pino, Victor; Kliemann, Wolfgang; Becker, Cristhian; Delpiano, José

doi:10.3390/en12122325

Cited by 9 publications

(8 citation statements)

References 44 publications

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“…It uses artificial intelligence via adaptive memory and iterative methods to solve the given problem. In [146], this algorithm is used for tuning PSS controllers in a three-machine nine-bus system. For effective damping, all parameters must be precisely tuned.…”

Section: Tabu Search Algorithm (Ts)mentioning

confidence: 99%

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

et al. 2022

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Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

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Section: Tabu Search Algorithm (Ts)mentioning

confidence: 99%

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

et al. 2022

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“…The PSS-SCA system had the shortest damping time, approximately 1.8 s, and the smallest oscillation rate and damping performance of the SMIB system compared with those of the other approaches. PSS-MFO and PSS-EP followed with damping before 1.9 s and then PSS-U with damping before 5 s. The PSS-EP system required the fewest iterations (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) to converge on the minimum value objective function compared with those needed by the other approaches. The PSS-SCA and PSS-MFO systems required 75-150 iterations to converge on the solutions.…”

Section: List Of Parametersmentioning

confidence: 99%

“…The particle swarm optimization (PSO) algorithm was used to design a damping controller [5,24,25], as were cuckoo and BAT optimization algorithms [26,27]. The firefly optimization algorithm was used to design an SVC damping controller [28,29]. Various heuristic algorithms for optimization have used stochastic methods that have deficiencies in solution convergence.…”

Section: Introductionmentioning

confidence: 99%

Design of a Damping Controller Using the SCA Optimization Technique for the Improvement of Small Signal Stability of a Single Machine Connected to an Infinite Bus System

2021

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This paper discusses the use of a stochastic metaheuristic population-based optimization algorithm known as the sine cosine algorithm (SCA) to design the parameters of a power system stabilizer (PSS) for damping electromechanical oscillations in a single machine connected to a large power system. The design of the PSS parameters was formulated as an optimization problem to minimize the objective function value. The SCA was used to obtain the best values of the PSS parameters under the objective function. Simulation was carried out by a linearized power system model. The lead lag controller was used as the PSS structure and the results from that were compared with those obtained by moth flame optimization and evolutionary programming. The results showed that the SCA is more effective than are the other techniques in exploration and exploitation to tune the PSS parameters and enhance the power system stability by damping oscillations in a range of loading conditions.

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“…However, the arrangement of the system operating points changes, which necessitates a proportional change in the PSS’s parameters in order to maintain the best system operation (Butti et al, 2020). Therefore, the success of the entire PSS design depends on the tuning stage (Gurung et al, 2019; Rana et al, 2019; Verdejo et al, 2019). Thus, it has become a milestone work for an electrical engineer to achieve a reasonable level of robust conventional PSSs based on the parameters tuning methodology.…”

Section: Introductionmentioning

confidence: 99%

Application of a neuro-fuzzy controller for single machine infinite bus power system to damp low-frequency oscillations

Sabo

Wahab

Othman

et al. 2021

Transactions of the Institute of Measurement and Control

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Generally, power systems experience a variety of disturbances that can result in low frequency electromechanical oscillations. These low frequency oscillations (LFOs) take place among the rotors of synchronous generators connected to the power system. These oscillations may sustain and grow to cause system separation if no adequate damping is provided. Power system stabilizers (PSSs) are one of the alternative devices used to solve this rotor oscillation problem. The major limitation of using PSSs at the excitation system of synchronous machine is that the conventional PSS is a permanent parameter type operating under a particular system operating condition, and its parameters are acquired through trial and error. An efficient way of operating the PSS has been by designing the PSS parameters using a powerful optimization procedure. However, designing PSS damping controller is a cumbersome task as it needs a comprehensive test system modeling and a heavy computational burden on the system. In this research, a novel, model-free neuro-fuzzy controller (NFC) is designed as the LFOs’ damping controller to substitute the traditional PSS system making the power system simple without complications in PSS design and parameter optimization. The proposed controller application implements the LFOs’ control without a linearized mathematical model of the system, as such it makes the system less complex and bulky. Single machine infinite bus (SMIB) test system was simulated in SIMULINK domain with the PSSs and with the proposed controller to compare the NFC effectiveness. The simulation outcome for the eigenvalue study with NFC stabilizer yields steady eigenvalues that enhanced the damping status of the system greater than 0.1 with decreased overshoots and time to rise via the proposed NFC process than with the conventional FFA-PSS. Similarly, the generator transient reaction also presents the ω and δ based on the time to settle was improved by 64.66% and 28.78%, respectively, via the proposed NFC process than with the conventional FFA-PSS. Finally, the conventional PSS was found to be complicated in its design, parameter optimization and less effective than the proposed controller for the LFOs’ control.

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Tuning of Controllers in Power Systems Using a Heuristic-Stochastic Approach

Cited by 9 publications

References 44 publications

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Design of a Damping Controller Using the SCA Optimization Technique for the Improvement of Small Signal Stability of a Single Machine Connected to an Infinite Bus System

Application of a neuro-fuzzy controller for single machine infinite bus power system to damp low-frequency oscillations

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