Abstract:This work suggests a type-2 fuzzy lead–lag (T2FLL) controller structure for flexible AC transmission system (FACTS)-based damping controllers and power system stabilizers (PSSs) for power system stability improvement. The values of the suggested controller are optimized by a hybrid adaptive differential evolution and pattern search algorithm (hADE-PS) method. Initially, a single-machine infinite-bus (SMIB) system with lead–lag (LL)-structured FACTS and PSS controllers is considered, and the dominance of the hA… Show more
“…However, this combination of damping controllers needs precision; otherwise, the entire power system stability may be negatively affected [118,119]. The collaborative design of PSS and FACTS has been the subject of numerous studies [120][121][122][123][124].…”
Section: Facts-based Dampingmentioning
confidence: 99%
“…However, this combination of damping controllers needs precision; otherwise, the entire power system stability may be negatively affected [117,118]. The collaborative design of PSS and FACTS has been the subject of numerous studies [119][120][121][122][123]. Designing a reliable damping scheme to address oscillations is the goal of damping controller coordination schemes.…”
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.
“…However, this combination of damping controllers needs precision; otherwise, the entire power system stability may be negatively affected [118,119]. The collaborative design of PSS and FACTS has been the subject of numerous studies [120][121][122][123][124].…”
Section: Facts-based Dampingmentioning
confidence: 99%
“…However, this combination of damping controllers needs precision; otherwise, the entire power system stability may be negatively affected [117,118]. The collaborative design of PSS and FACTS has been the subject of numerous studies [119][120][121][122][123]. Designing a reliable damping scheme to address oscillations is the goal of damping controller coordination schemes.…”
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.
“…The author analyses the coordinated structure of SSSC and PSS using the ACO technique [31]. The author investigates the coordinated SSSC and PSS design using a hybrid technique [32]. In [33,34], the author discussed simultaneous tuning of PSS and SSSC controllers using modified SCA.…”
The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control to augment with an automatic voltage regulator (AVR) supplemental feedback stabilizing signal. This paper proposes a new strategy for simultaneously tuning the power system stabilizer (PSS) and FACTS controller, considering time delays. The design of the proposed controller is modeled as an optimization problem, and the parameters of the controller are optimized through the grasshopper optimization algorithm (GOA). The suggested controller’s efficacy is evaluated for both single-machine infinite bus systems and multi-machine power systems under various disturbances. It also investigated the performance of the proposed controller with variations in signal transmission delays. The results obtained from GOA optimized proposed controller are compared with those obtained from the differential evolution algorithm, genetic algorithm, and whale optimization algorithm. In this context, the proposed GOA optimized controller reduced the objective function value by 16.32%, 14.56%, and 13.72%, respectively, in the SMIB system and 1.41%, 9.98%, and 13.31%, respectively, for the multi-machine system compared with the recently published WOA, and the well-established GA and DE. Further, the proposed controller is found to be stable and effectively increases stability even under small disturbances.
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