Robust State Estimation Method for Adaptive Load Frequency Control of Interconnected Power System in a Restructured Environment

Aluko, Anuoluwapo; Carpanen, Rudiren Pillay; Dorrell, David G.; Ojo, Evans E.

doi:10.1109/jsyst.2020.3005979

Cited by 22 publications

(11 citation statements)

References 33 publications

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“…Frequency stability using improved FCSs when interconnecting multi-area power systems is the aim of many researchers. Thus [63,64,71,136] used simulations to demonstrate the efficacy of their hybrid type-2 fuzzy controllers and compared their proposed methods with type-1 fuzzy controllers. Aluko and his colleagues in [71] combine the UIO (Uknown Input Observer) with interval type-2 control to increase the stability and the unknown input aspect.…”

Section: Discussionmentioning

confidence: 99%

“…Thus [63,64,71,136] used simulations to demonstrate the efficacy of their hybrid type-2 fuzzy controllers and compared their proposed methods with type-1 fuzzy controllers. Aluko and his colleagues in [71] combine the UIO (Uknown Input Observer) with interval type-2 control to increase the stability and the unknown input aspect. They demonstrate in their work that the proposed type-2 FLC deals much better with undershoot frequency deviations than type-1 FLCs and PI controllers.…”

Section: Discussionmentioning

confidence: 99%

“…The proposed controller contrasted with conventional PI and Takagi-Sugeno probabilistic fuzzy controller [71] Type-2 fuzzy…”

Section: Software Implementation For Efficacy Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy Control Systems for Power Quality Improvement—A Systematic Review Exploring Their Efficacy and Efficiency

Miron,

Cziker,

Beleiu

2024

Applied Sciences

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Fuzzy-based control systems have demonstrated a remarkable ability to control nonlinear processes, a characteristic commonly observed in power systems, particularly in the context of power quality enhancement. Despite this, an updated and comprehensive literature review on the applications of fuzzy logic in the domain of power quality control has been lacking. To address this gap, this study critically examines published research on the effective and efficient use of fuzzy logic in resolving quality issues within power systems. Data sources included the Web of Science and academic journal databases, followed by an evaluation of target articles based on predefined criteria. The information was then classified into seven categories, including control system type, features of the fuzzy logic controller, fuzzy logic inference strategy, power quality issue, control device, implementation methodology (efficacy testing), and efficiency improvement. Our study revealed that fuzzy-based control systems have evolved from simple type-1 fuzzy controllers to advanced control systems (type-2 fuzzy and hybrid) capable of effectively addressing complex power quality issues. We believe that the insights gained from this study will be useful to both experienced and inexperienced researchers and industry engineers seeking to leverage fuzzy logic to enhance power quality control.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Fuzzy Control Systems for Power Quality Improvement—A Systematic Review Exploring Their Efficacy and Efficiency

Miron,

Cziker,

Beleiu

2024

Applied Sciences

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“…To design protective devices in the restructured power system, it is essential to take note of the short circuit or fault current in the connected network. The cost of the protective devices is also considered to accommodate any increase or decrease in the number of distribution generator units in the deregulated power system [20]. The estimation of unserved energy, evaluated through reliability indices, is taken into account when designing or modeling the distribution generator.…”

Section: Dimension and Rating Of Dgsmentioning

confidence: 99%

Fuzzy logic-based approach for optimal allocation of distributed generation in a restructured power system

Lindsay,

Emimal

2024

IJAPE

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Fuzzy logic emerges as a powerful tool for optimizing power flow solutions, particularly in the context of deregulated power systems. By employing fuzzy logic controls, the ideal placement of distribution generators (DGs) can be determined, ensuring the reliability indices are identified through optimal power flow solutions and fuzzy logic controllers to maintain system feasibility. In a deregulated power system, strategic placement of distribution generator units plays a crucial role in minimizing power loss and enhancing overall system performance by mitigating fluctuations. To identify areas of weakness, especially within transmission companies, accessing optimal power flow algorithms becomes essential in a deregulated power system. Both transmission and distribution networks should be appropriately adjusted to alleviate congestion within the respective companies. The aggregator must assess system performance, utilizing data obtained from distribution and transmission companies within the deregulated power system.

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“…Figure 1 illustrates how frequency controls are categorized according to the length and magnitude of frequency deviations. The four sections that make up frequency control levels are as [42,43]: primary control (droop control), secondary control (acting based on measurement of frequency change and power flow between areas), tertiary control (the system operator's use of various protection methods to reduce the magnitude of the frequency if the secondary control loop is not capable), and emergency control (continuous control to avoid blackouts, massive outages, or cascading failures in case of large disturbances) [44,45]. The shift from traditional synchronous generators to generators controlled by electronics for the integration of renewable energy sources results in a notable decrease in system inertia, which may present challenges to the stability and dependability of the system over an extended period of time.…”

Section: Load Frequency Controlmentioning

confidence: 99%

Analyzing Small-Signal Stability in a Multi-Source Single-Area Power System with a Load-Frequency Controller Coordinated with a Photovoltaic System

Shahgholian,

Fathollahi

2024

AppliedMath

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The frequency deviation from the nominal working frequency in power systems is a consequence of the imbalance between total electrical loads and the aggregate power supplied by production units. The sensitivity of energy system frequency to both minor and major load variations underscore the need for effective frequency load control mechanisms. In this paper, frequency load control in single-area power system with multi-source energy is analysed and simulated. Also, the effect of the photovoltaic system on the frequency deviation changes in the energy system is shown. In the single area energy system, the dynamics of thermal turbine with reheat, thermal turbine without reheat and hydro turbine are considered. The simulation results using Simulink/Matlab and model analysis using eigenvalue analysis show the dynamic behaviour of the power system in response to changes in the load.

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Robust State Estimation Method for Adaptive Load Frequency Control of Interconnected Power System in a Restructured Environment

Cited by 22 publications

References 33 publications

Fuzzy Control Systems for Power Quality Improvement—A Systematic Review Exploring Their Efficacy and Efficiency

Fuzzy Control Systems for Power Quality Improvement—A Systematic Review Exploring Their Efficacy and Efficiency

Fuzzy logic-based approach for optimal allocation of distributed generation in a restructured power system

Analyzing Small-Signal Stability in a Multi-Source Single-Area Power System with a Load-Frequency Controller Coordinated with a Photovoltaic System

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