The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

Shouran, Mokhtar; Anayi, Fatih; Packianather, Michael

doi:10.3390/en14185701

Cited by 24 publications

(6 citation statements)

References 38 publications

(59 reference statements)

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“…Several researchers optimally tuned the proposed controller (SMC, ASTSMC, ISMC, …., etc.) by an optimization algorithm such as Hybridized gravitational search algorithm, Artificial Bee Colony, and Bees Algorithm [16][17][18]. In ref.…”

Section: Literature Surveymentioning

confidence: 99%

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

Elsaied

Hameed

Hasanien

et al. 2023

IET Renewable Power Gen

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The constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices.

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Section: Literature Surveymentioning

confidence: 99%

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

Elsaied

Hameed

Hasanien

et al. 2023

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Shouran et al [21] in their paper suggested a Sliding Mode Control (SMC) concept for Load Frequency Control (LFC) in a two-area electrical power system. Depending on the researched system's properties, the mathematical model design for the SMC is generated.…”

Section: Literature Surveymentioning

confidence: 99%

Load Frequency Control in Renewable Energy Penetrated Hybrid Power Systems

Koley,

Datta,

Panda

2023

JNMES

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In order to ensure zero steady-state error in multi-area hybrid power systems, load frequency control is implemented in the power system. However, variations in load due to cyclic amplitude deviation create frequency fault leading to unscheduled tie-line power. Hence a novelOperational Load Forecasting Approach is utilized in which objective function in support vector regression predicts load demand and generation based on temporalcharacteristicsand utilize parallel processing to tolerate the acceptable error margin.Moreover, the uncertainties of active power generation in islanding mode make the estimation of frequency response deviation under decentralized islanding modes difficult. Hence a novelDifferential ControllerAlgorithm has been proposed in which the sigmoidal range function determines the optimal amplitude value from individual areasand the controller predicts the high load demand area that exceeds the threshold limit and isolatesthat area until the deviation is rectified. Low tie-line power, frequency, and settling time deviations were accomplished using the proposed methodologies as they were simulated using the Simulink platform.

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“…Currently, rising energy demand and the depletion of fossil fuel resources have necessitated the extensive use of Renewable Energy (RE), which is considered clean and cost-effective, and likely to be connected to interconnected power systems for distributed utilization [1]. The integration of RE such as solar and wind leads to an uncertain variation in the generation of power due to the intermittent nature of RE, which introduces frequency oscillation that leads to multiple protection relays trip in the power system [2]. Automatic Load Frequency Control (ALFC) has proven very effective in regulating the system frequency by adjusting the generation system.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Grey Wolf Assisted-Sparrow Search Algorithm for Frequency Control of RE Integrated System

et al. 2023

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Nowadays, renewable energy (RE) sources are heavily integrated into the power system due to the deregulation of the energy market along with environmental and economic benefits. The intermittent nature of RE and the stochastic behavior of loads create frequency aberrations in interconnected hybrid power systems (HPS). This paper attempts to develop an optimization technique to tune the controller optimally to regulate frequency. A hybrid Sparrow Search Algorithm-Grey Wolf Optimizer (SSAGWO) is proposed to optimize the gain values of the proportional integral derivative controller. The proposed algorithm helps to improve the original algorithms’ exploration and exploitation. The optimization technique is coded in MATLAB and applied for frequency regulation of a two-area HPS developed in Simulink. The efficacy of the proffered hybrid SSAGWO is first assessed on standard benchmark functions and then applied to the frequency control of the HPS model. The results obtained from the multi-area multi-source HPS demonstrate that the proposed hybrid SSAGWO optimized PID controller performs significantly by 53%, 60%, 20%, and 70% in terms of settling time, peak undershoot, control effort, and steady-state error values, respectively, than other state-of-the-art algorithms presented in the literature. The robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameters, and weather intermittency of RE resources in real-time conditions. Furthermore, the controller’s efficacy was also demonstrated by performing a sensitivity analysis of the proposed system with variations of 75% and 125% in the inertia constant and system loading, respectively, from the nominal values. The results show that the proposed technique damped out the transient oscillations with minimum settling time. Moreover, the stability of the system is analyzed in the frequency domain using Bode analysis.

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The Bees Algorithm Tuned Sliding Mode Control for Load Frequency Control in Two-Area Power System

Cited by 24 publications

References 38 publications

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

Load Frequency Control in Renewable Energy Penetrated Hybrid Power Systems

A Hybrid Grey Wolf Assisted-Sparrow Search Algorithm for Frequency Control of RE Integrated System

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