Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm

Alattar, Alhassan H.M.; Selem, Sameh I.; Metwally, Hamid; Ibrahim, Аhmed; Aboelsaud, Raef; Tolba, Mohamed A.; El-Rifaie, Ali M.

doi:10.3390/en12163110

Cited by 18 publications

(10 citation statements)

References 52 publications

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“…where y i -actual wind speed data characteristic, f i -simulated wind speed characteristic. Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) are used to compare the models [30,31]:…”

Section: Model Validation and Resultsmentioning

confidence: 99%

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Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

et al. 2021

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The primary task of the design and feasibility study for the use of wind power plants is to predict changes in wind speeds at the site of power system installation. The stochastic nature of the wind and spatio-temporal variability explains the high complexity of this problem, associated with finding the best mathematical modeling which satisfies the best solution for this problem. In the known discrete models based on Markov chains, the autoregressive-moving average does not allow variance in the time step, which does not allow their use for simulation of operating modes of wind turbines and wind energy systems. The article proposes and tests a SDE-based model for generating synthetic wind speed data using the stochastic differential equation of the fractional Ornstein-Uhlenbeck process with periodic function of long-run mean. The model allows generating wind speed trajectories with a given autocorrelation, required statistical distribution and provides the incorporation of daily and seasonal variations. Compared to the standard Ornstein-Uhlenbeck process driven by ordinary Brownian motion, the fractional model used in this study allows one to generate synthetic wind speed trajectories which autocorrelation function decays according to a power law that more closely matches the hourly autocorrelation of actual data. In order to demonstrate the capabilities of this model, a number of simulations were carried out using model parameters estimated from actual observation data of wind speed collected at 518 weather stations located throughout Russia.

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Section: Model Validation and Resultsmentioning

confidence: 99%

“…Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) are used to compare the models [30,31]:…”

Section: Model Validation and Resultsmentioning

confidence: 99%

Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

et al. 2021

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“…The sine cosine technique (SCT) based cascade proportional-derivative with PID (PD-PID) controller method has presented in [18] for frequency regulation of renewable wind-diesel-fuel cell-battery based microgrid. The work in [19] presented PID control structure to strengthen the frequency stabilization of wind-super conducting magnetic energy (SMES) storage-nonrenewable diesel units based microgrid network.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid

et al. 2021

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It is known that keeping the power balance between generation and demand is crucial in containing the system frequency within acceptable limits. This is especially important for renewable based distributed hybrid microgrid (DHμG) systems where deviations are more likely to occur. In order to address these issues, this article develops a prominent dual-level “proportional-integral-one plus double derivative {PI−(1 + DD)} controller” as a new controller for frequency control (FC) of DHμG system. The proposed control approach has been tested in DHμG system that consists of wind, tide and biodiesel generators as well as hybrid plug-in electric vehicle and an electric heater. The performance of the modified controller is tested by comparing it with standard proportional-integral (PI) and classical PID (CPID) controllers considering two test scenarios. Further, a recently developed mine blast technique (MBA) is utilized to optimize the parameters of the newly designed {PI − (1 + DD)} controller. The controller’s performance results are compared with cases where particle swarm optimization (PSO) and firefly (FF) techniques are used as benchmarks. The superiority of the MBA-{PI − (1 + DD)} controller in comparison to other two strategies is illustrated by comparing performance parameters such as maximum frequency overshoot, maximum frequency undershoot and stabilization time. The displayed comparative objective function (J) and JFOD index also shows the supremacy of the proposed controller. With this MBA optimized {PI − (1 + DD)} controller, frequency deviations can be kept within acceptable limits even with high renewable energy penetration.

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“…Wind and super conducting magnetic energy systems are incorporated with non-renewable sources like diesel power plants to study and analyse the frequency regulation of hybrid power system using a PID controller. In this research, a controller's gain values are tuned by utilizing mine blast technique (MBA) [20].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Two-Stage IPD-(1+I) Controllers for Frequency Regulation of Sustainable Energy Based Hybrid Microgrid Network

et al. 2021

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Sustainable energy based hybrid microgrids are advantageous in meeting constantly increasing energy demands. Conversely, the intermittent nature of renewable sources represents the main challenge to achieving a reliable supply. Hence, load frequency regulation by adjusting the amount of power shared between subsystems is considered as a promising research field. Therefore, this paper presents a new stratagem for frequency regulation by developing a novel two stage integral-proportional-derivative with one plus integral (IPD-(1+I)) controller for multi sources islanded microgrid system (MS-IμGS). The proposed stratagem has been tested in an MS-IμGS comprising of a wind turbine, parabolic trough, biodiesel generators, solid-oxide fuel cell, and electric water heater. The proposed model under different scenarios is simulated in MATLAB environment considering the real-time recorded wind data. A recently developed sine-cosine algorithmic technique (SCA) has been leveraged for optimal regulation of frequency in the considered microgrid. To identify the supremacy of the proposed technique, comparative studies with other classical controllers with different optimization techniques have been performed. From the comparison, it is clearly evident that, SCA-(IPD-(1+I)) controller gives better performance over other considered stratagems in terms of various time domain specific parameters, such as peak deviations (overshoot, undershoot) and settling time. Finally, the robustness of the proposed stratagem is evaluated by conducting sensitivity analysis under ±30% parametric variations and +30% load demand. The lab tests results validate the operation of the proposed system and show that it can be used to regulate the frequency in stand-alone microgrids with a high penetration of renewable energy.

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Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm

Cited by 18 publications

References 52 publications

Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid

Optimization of Two-Stage IPD-(1+I) Controllers for Frequency Regulation of Sustainable Energy Based Hybrid Microgrid Network

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