Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Rojin, R. K.; Linda, M. Mary

doi:10.32604/iasc.2022.021834

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…per second for the responsive DR load. The parameter Toff of the ith appliances can be calculated in (19):…”

Section: H Demand Response Controllermentioning

confidence: 99%

“…However, the effectiveness of these controllers is contingent upon a properly designed network; otherwise, their performance may degrade [18]. Researchers employ population-based evolutionary computational intelligence approaches such as PSO [19], Fuzzy inference system [20], Manta Ray Foraging [21], and numerous other methods. The controller gain values obtained from the above classical method have improved MG system efficiency and robustness.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

Fadheel,

Wahab,

Manoharan

et al. 2024

IEEE Access

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This paper introduces a robust approach, integrating a Virtual Inertia Controller (VIC) with a modified demand response controller for an islanded Multi-Microgrid (MMG) system, accommodating high levels of Renewable Energy Sources (RESs). In these MGs, the low inertia in the system has an undesirable impact on the stability of MG frequency. As a result, it leads to a weakening of the MGs overall performance. A novel fractional derivative virtual inertia is integrated into the VIC loop to address this issue. This enhancement aims to fortify the MG's stability and robust performance, particularly when facing contingencies. Furthermore, a modified demand response controller has been incorporated into the proposed inertia control technique to mitigate the frequency fluctuations and reduce stress on the energy storage system (ESS). Fractional Order Proportional Integral Derivative (FOPID) controllers have been employed to regulate the active power output of the biodiesel generators and the Geothermal station in the MG. The hybrid sparrow search and mountain gazelle optimizer algorithm (SSAMGO) optimizes the parameters for the three-loop controller. Time-domain simulations assess the effectiveness of proposed controllers in enhancing system frequency stability. SSAMGO's performance was comprehensively evaluated, comparing it to various optimization algorithms in diverse scenarios. The results obtained from the MMG system demonstrate that utilizing the proposed controller technique, optimized with hybrid SSAMGO parameters, yields notable improvements in settling time by 24.68%, 46.20%, 7.52%, and 61.01%, steady-state error values by 72.56%, 98.18%, 98.73%, and 6.67%, undershoot by 105.76%, 144.23%, 19.23%, and 7.69% compared to other stateof-the-art algorithms presented in the literature. Finally, the proposed control technique's effectiveness and robustness are assessed in comparison to conventional inertia control across various system scenarios. These scenarios encompass random load demand fluctuations, real-time changes in RES, and a wide spectrum of system operations, including situations with reduced damping and inertia and high levels of load variation.INDEX TERMS Virtual inertia control, Load frequency control, Renewable energy resources, Hybrid optimization algorithm, Demand response control, Power system stability, Microgrid system.

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“…per second for the responsive DR load. The parameter Toff of the ith appliances can be calculated in (19):…”

Section: H Demand Response Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

Fadheel,

Wahab,

Manoharan

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Karimi and Jadid [23] have developed a multi-microgrid operation model with multiple-generation resources to address the issue of multi-objective management of energy in microgrid systems. Rojin and Linda [24] investigated the stability of microgrids caused by lowamplitude disturbances and proposed an improved particle swarm optimization algorithm to solve this problem. Reza et al [25] propose an innovative multi-tiered, microgrid-cluster, optimization framework that divides clustered microgrids into tiers using distribution networks and distribution systems for coordinated energy management based on demand.…”

Section: Introductionmentioning

confidence: 99%

Power Dispatching of Multi-Microgrid Based on Improved CS Aiming at Economic Optimization on Source-Network-Load-Storage

Wang

Zhao

et al. 2022

Electronics

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The multi-microgrid is gradually springing up with widespread use of the distributed generation. It is of great meaning to have research on the energy mutual optimization of the multi-microgrid to improve the new energy-consumption capacity. In this paper, a comprehensive economic model of the multi-microgrid is proposed for optimizing the power dispatching, and the source-network-load-storage is taken into account. Different from other studies, the special novelty of this paper is the improved cuckoo search (CS) algorithm which is adopted to optimize the power dispatching of the multi-microgrid. Comparing with the particle swarm optimization (PSO) algorithm, the improved CS algorithm has better performance in solving the proposed model. The optimal power supply strategy is determined by predicting the optimal state of charge of the battery in the model of the multi-microgrid. The model effectiveness of the multi-microgrid is confirmed in the case study of Wangjiazhai area. With this method, the optimal power dispatching is determined.

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Probabilistic Robust Damping Controller Optimization for Mitigating Subsynchronous Control Interaction in DFIG and PMSG‐Based Wind Farms

Bodapatla,

Ghodake,

Kadam

et al. 2024

Optim Control Appl Methods

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Advanced control and mitigation solutions are required due to the enormous challenges posed by sub‐synchronous control interaction in wind farms. These concerns include system instability, potential damage to turbines, and grid stability issues. This research presents the probabilistic robust damping controller, an adaptive control approach, to address the issues in grid‐connected wind farms. The innovation employs the balanced remora optimization algorithm to optimize controller parameters, ensuring system stability under various conditions. For permanent magnet synchronous generator‐based wind farms with weak grid circumstances, critical elements such as the DC‐link voltage, the d‐q axis current reference, and the actual values in the grid‐side converter are essential for problem mitigation. The controller generates controlled output using these input signals. The MATLAB‐based implementation demonstrates the controller effectiveness in damping issues within a series‐compensated doubly fed induction generator. Comparative analysis with conventional controllers under different grid conditions and disturbances validates its superior performance. Time‐domain simulations, both with and without time delay, further confirm the controller's ability to enhance system stability and dampen the issues. Four schemes are used to evaluate the doubly fed induction generator‐based wind farms: wind speed at 13 m/s with 75% series compensation, 7 m/s with 75% compensation, 9 m/s with 45% compensation, and 9 m/s with 60% compensation. Under short circuit ratio, the wind farms based on permanent magnet synchronous generators are analyzed in three scenarios: normal, strong, and weak cases.

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Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Cited by 6 publications

References 28 publications

A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System

Power Dispatching of Multi-Microgrid Based on Improved CS Aiming at Economic Optimization on Source-Network-Load-Storage

Probabilistic Robust Damping Controller Optimization for Mitigating Subsynchronous Control Interaction in DFIG and PMSG‐Based Wind Farms

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