Real Time Simulation for Load Frequency Control of Multisource Microgrid System Using Grey Wolf Optimization Based Modified Bias Coefficient Diagram Method (GWO-MBCDM) Controller

Kumar, Badal; Adhikari, Shuma; Datta, Subir; Sinha, Nidul

doi:10.1007/s42835-020-00596-2

Cited by 18 publications

(4 citation statements)

References 27 publications

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“…Here, to bring the responses closer to reality, some nonlinear elements are also applied in the MG modeling. The validity of the models used in this paper has been confirmed in past related studies through real-time tests [4,30]. The general scheme of the non-identical two-zone system under study is depicted in Figure 1.…”

Section: System Modelingsupporting

confidence: 61%

Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects

et al. 2022

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Because of the lack of upstream grid support and low inertia, independent microgrids are very susceptible to load variations and uncertainty in the generation of renewable energy sources. Disruption of microgrid frequency stability causes severe damage to various system equipment and frequency-sensitive loads. By taking into account the effects of electric vehicles (EVs), this paper introduces an innovative control strategy with a master-slave configuration for frequency control of interconnected microgrids. In the proposed configuration, an integer-order controller serves as the master, while a merely fractional-order integrator acts as the slave controller. The master and slave controllers are concurrently optimized by the JAYA intelligent algorithm to achieve robust effectiveness. Additionally, nonlinearities in the system are implemented, such as diesel generator operating limits, signal controllers, and sending/receiving time delays. To assess the effectiveness of the proposed control strategy in a two-area microgrid, six basic scenarios are investigated: sudden load changes, perturbations at the inputs of renewable energy-based units, parametric uncertainties, time-delay effects as a nonlinear factor, complicated working conditions, and EVs impacts. Moreover, the controller’s performance on a simple closed-loop system has been carried out in order to confirm the viability of its practical implementation, and a comparison of experimental and simulation findings has also been provided. Studies demonstrate the proposed controller’s robustness as well as its fast-response capability. Besides, this controller features a simple structure that allows extra design flexibility.

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Section: System Modelingsupporting

confidence: 61%

Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects

et al. 2022

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“…The disturbance in the power system and load caused by changeable solar and thermal is also decreased with this technology. The Coefficient Diagram Method [42,43,44,45] is an algebraic approach for analyzing polynomial loops in the power system. The CDM approach gives information on the systems stability condition.…”

Section: Load Frequency Control Using Coefficient Diagram Methodsmentioning

confidence: 99%

An overview of load frequency control for grid using various control techniques

Vinitha¹,

Rani²

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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Nowadays Electrical power generation using renewable energy systems brings more novel ideas to satisfy the power demand worldwide. Microgrid is one of the ideas that ensures stability and reliability of the power system. Due to seasonal or climatic effect, the power generated by the renewable energy sources has issue in providing a constant power output and hence produces the power imbalance between the source to load. Furthermore, the system frequency cannot be kept constant in all cases. In this case, an electric vehicle (EV) can serve as a power generation source to support the power grid and meet the Load Frequency Control requirement (LFC). Due to their fast-regulating characteristics, electric vehicles provide frequency regulation services. Electric vehicles are used in both primary and secondary frequency management in power systems to quickly suppress frequency oscillations caused by changes in load. The control centre gathers and updates real-time Electric Vehicle data, such as information regarding state of charge and the state of each Electric Vehicle, in order to decide on load frequency regulation dispatch to Electric Vehicles. This paper compares and consolidate the performance of Load frequency control through Conventional plants and Renewable energy systems. The graphical abstract of power system grid is shown in Figure.1

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“…The schematic and the transfer function modeling of the proposed HPS using different generations and energy storage is presented in Figures 2 and 3 respectively. The nominal electrical specifications of all the components are taken from Kumar et al 28 with a base load of 700 kW (1 pu). The rated output powers of PV and WTG are taken as 300 and 400 kW, respectively.…”

Section: Details Of Hpsmentioning

confidence: 99%

Sine cosine adopted Harris' hawks optimization for function optimization and power system frequency controller design

Mohanty

Panda

2021

Int Trans Electr Energ Syst

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Summary A considerable number of intermittent renewable resources like photovoltaic generation and wind energy when integrated into the conventional grid technology causes serious issues in the power systems like frequency instability. So an intelligent controller is desired for steady and reliable operation of the electric grid. This paper deals with the frequency control of hybrid power system (HPS) employing a sine cosine adopted Harris' hawks optimization (SCaHHO) technique. The proposed technique aims at improving the performance of the original Harris' hawks optimization (HHO) algorithm by incorporating a sine and cosine function in the calculation of escaping energy and chances of escaping of prey respectively to emphasize the exploitation process of hawks. The effectiveness of the SCaHHO technique is validated with the novel HHO technique as well as moth flame optimization, sine cosine algorithm, grey wolf optimization, salp swarm algorithm and gravitational search algorithm using 23 standard test functions. A non‐parametric statistical investigation is also carried out to verify the effectiveness of the suggested technique. Later the SCaHHO technique is utilized to tune a newly proposed adaptive fuzzy proportional integral derivative controller (AFPID) for frequency control of HPS. The suggested SCaHHO‐tuned AFPID controller achieves an improved control action by moderating the frequency fluctuations as compared to the PID controller. Hardware‐in‐loop validation of the proposed load frequency control scheme is also carried out using OPAL‐RT to measure its fidelity with the numerical simulation results.

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Real Time Simulation for Load Frequency Control of Multisource Microgrid System Using Grey Wolf Optimization Based Modified Bias Coefficient Diagram Method (GWO-MBCDM) Controller

Cited by 18 publications

References 27 publications

Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects

Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects

An overview of load frequency control for grid using various control techniques

Sine cosine adopted Harris' hawks optimization for function optimization and power system frequency controller design

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