A hybrid
            <scp>RFCRO</scp>
            approach for the energy management of the grid connected microgrid system

Roy, Kallol; Mandal, Kamal Krishna; Mandal, Atis Chandra

doi:10.1002/2050-7038.12660

Cited by 14 publications

(5 citation statements)

References 37 publications

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“…This system efficiently manages thermal, gas, and electrical systems on different time scales, enhancing microgrid operation and interactions among energy sources. Roy et al [9] introduced the RFCRO hybrid algorithm, combining random forest and coral reefs optimization, to optimize energy flow management in grid-connected microgrids. The algorithm targeted cost reductions by optimizing multiple fitness functions simultaneously, showcasing the potential of hybrid techniques for efficient microgrid power flow management.…”

Section: Introduction 1problem Statement and Motivationmentioning

confidence: 99%

A Novel Hybrid Imperialist Competitive Algorithm–Particle Swarm Optimization Metaheuristic Optimization Algorithm for Cost-Effective Energy Management in Multi-Source Residential Microgrids

Charadi,

Chakir,

Redouane

et al. 2023

Energies

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The integration of renewable sources and energy storage in residential microgrids offers energy efficiency and emission reduction potential. Effective energy management is vital for optimizing resources and lowering costs. In this paper, we propose a novel approach, combining the imperialist competitive algorithm (ICA) with particle swarm optimization (PSO) as ICA-PSO to enhance energy management. The proposed energy management system operates in an offline mode, anticipating data for the upcoming 24 h, including consumption predictions, tariff rates, and meteorological data. This anticipatory approach facilitates optimal power distribution among the various connected sources within the microgrid. The performance of the proposed hybrid ICA-PSO algorithm is evaluated by comparing it with three selected benchmark algorithms, namely the genetic algorithm (GA), ICA, and PSO. This comparison aims to assess the effectiveness of the ICA-PSO algorithm in optimizing energy management in multi-source residential microgrids. The simulation results, obtained using Matlab 2023a, provide clear evidence of the effectiveness of the hybrid ICA-PSO algorithm in achieving optimal power flows and delivering substantial cost savings. The hybrid algorithm outperforms the benchmark algorithms with cost reductions of 4.47%, 14.93%, and 26% compared to ICA, PSO, and GA, respectively. Furthermore, it achieves a remarkable participation rate of 50.6% for renewable resources in the energy mix, surpassing the participation levels of the ICA (42.88%), PSO (40.51%), and GA (38.95%). This research contributes to the advancement of power flow management techniques in the context of multi-source residential microgrids, paving the way for further research and development in this field.

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Section: Introduction 1problem Statement and Motivationmentioning

confidence: 99%

A Novel Hybrid Imperialist Competitive Algorithm–Particle Swarm Optimization Metaheuristic Optimization Algorithm for Cost-Effective Energy Management in Multi-Source Residential Microgrids

Charadi,

Chakir,

Redouane

et al. 2023

Energies

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“…7,8 To reduce the harmonics, a control approach for single phase inverters along with active harmonic filtering is used. 9,10 Researchers have discovered dissimilar approaches like linear approximation, 11 conical formulation, 12 semi-definite programming, 13 F I G U R E 2 Active and reactive power control with proposed methodology Quadratic Convex Relaxation, 14 and decomposition 15 are established for quicker solution. A comprehensive study of inaccurate convex relaxation on the viability of AC-OPF is provided.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a closed loop (CL) power control mode is essential to precise electrical monitoring the events of deformed voltages on PCC 7,8 . To reduce the harmonics, a control approach for single phase inverters along with active harmonic filtering is used 9,10 …”

Section: Introductionmentioning

confidence: 99%

A hybrid approach for enhancing and optimizing the power quality and power flow in Smart Grid Connected System

Dsouza

Ananthapadmanabha

2022

Systems Engineering

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This article proposes a hybrid approach for power flow management and power quality (PQ) improvement in smart grid (SG) system. The proposed methodology is designed into two phases, power flow management is the first stage and power quality improvement is the second stage of the system. The key purpose of the proposed method is “to regulate that power flow depends on variation of source and load side parameters deliver the highest PQ.” The initial phase of power flow management is executed by using Improved Binary Sailfish Optimizer (IBSFO) approach. The control signal is recognized by the IBSFO approach against active and reactive power variation. The second phase of power quality enhancement is implemented by K2ORBFNN, which is the combination of Kho‐Kho optimization (KKO) and Radial Basis Function Neural Network (RBFNN). The gain parameter of the proportional integral (PI) controller is tuned based on load current, DC link, and voltage sources using K2ORBFNN approach. The prediction of optimal control signal minimizes the error which is obtained by RBFNN approach. The proposed method is utilized to attain compensating non‐linear load current harmonics, compensating reactive load power requirement, compensating unbalanced load current with neutral current. Finally, the performance of proposed system is executed in the MATLAB platform and performance is compared with existing techniques. The efficiency under the trails of 100, 200, 500, and 1000 attains 99.1673%, 99.4567%, 99.8402%, and 99.9879%.

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“…Such microgrid systems are presented in literature to operate in grid-connected mode. [27][28][29][30][31][32][33] In References 27-29, a gridconnected community-based microgrid is presented. The system is implemented to minimize the COE.…”

Section: Introductionmentioning

confidence: 99%

Optimal selection of renewable energy–based microgrid for sustainable energy supply

Sarwar

Warsi

Siddiqui

et al. 2021

Intl J of Energy Research

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Escalation in electricity consumption and environmental pollution worldwide necessitates the need for alternative and sustainable energy sources other than conventional sources. Therefore, in this article, renewable energy-based microgrid is presented to cater such needs. Different feasible microgrid topologies are determined and analyzed to meet the demand of the proposed site. The feasibility evaluation of the different microgrid configurations is performed based on the cost factors and carbon dioxide (CO 2 ) emissions. The optimum configuration is selected based on the minimum cost of annual operating charges, annual energy charges and annual social cost of CO 2 emissions taken altogether. Besides this, the comparison of the various configurations is also performed on the basis of net present cost, capital expenditure and cost of energy. For analysis, the site profile and load profile of Jamia Millia Islamia University, India, are taken. The optimization is performed in HOMER. It is obtained from the simulation results that the microgrid configuration comprising grid-solar photovoltaic-wind turbine is found to be best suited for the proposed site based on various parameters. Furthermore, the efficacy of the proposed system is compared with conventional grid-only system.

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A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Cited by 14 publications

References 37 publications

A Novel Hybrid Imperialist Competitive Algorithm–Particle Swarm Optimization Metaheuristic Optimization Algorithm for Cost-Effective Energy Management in Multi-Source Residential Microgrids

A Novel Hybrid Imperialist Competitive Algorithm–Particle Swarm Optimization Metaheuristic Optimization Algorithm for Cost-Effective Energy Management in Multi-Source Residential Microgrids

A hybrid approach for enhancing and optimizing the power quality and power flow in Smart Grid Connected System

Optimal selection of renewable energy–based microgrid for sustainable energy supply

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