Multi swarm optimization based adaptive fuzzy multi agent system for microgrid multi-objective energy management

Serraji, Maria; Amine, Didi Omar El; Boumhidi, Jaouad

doi:10.3233/kes-160350

Cited by 10 publications

(2 citation statements)

References 36 publications

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“…The specific implications of management of power and energy also encompass sustainability. This refers to the use of energy resources in such a way that the needs of the future generations are considered even while scarce resources are being utilized by current generations [11]. Despite the fact that there are many factors and issues that contribute towards the sustainable use of power, the framework of management is always important.…”

Section: Implications Of Power and Energy Managementmentioning

confidence: 99%

Analysis of Green Building Effect on Micro grid Based on Potential Energy Savings and BIM

Baht¹,

Nicolae²,

Diana³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Section: Implications Of Power and Energy Managementmentioning

confidence: 99%

Analysis of Green Building Effect on Micro grid Based on Potential Energy Savings and BIM

Baht¹,

Nicolae²,

Diana³

et al. 2020

Adv. sci. technol. eng. syst. j.

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“…Generally, MGs may operate in islanding mode or interconnected to the main grid, in which the energy can be bought from or sold to the grid or be isolated from the grid as a controlled entity [1,9]. The energy management (EM) problem has a complex and nonlinear nature problem.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Modeling and Equilibrium Optimizer Solving for Energy Management of Renewable Micro-Grids Incorporating Storage Devices

et al. 2021

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Recently, micro-grids (MGs) have had a great impact on power system issues due to their clear environmental and economic advantages. This paper proposes an equilibrium optimizer (EO) technique for solving the energy management problem of MGs incorporating energy storage devices concerning the emissions from renewable energy sources (RES) of MGs. Because of the imprecision and uncertainties related to the RESs, market prices, and forecast load demand, the optimization problem is described in a probabilistic manner using a 2m + 1 point estimation approach. Then, the EO approach is utilized for solving the probabilistic energy management (EM) problem. The EM problem is described according to the market policy on the basis of minimizing the total operating cost and emission from RESs through optimal settings of the power generated from distributed generators (DGs) and grids connected under the condition of satisfying the operational constraints of the system. The proposed EO is evaluated based on a grid-connected MG that includes energy storage devices. Moreover, to prove the effectiveness of the EO, it is compared with other recently meta-heuristic techniques. The simulation results show acceptable robustness of the EO for solving the EM problem as compared to other techniques.

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A robust energy management approach in two-steps ahead using deep learning BiLSTM prediction model and type-2 fuzzy decision-making controller

Bourakadi

Ramadan

Yahyaouy

et al. 2023

Fuzzy Optim Decis Making

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Multi swarm optimization based adaptive fuzzy multi agent system for microgrid multi-objective energy management

Cited by 10 publications

References 36 publications

Analysis of Green Building Effect on Micro grid Based on Potential Energy Savings and BIM

Analysis of Green Building Effect on Micro grid Based on Potential Energy Savings and BIM

Probabilistic Modeling and Equilibrium Optimizer Solving for Energy Management of Renewable Micro-Grids Incorporating Storage Devices

A robust energy management approach in two-steps ahead using deep learning BiLSTM prediction model and type-2 fuzzy decision-making controller

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