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Frontiers | Multi-objective coordinated control and optimization for
In contrast, IMOPSO ensures coordinated control and effectively balances economic efficiency, environmental sustainability, and operational safety. This study provides a robust
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A multi-agent system approach for real-time energy management and
This study focuses on the management and optimization of a low-voltage microgrid with a multi-source (wind, PV, diesel generator) and multi-load (DC and AC) configuration, coupled with an
An improved sinh cosh optimizer for optimal scheduling of a microgrid
Article Open access Published: 08 April 2026 An improved sinh cosh optimizer for optimal scheduling of a microgrid with multi-energy resources and storage considering different weather
Optimal Scheduling of a Microgrid Considering Multi-Source
Abstract: To address the insufficient scheduling economy of microgrids caused by renewable energy output fluctuations and the time-of-use (TOU) electricity pricing environment, a multi-source
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Optimizing microgrid performance a multi-objective
The microgrid energy management (MGEM) problem in the presence of hybrid sources of energy and storage units is approached by
Multi-Objective Energy Management in Microgrids with Hybrid
While existing studies on optimal energy dispatch focus on single-objective optimization or simpler algorithms, this research proposes a comprehensive strategy for both grid-connected and
Research on Multi-Objective Optimal Allocation of Multi-Microgrid
Regarding the power and capacity configuration of the SES system, a multi-objective optimization model is established aiming to minimize both the energy storage investment costs and
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Smart grid management: Integrating hybrid intelligent algorithms for
These papers are categorized based on the optimization techniques employed into two main groups: conventional optimization approaches and intelligent optimization techniques.
Optimal energy management for multi-energy microgrids using hybrid
In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems.
Optimizing Microgrid Operation: Integration of Emerging Technologies
This review examines critical areas such as reinforcement learning, multi-agent systems, predictive modeling, energy storage, and optimization algorithms—essential for improving microgrid
Optimizing microgrid performance a multi-objective strategy for
The microgrid energy management (MGEM) problem in the presence of hybrid sources of energy and storage units is approached by proposing a multi-objective optimization approach.