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Optimal operation and power management are fundamental in maximizing efficiency and minimizing the losses in microgrids, particularly in systems with a high penetration of distributed energy resources.
This review examines critical areas such as reinforcement learning, multi-agent systems, predictive modeling, energy storage, and optimization algorithms—essential for improving microgrid efficiency and reliability.
AI-enhanced energy management systems (EMSs) have shown promising results in various microgrid configurations. For instance, field-programmable gate arrays (FPGAs) equipped with AI algorithms have significantly improved cost savings and reliability by dynamically adjusting to load and generation changes .
The application of deep reinforcement learning (DRL) has shown great potential in enhancing the control and management of microgrids, addressing complex challenges such as power distribution and stability in renewable energy systems .
Energy storage is essential for managing the intermittency of renewable energy sources in microgrids . Effective energy storage solutions allow microgrids to balance supply and demand, especially when integrating variable renewable sources such as wind and solar power.
RL strategies could optimize charging and discharging patterns, ensuring better integration of electric vehicles into microgrid systems [77, 78]. In addition, transfer learning techniques could be explored to accelerate the deployment of these models across different environments [79, 80, 81, 82]. 3.1.3.
An example of each methodology applied to a residential community …
Microgrids combine distributed generating units (DGs) and energy storage systems to achieve …
The multi-agent systems paradigm has been advocated as a useful and promising tool for a wide range of applications. In this paper, the major issues and challenges …
Abstract: In order to study the ability of microgrid to absorb renewable energy and stabilize peak and valley load, This paper considers the operation modes of wind power, photovoltaic power, …
The battery energy storage system (BESS) is an important part of a DC micro-grid because renewable energy generation sources are fluctuating. The BESS can provide …
In this paper, we propose a dynamic energy management system (EMS) for a solar-and-energy storage-integrated charging station, taking into consideration EV charging demand, solar power generation, status of …
A two-layer optimal configuration model of fast/slow charging piles between …
The traditional charging pile management system usually only focuses on the basic charging function, which has problems such as single system function, poor user experience, and inconvenient management. In this …
The system needs to consider that wind–solar power generation system, energy storage battery and microgrid should always meet the load demand of the scenario, and its …
Aiming at the charging demand of electric vehicles, an improved genetic algorithm is proposed to optimize the energy storage charging piles optimization scheme.
The charging pile energy storage system can be divided into four parts: the distribution network device, the charging system, the battery charging station and the real-time …
This paper proposes a microgrid optimization strategy for new energy …
Abstract: In order to study the ability of microgrid to absorb renewable energy and stabilize …
The integration of renewable energy sources (RESs) and smart power system has turned microgrids (MGs) into effective platforms for incorporating various energy sources …
As shown in Figure 9, the energy storage supplies power to Park 3 for 23 h a day, making Park 3 the primary outlet for energy storage discharge. The charging hours of the …
The preferred microgrid system brand for energy storage charging piles. In this study, we …
Microgrids combine distributed generating units (DGs) and energy storage systems to achieve this. This research paper aims to simultaneously minimize the daily operational cost and net …
Microgrid energy management is a challenging task for microgrid operator (MGO) for optimal energy utilization in microgrid with penetration of renewable energy …
A two-layer optimal configuration model of fast/slow charging piles between multiple microgrids is proposed, which makes the output of new energy sources such as wind …
The battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging, discharging, and storage; …
This paper proposes a microgrid optimization strategy for new energy charging and swapping stations using adaptive multi-agent reinforcement learning, employing deep …
The multi-agent systems paradigm has been advocated as a useful and …
The battery energy storage technology is applied to the traditional EV (electric vehicle) …