This article proposes a new bidirectional stochastic adaptive robust framework with transient stability constraints to optimally and securely operate microgrids (MGs). Within
This paper introduces a deep reinforcement learning based optimization framework to improve a multi-energy island microgrid. Furthermore, an innovative approach using a fusion model of
To optimize the cost of the micro grid, the first thing is to ensure the safety and stability of the power grid operation, and then consider: the photovoltaic operation cost of the
The transition from grid-connected operation to isolated island operation state is the primary consideration in the operation of microgrid in the island mode. In this process, the energy conversion and control system of
Microgrid operations planning is one of the keys to ensuring the safe and efficient outputs of distributed energy resources (DERs) and the stable operation of a power system in a microgrid (MG). In this study, for the
The transition from grid-connected operation to isolated island operation state is the primary consideration in the operation of microgrid in the island mode. In this process,
Case B overlooks the impact of extreme scenarios on configuration and operation for the island microgrid. It is important to note that this study proposes a data-driven DRO
To optimize the cost of the micro grid, the first thing is to ensure the safety and stability of the power grid operation, and then consider: the photovoltaic operation cost of the micro grid in
Island microgrids play a crucial role in developing and utilizing offshore renewable energy sources. However, high operation costs and limited operational flexibility are significant
Through operation optimization calculation, a reasonable operation scheme can be formulated to improve the economy of microgrid operation . Thus, there have been many studies about microgrid operation optimization [20, 21]. Consequently, some reviews related to microgrid operation have been published in recent years.
To reduce the variability among scenario costs caused by uncertainties, Yu et al. developed a multi-objective optimization model for robust microgrid planning, which is based on an economic robustness measure . The objective of the study was to reduce the cost and lower the pollutant emissions. 4.5.1.
At present, the research on microgrid optimization mainly simplifies multiple objectives such as operation cost reduction, energy management and environmental protection into a single objective for optimization, but there are often conflicts between multiple objectives, thus making it difficult to achieve the optimization at the same time.
Several studies in the literature show that the optimization of a microgrid can be solved by various algorithms. The most frequently used algorithm type is a genetic algorithm (GA) [83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95].
Lastly, a literature bibliometric analysis is provided; the results show that the operation optimization of microgrids has received increasing attention in recent years, and developing countries have shown more interest in this field than developed countries have.
Microgrid Operation A microgrid operation (MGO) is a distributed class of electricity supply points and loads that typically connect and synchronize with the conventional wide area synchronous grid but could disconnect to an islanded mode through static transfer switch (STS) and function without support.
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