To address this problem, this paper uses a multi‐agent deep reinforcement learning (DRL) algorithm to design the controllers to control the frequency of the multi‐microgrids. Firstly, a
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Voltage and frequency stability are paramount for MG operation, necessitating advanced control frameworks to regulate key parameters effectively. This research introduces a multilayer
By taking into account the effects of electric vehicles (EVs), this paper introduces an innovative control strategy with a master-slave configuration for frequency control of interconnected
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Many research studies have explored various frequency control methods for power systems characterized by low inertia, encompassing both single and multi-microgrid configurations.
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This paper presents an advanced frequency control solution for multi-microgrid systems (MMGS) with high renewable energy penetration, where conventional control methods struggle with scalability and
Under loss of utility power, a microgrid must regulate voltage and frequency within the grid, and therefore these controls would be well suited to microgrids. This research uses virtual
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An optimal model-free control (MFC) strategy with distributed energy storage systems (DESS) is proposed to optimize frequency dynamic response and enhance stability of multi-microgrid
This paper addresses load frequency control (LFC) in wind-diesel multi-microgrids by exploiting a multi-agent deep deterministic policy gradient (MADDPG) method.
A novel control technique which can combines fuzzy control with Model Predictive Control (MPC) is proposed to address significant frequency fluctuations during the load deviation in micro
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