Optimal control in microgrid using multi-agent reinforcement learning
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资源说明:This paper presents an improved reinforcement learning method to minimize electricity costs on the
premise of satisfying the power balance and generation limit of units in a microgrid with grid-
connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of
optimal control for microgrid is proposed. Then, a state variable ‘‘Average Electricity Price Trend’’ which
is used to express the most possible transitio
premise of satisfying the power balance and generation limit of units in a microgrid with grid-
connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of
optimal control for microgrid is proposed. Then, a state variable ‘‘Average Electricity Price Trend’’ which
is used to express the most possible transitio
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