Microgrid hybrid coordination control method based on reinforcement learning and multi-agent theory
A reinforcement learning and multi-agent technology, applied in electrical components, energy storage, circuit devices, etc., can solve problems such as general performance, loss of energy storage life, and single strategy, and achieve the goal of reducing unstable factors and stabilizing bus voltage Effect
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[0029] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:
[0030] Such as Figure 4 A hybrid coordinated control method of microgrid based on reinforcement learning and multi-agent theory is shown, including the following steps:
[0031] Step 1: In order to optimally control the bus voltage, the voltage layered control strategy divides the bus voltage into 6 detection levels: (—, 0.95U ref ], (0.95U ref , 0.96U ref ], (0.96U ref , 0.98U ref ], (0.98U ref , 1.02U ref ], (1.02U ref , 1.05U ref ], (1.05U ref , —], where U ref is the reference voltage.
[0032] Due to the randomness of renewable energy generation and load demand, the bus voltage will fluctuate to a certain extent. When the bus voltage jumps from a certain range to another ra...
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