Wei Zhang1, Bin Ji2, Ping He1, Nanqin Wang1, Yuwei Wang1, Mengzhe Zhang2,*
Energy Engineering, Vol.120, No.9, pp. 2177-2192, 2023, DOI:10.32604/ee.2023.026504
Abstract Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions. To address the unsolvable power flow problem caused by the reactive power imbalance, a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed. The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment. For the non-convergence power flow, the 500 kV nodes with reactive power compensation devices on the low-voltage side More >
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