Abstract

To alleviate the impact of output uncertainty of renewable energy sources (RESs) in unbalanced active distribution networks (ADNs), this paper proposed a two-time scale robust optimization method for the multi-terminal soft open point (SOP). In the long-term scale, the operation points of the SOP were optimized by semidefinite programming (SDP) model to minimize system loss and mitigate voltage unbalance. An improved iterative cutting plane (ICP) method was proposed to strengthen the exactness of the SDP rank-one relaxation. In the short-term scale, V 2- P and V 2- Q droop control mode was implemented in the SOP to better respond to the output uncertainty of RESs. Then a slope robust optimization model was established based on long-term operation points and short-term forecast data to improve system robust security. To coordinate these two time scales, a co-optimization re-dispatch strategy was proposed in the short-term model so that the robust safety margin could be further expanded in extreme conditions. Case studies show that the proposed method can fully utilize the flexible power flow regulation ability of the multi-terminal SOP to reduce system loss, mitigate voltage unbalance and guarantee system robust security in the presence of RES output uncertainty.

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