Optimal Energy Storage Allocation for Mitigating the Unbalance in Active Distribution Network via Uncertainty Quantification

Voltage unbalance (VU) in an active distribution network (ADN) could result in increased network losses and even system instability. The additional uncertainties embedded in ADN might lead to serious VU problems with the proliferation of single-phase distributed energy resources (DERs). This paper proposes a two-stage uncertainty quantification and unbalance mitigation (UQUM) framework to cope with the corresponding VU problems and quantify and mitigate the impacts of variable DERs on VU. In Stage one, the global sensitivity analysis based on the Rosenblatt transformation (RT-based GSA) method is proposed to quantify the impacts of nonlinearly correlated DERs with tail dependence on VU. The RT-GSA method can identify critical DERs with significant impacts on VU. In Stage two, the joint allocations of fixed and mobile energy storage devices (ESDs) are considered in which an optimal mitigation strategy is proposed to alleviate VU and effectively compensate the critical DER fluctuations (identified in Stage one). Based on the given DER data and the available ESD capacity, the effectiveness of the proposed UQUM framework is verified in a 123-bus three-phase unbalanced ADN and the corresponding results are discussed.