Linear Programming Contractor for Interval Distribution State Estimation Using RDM Arithmetic

State estimation (SE) of distribution networks heavily relies on pseudo measurements that introduce significant errors, since real-time are insufficient. Interval SE models regularly used, where true values system states supposed to be within the estimated intervals. However, conventional interval algorithms cannot consider correlations same variables in different terms constraints, which results overly conservative results. In this paper, we propose a new model is based relative distance measure (RDM) arithmetic. proposed model, measurement errors assumed bounded given sets and state described as RDM variables. Since non-convex, solution's credibility guaranteed. Therefore, each nonlinear equation transformed into dual inequality linear equations using mean value theorem. The finally reformulated programming contractor iteratively narrows upper lower bounds Numerical tests IEEE three-phase show method outperforms interval-constrained propagation, modified Krawczyk-operator optimization methods.