Reliability Evaluation of Cabled Active Distribution Network Considering Multiple Devices—A Generalized MILP Model

Abstract

With the rapid development of power electronic equipment, the automation and intelligence level of active distribution networks (ADNs) continues to improve. Against this background, soft open points (SOPs) are gradually replacing traditional segmented switches and interconnection switches. The voltage support capability and fast response characteristics of SOPs can shorten power outage time and expand load recovery range. However, the widespread integration of distributed renewable energy and new power electronic devices has made the fault characteristics of ADNs more complex, significantly increasing the computational complexity of ADN reliability assessment. At present, there are few studies that comprehensively consider ADNs with multiple devices. Therefore, this paper proposes a reliability evaluation method for ADNs that considers multiple devices. Firstly, the impact of circuit breakers, SOPs, and segmented switches on the load recovery process is analyzed. Secondly, an improved virtual fault flow model based on the action mechanisms of circuit breakers, SOPs, and segmented switches is established. The virtual fault flow is represented by logical variables to simulate post fault network reconstruction strategies that include circuit breaker tripping, SOP power supply recovery, and segmented switch isolation actions. Then, with the goal of minimizing the system average outage time after network reconstruction, a generalized mixed integer linear programming (MILP) model is given. Finally, taking the IEEE 33-node testing system as a case, the effectiveness and feasibility of the proposed method are demonstrated.

A Model and Data Hybrid-Driven Method for Operational Reliability Evaluation of Power Systems Considering Endogenous Uncertainty

“…However, a separate set of techniques aims to expedite the analysis of individual system states. These methods, such as the Lagrange multiplier-based state enumeration (LMSE) [22], the multiparametric linear program (MPLP) [23,24], and the load feasible region (LFR) approach [25], bypass the need for full optimal power flow (OPF) calculations for each state by employing alternative methods to determine load shedding requirements. While existing methods offer faster reliability evaluation through reduced state exploration and analysis, they struggle to keep pace with the dynamic nature of renewable energy.…”