Abstract

Abstract
Performance indicators, such as the SAIFI and the SAIDI, are commonly used by regulatory agencies to evaluate the performance of distribution companies (DisCos). Based on such indicators, it is common practice to apply penalties or grant rewards if the indicators are greater to or less than a given threshold. This work proposes a new multi-objective optimization model for pinpointing the critical assets involved in outage events based on past performance indicators, such as the SAIDI and the System Average Interruption Duration Exceeding Threshold (SAIDET) indexes. Our approach allows to retrieve the minimal set of assets in large historical interruption datasets that most contribute to past performance indicators. A case study using a real interruption dataset between the years 2011–2104 from a Brazilian DisCo revealed that the optimal inspection plan according to the decision maker preferences consist of 332 equipment out of a total of 5873. This subset of equipment, which contribute 61.90% and 55.76% to the observed SAIFI and SAIDET indexes in that period, can assist managerial decisions for preventive maintenance actions by prioritizing technical inspections to assets deemed as critical. © 2021

Abstract
Modern power grids have high levels of distributed energy resources, automation, and inherent flexibility. Those characteristics have been proven to be favorable from an environmental, social and economic perspective. Despite the increased versatility, modern grids are becoming more vulnerable to high-impact low-probability (HILP) threats, particularly for the distribution networks. On one hand, this is due to the increasing frequency and severity of weather events and natural disasters. On the other hand, it is aggravated by the increased complexity of smart grids. Resilience is broadly defined as the capability of a system to mitigate the effects of and recover from HILP events, which is often confused with reliability that is concerned with low-impact high-probability (LIHP) ones. In this paper, a distribution system in Portugal is simulated to showcase how the utilization of flexibility and mobile energy resources (MERs) should be considered differently relative to HILP vs LIHP threats.

Abstract
This paper presents an approach to optimize the placement of fault indicator devices in distribution systems using the cross-entropy method and results from traffic simulations. The problem formulation takes into account the impact of the devices on restoration times and costs due to fines related to service interruption reliability indices. Candidate solutions to the problem are evaluated using sequential Monte Carlo simulations, where travel times of maintenance crews are sampled according to data acquired from mobility traffic simulations. Results show the applicability of the approach in different simulation scenarios and the benefits of installing the devices in distribution networks. © 2022 Elsevier B.V.

Abstract
In this paper, a multi-temporal optimal power flow (OPF) model for radial networks is proposed. The mathematical problem formulation is presented as a mixed-integer quadratically constrained programming (MIQCP) problem. The main core of the developed OPF problem is benefiting from the second-order conic programming (SOCP) approach while the quadratic constraints of the power flow equations have been efficiently handled. In the developed model, the dynamic behaviour of the electrical energy storage (EES) has been addressed for the day-ahead operation problem. In addition, the developed model is tested and verified for both normal and contingent events and the obtained results are satisfactory in terms of feasibility and optimality. In the islanded operation, a grid-forming unit is the main responsible for maintaining the voltage reference while other units behave as slave. The model is tested on the modified IEEE 33-bus network to verify the performance of the developed tool. © 2022 IEEE.