Reliability Assessment of Active Distribution System Using Monte Carlo Simulation Method

Abstract

In this paper we have treated the reliability assessment problem of low and high DG penetration level of active distribution system using the Monte Carlo simulation method. The problem is formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation. The load shedding strategy and the simulation process were introduced in detail during each FMEA process. Results indicate that the integration of DG can improve the reliability of the system if the system was operated actively.

Application of System Reliability Indices in Electric Power System

“…System Average Interruption Frequency Index (SAIFI) indicates the average frequency of sustained interruptions per customer over a predefined area [11][12], [19], [27]. The number of customers and the interruptions experienced by them vary from time to time.…”

“…Thus, the method could not provide the concrete information for real engineering decision making [18]. Ge et al (2014) presented the reliability assessment problem of low and high DG penetration level of active distribution system using Monte Carlo simulation method. The problem was formulated as a two-case program, the program of low penetration simulation and the program of high penetration simulation.…”

A review on economic and technical operation of active distribution systems

“…EENS, the probability of load curtailment, expected frequency of load curtailment and a new severity factor are considered as reliability indices for transmission systems. In [67], authors use the Monte Carlo simulation to assess reliability index of ADS for low/high levels of DG penetration. A two-case programing is formulated in which the load shedding strategy is modeled when there is an imbalanced generation-load situation.…”

New reward and penalty scheme for electric distribution utilities employing load‐based reliability indices

“…The simulation results based on load point average failure rate and average outage duration in [20] are different from the true values captured during interruptions. Several techniques for analysing utility long-term investment plans are suggested in [21,22], where the reliability indices and utility regulations are overlooked. A multi-agent system architecture for virtual power plants has been introduced to manage smart grids and forecast energy demand in [23], where a detailed model for low-level management of virtual power plants is introduced.…”