Modeling and simulation of long term stochastic assessment in industrial microgrids proficiency considering renewable resources and load growth

Distributed Generation (DG) resources in industrial microgrids affect the reliability parameters in the networks. Therefore, the aim of the paper is to assess the reliability of industrial microgrids using a proposed composite index in the presence of DG and Demand Response (DR) resources. The reliability evaluation is performed on the basis of sequential Monte-Carlo method with regard to the available time load. Here, the widely used renewable generations such as wind and photovoltaic ones are used. Since the output of this type of DGs depends on random variables such as wind speed and solar radiation, a number of scenarios have been considered to determine the output amount per hour. The newly presented composite index shows the changes of conventional reliability indices (SAIFI, SAIDI, and EENS) per kW of DG installed. Due to the increase of industrial loads, a 10-year study is scheduled for both islanding and grid-connected performance conditions. In the islanding condition, the DR concept is also used. The proposed method is applied to IEEE-RBTS BUS2 standard network and real-world Mahmoud-Abad industrial zone network located in Isfahan, Iran in the presence of DG resources to show its effectiveness. The results are evaluated and compared in different conditions for elucidation.