Reliability-Sensitive Optimization for Provision of Ancillary Services by Tempo-Spatial Correlated Distributed Energy Resources

Abstract

In this paper, a reliability-sensitive optimization approach for the provision of ancillary services from distributed energy resources is proposed. The main focus here is on small-scale renewable energy sources such as wind turbines and PV arrays, which are highly distributed, and the generated power is weather dependent and intermittent. Therefore, providing a reliable ancillary service through these unreliable resources is a complicated problem addressed here. In this paper, the tempo-spatial correlation between these renewable resources is mathematically modeled by pair-copula functions and included in the reliability evaluation procedure using the non-sequential Monte Carlo simulation method. An optimization problem is formulated using proposed joint reliability model to find the minimum number of renewable resources to provide ancillary services within a desired reliability level. The proposed optimization model is applied to real wind farms in Lower Saxony in Germany to provide the spinning reserve service. The results prove that including the correlation concept in the reliability evaluation procedure leads to the more realistic scenarios that play an essential role in maintaining the service’s reliability level.