Microgrid Operation Optimization Considering Transient Stability Constraints: A New Bidirectional Stochastic Adaptive Robust Approach

Abstract

This article proposes a new bidirectional stochastic adaptive robust framework with transient stability constraints to optimally and securely operate microgrids (MGs). Within the proposed framework, the uncertainties of photovoltaic/wind turbine generation, load, and electricity price are modeled using adaptive robust optimization (ARO), while the uncertainty of unscheduled islanding occurrence is modeled by stochastic programming. Besides covering the uncertainties related to MG operation, the proposed approach considers transient stability uncertainties leading to a more secure MG operation scheduling framework. To the best of the authors’ knowledge, this is the first time that transient stability analysis along with stochastic adaptive robust optimization (SARO) is proposed for MG operational scheduling. In addition, a new bidirectional scenario generation method is proposed to model MG unscheduled-islanding occurrence and MG restoration to the grid-connected mode. Modeling both the grid-connected and unscheduled-islanded MG operation modes as well as their transitions further distinguishes the proposed approach from the previous ones. Furthermore, a new solution methodology is presented to solve the proposed MG scheduling problem. This methodology is capable of solving both SARO and transient stability constrained-optimal power flow problems. The proposed MG operation optimization framework and solution method are tested on the modified IEEE 33-bus network.