Information gap decision theory–based risk-constrained energy management of hybrid AC/DC microgrids

Abstract Impacts of different uncertainty parameters on the operation of the system should be well studied to get optimal management of the system. The information gap decision theory (IGDT) is one the most favorite methods to model both positive and negative aspects of any uncertainty parameter. In this chapter, power price uncertainty in a hybrid AC/DC microgrid is investigated utilizing the IGDT method and obtained results are provided in three strategies as risk-averse, risk-neutral, and risk-taker. The optimal energy management of hybrid AC/DC microgrids is formulated as mixed-integer nonlinear programming, which is solved by the DICOPT solver in GAMS optimization software in two cases, with- and without-demand response (DR) cases, to clarify the impact of such programs.