Assessing the Effectiveness of Weighted Information Gap Decision Theory Integrated with Energy Management Systems for Isolated Microgrids

In the context of microgrid, renewable energy variations are still a major concern for operators, especially in industrial applications in which microgrids are typically located in remote areas and are operated autonomously. Information gap decision theory (IGDT) is a nonprobabilistic method utilized to appraise various levels of risk without the availability of statistical data, such as probability density functions of uncertain parameters. Despite such a rewarding feature, the IGDT in its current form is unable to obtain time-varying robustness bands, meaning that it does not take into consideration the system risk imposed by renewable energy injections at each individual time interval in a short-term operation horizon. To overcome this issue, this article presents a modified version of the IGDT named weighted IGDT (W-IGDT), yielding risk-based time-varying robustness bands rather than time-independent ones. This article also proposes a W-IGDT-based energy management system (EMS) based on a linked unit commitment-optimal power flow (UC-OPF) framework, which simultaneously incorporates the generating units on/off status as well as power flow limits into the optimization procedure. In order to illustrate the performance of the proposed EMS, a CIGRE microgrid benchmark is utilized, and the results indicate the effectiveness of the W-IGDT-based EMS in terms of optimal operation and addressing the intermittency of renewable energy sources.