Improving resilience of networked multi-energy carrier microgrids through proactive scheduling

• Published in: International journal of electrical power & energy systems Vol. 165; p. 110510
• Main Authors: Ghasemi, Ali Akbar, Gitizadeh, Mohsen, Norouzi, Mohammadali
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2025; Elsevier
• Subjects: Feasibility islanding; Networked multi-energy carrier microgrids (NMECMs); Preparedness; Resilient proactive scheduling; Networked multi-energy carrier microgrids (NMECMs); Preparedness; Feasibility islanding; Resilient proactive scheduling
• ISSN: 0142-0615
• DOI: 10.1016/j.ijepes.2025.110510

•Proposing a proactive scheduling model designed to bolster NMECM resilience.•Developing a two stage MILP optimization model of NMECM.•Achieving secure islanding, proper preparedness, and lowered operating costs.•Considering normal operation and contingency-based uncertainties.•Considering the responsive behavior of electric, gas and heat loads. The interdependence of various energy carriers within networked multi-energy carrier microgrids (NMECMs) enhances resilience against high-impact low-probability (HILP) events. However, these interdependences can also increase vulnerability to disruptions. This paper introduces a proactive scheduling model designed to bolster NMECM resilience during sudden outages in upstream gas and electricity networks. The proposed method adjusts microgrid scheduling to secure feasible islanding, maximize preparedness, and minimize operating costs and load shedding. The optimization problem is modeled as a two-stage mixed-integer linear programming. In the first stage, scheduling of the microgrids is programmed in normal mode. In the second stage, the schedule of the microgrids is modeled in the mode of disconnection from both the gas and electricity networks. Furthermore, to consider both normal and contingency uncertainties, stochastic and deterministic models of proactive resilient scheduling for the NMECMs are presented. Moreover, the benefits of responsive electrical and heat loads are considered. Finally, by performing simulations, the efficiency of the proposed method in improving the resilience of the test NMECMs is evaluated. Numerical results demonstrate the superior performance of the proposed model over the other scheduling models. In particular, the unpreparedness index of the proposed stochastic proactive scheduling model reduces by 68% compared with the normal scheduling, while ensuring uninterrupted power supply to critical electrical and heat loads even in islanding conditions.