A resilience enhancement strategy for networked microgrids incorporating electricity and transport and utilizing a stochastic hierarchical control approach. (June 2021)

• Record Type: Journal Article
• Authors: Wang, Y.; Rousis, A. Oulis; Strbac, G.
• Is Part Of: Sustainable energy, grids and networks. Volume 26(2021)
• Publication Date: 2021-06
• Subjects: Resilience -- Networked microgrids -- Electric vehicles -- AC OPF -- Hierarchical control -- Stochastic programming; Renewable energy sources -- Periodicals; Smart power grids -- Periodicals; Electric power systems -- Periodicals; 333.794
• DOI: 10.1016/j.segan.2021.100464
• Languages: English
• ISSNs: 2352-4677

Abstract

Abstract: High-impact and low-probability (HILP) events can cause severe damage to power systems. Networked microgrids (MGs) with distributed generation resources provide a viable solution for the resilience enhancement of power systems. However, most literature utilizes centralized control methods based on energy management systems to model networked MGs and employs static storage units to enhance resilience, which are both unrealistic. In this paper, a hierarchical control approach based on detailed AC OPF algorithm is developed to capture technical constraints relating to voltage, angle and power loss as well as obtaining accurate solutions of power exchange between MGs, while the routing of electric vehicles (EVs) is incorporated into the model to reduce load shedding during extreme events. Uncertainties relating to load profiles and renewable energy sources are captured via stochastic programming. The impacts of limited generation resources and different levels of contingencies (including multiple line faults) are captured in the model to mimic a realistic scenario and verify the effectiveness of the proposed resilience enhancement strategy. Appropriate sensitivity analyses are suggested to investigate the influence of uncertain event occurrence time, tie-line capacity and EV scheduling horizon. Highlights: A hierarchical control approach based on detailed AC OPF is proposed. Uncertainties relating to renewable energy sources and loads are considered. Time-coupled routing of electric vehicles is integrated. Limited generation, load distinction and contingencies are considered. Impact of event time, line capacity and EV scheduling horizon is analyzed.