Hybridization of planning and operational techniques for resiliency improvement of electrical distribution networks against multi-scenario natural disasters based on a convex model.

• Proposing new convex optimization model to improve resiliency of electrical network. • Considering both planning and operational aspects as a complete technique. • Considering resiliency of electrical networks through multi-scenario disasters. • Dynamic micro-grid formation is applied to guarantee sustainability of networks. • Considering load priority, uncertainty of wind turbine and photovoltaic generation. Due to increasing the intensity and frequency of natural catastrophes, sustainable supplying of consumers is one of the main challenges of electrical distribution companies against these high-impact and low-probability (HILP) events. Recently, researches are directed to solve the mentioned challenge by various methods including optimal distributed generation and energy storage placement, micro-grid formation, structural reinforcement and etc. In addition, the uncertainty nature of the disasters, loads and renewable generations has influenced these studies. Despite the availability of different solutions considering all resilient-oriented methods and uncertain parameters, applying a proper model as long as simplifying the equations, which satisfies all the needs, are still the outstanding aspects that must be studied. This paper applies and proposes convex equations in all parts, including both operational and planning perspectives as an innovation. Mixed-integer quadratically-constrained programming (MIQCP) is adapted for formulating the problem. The proposed model is developed under GAMS environment, and its performance is evaluated by the IEEE 33-node test system under various severe fault scenarios. Comparing the results reveals that the hybridization technique against only planning technique leads to a decrease of 46.15 % and 42.45 % in load shedding and investment costs respectively. Also, it causes a decrease of 40.63 % and 25.32 % in load shedding and investment costs respectively compared to only operational techniques causes. [Display omitted] [ABSTRACT FROM AUTHOR]