Iterative optimization of a bi-level formulation to identify severe contingencies in power transmission systems

A Robust Renewable Energy Source-oriented Strategy for Smart Charging of Plug-in Electric Vehicles Considering Diverse Uncertainty Resources

“…The original PSO inspires from group movement of the fishes/birds herd (population). This metaheuristic optimization algorithm and also its enhanced variants have been numerously utilized in recent power system problems [21][22][23][24]. In original PSO, each member of the population (i.e.…”

“…where Nsol and iter are respectively symbolized for the number of particles and counter of PSO iterations. Furthermore, c1 and c2 are two predefined weighting factor regulating the moving step toward the particle's PBT and population's GPT, respectively (classically c1+c2 =4 [21][22][23][24]). The inertial coefficient λ depicts the particle's tendency to move along the previous position.…”

Co‐planning of generation and transmission expansion planning for network resiliency improvement against extreme weather conditions and uncertainty of resiliency sources

“…Table 1 shows the summary of recent studies [16,17]. Develop a model for planning of hub, taking into account various uncertainties, in which the sizing of hub converters is performed with the aim of improving hub resilience [18]. Presents A modified Binary Particle Swarm Optimization (BPSO) to help power system planners and operators to upgrade the network resiliency by finding critical contingences that may initiate cascading outages [19].…”

Is exponential stability achievable in singular perturbed delayed systems with time-varying parameters? A comprehensive analysis

“…Singularly perturbed systems have demonstrated their efficacy as potent mathematical tools for effectively capturing intricate interactions among subsystems characterized by distinct temporal characteristics [ [1] , [2] , [3] ]. These versatile systems find wide-ranging applications across various domains, encompassing chemical reactions, electrical circuits, ecological models, and neural networks [ [4] , [5] , [6] ].…”