Evaluation of composite reliability indices based on non-sequential Monte Carlo simulation and particle swarm optimization

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review

“…This method known as the state sampling approach. An efficient method for composite system wellbeing evaluation based on non-sequential MCS is presented in [75].Also in [76], non-Sequential MCS is presented to evaluate reliability indices of composite system. In [77], a novel approach based on non-sequential MCS and pattern recognition techniques was proposed to evaluate well-being indices for a composite generation.…”

MOPSO using probabilistic and deterministic criteria based on OHL's thermal ratings

“…PSO, similarly to the algorithms belonging to the Evolutionary Algorithm family, is a stochastic algorithm that can be used on functions where the gradient is either unavailable or computationally expensive to obtain. The origins of PSO are best described as sociologically inspired, since the original algorithm was based on the sociological behaviour associated with bird flocking and school of fish [20]. The algorithm maintains a population of particles, where each particle represents a potential solution to an optimization problem.…”

Characteristic matching of stochastic scenarios and flexible resource capacity optimisation for isolated microgrids

“…Among them, probabilistic methods are most widely used and include Monte Carlo simulations (MCS) and scenario‐based approaches [6]. Considerable research has been performed to increase the accuracy of MCSs, but this effort results in computational inefficiency [7–9]. Generally, the uncertainties have countless realisations, and considering all these realisations is impossible.…”