Abstract
Uncertainty characterization is an essential component of decision-making problems in electricity markets. In this work, a class-driven approach is proposed to describe stochasticity. The methodology consists of a three-step process that includes a class allocation component, a generative element based on a long short-term memory neural network and an automated
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