A heuristic fuzzy algorithm bio-inspired by Evolution Strategies for energy forecasting problems

A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment

“…Initial ideas regarding to this proposed fuzzy model can be found in Coelho et al [40,41]. This current work presents a more complete and general mathematical formulation of it.…”

“…According to empirical calibration and parameters suggested by the literature [29,41], the size of the population, l, and number of offspring, k, generated in each generation were fixed: l ¼ 10 and k ¼ 60, respectively. Initial values for the standard deviation matrix M were chosen at random from ½1; 10 and r update was fixed to be 1.…”

Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey

“…Lezama et al [253] used differential ESs for large-scale energy resource management in smart grids. Coelho et al [254] used it for energy load forecasting in electric grids. Versloot et al [255] optimized near-field wireless power transfer using ESs.…”

Genetic algorithm‐based non‐linear auto‐regressive with exogenous inputs neural network short‐term and medium‐term uncertainty modelling and prediction for electrical load and wind speed

“…A fuzzy‐NN with particle swarm optimisation‐based BP method was employed in [15] for MTLF. A heuristic fuzzy algorithm bio‐inspired by evolution strategies is employed in [16]. Another hybrid scheme is applied in [17] for load forecasting that combined statistical and physical constraints.…”