Multi-agent system based on the fuzzy control and extreme learning machine for intelligent management in hybrid energy system
Dounia El Bourakadi, Ali Yahyaouy, Jaouad Boumhidi · 2017
Given the current energy challenge, renewable energy appear as a real and strategic solution for electricity generation, but its intermittent nature requires us to combine two or more power sources to ensure continuity of electricity supply. In this paper we present a multi-agent system based on wind and photovoltaic power prediction using neural network trained by Extreme Learning Machine algorithm, to estimate the amount of photovoltaic and wind energy produced by photovoltaic panels and wind turbines respectively. This process aims to implement a hybrid renewable energy system with generation units (wind turbines and photovoltaic panels) and storage units (batteries). To address uncertainties in the system, we use a fuzzy logic technique to decide which auxiliary energy source will fill the need energetic. For the simulation, we use Java Agent Development Framework to implement the approach and analyze the results.