Fuzzy energy management of hybrid renewable power system with the aim to extend component lifetime

Summary In this paper, a fuzzy energy management algorithm for a hybrid renewable power system based on lifetime extending is presented. When the system contains two storage elements or more, the selection of the suitable element to be charged or discharged becomes of paramount importance. When the storage elements are of different types, the decision will be difficult. Conventional algorithms that make series of tests to select the storage element choose always the first available element. This way of testing affects badly the most used element and may affect the other storage elements too as they rarely operate under hard load scenarios. In this study, and in order to solve this problem, two fuzzy controllers have been used to manage the energy flow for a hybrid renewable power system. It is composed of: a photovoltaic generator as a main source, a fuel cell and batteries as a storage elements. The controllers operate as master and slave. The master controller gives orders to all the system power converters and to the slave controller as well. The latter is activated only when the storage elements are at the same state of charge. It is charged, instead of the master's, to select the suitable element to be charged or discharged. Its orders are given based on lifetime functions for each element. To examine the proposed algorithm, simulations have been performed under Matlab/Simulink (The MathWorks, Inc., Massachusetts, USA). Comparison and statistics have been carried out to give the percentage of the worked hours for each element in each operating mode. The obtained results show the high performance of the proposed algorithm. Copyright © 2017 John Wiley & Sons, Ltd. The objective of this study is to extend the lifetime of a hybrid renewable power system. The main features of the algorithm can be summarized in the following points: Using lifetime functions as criteria to select the suitable storage element when they are equally charged. Avoiding excessive use of the element over the other thanks to the form of fuzzy membership functions. Extracting the maximum power from the PVG when needed.