ANN-supported control strategy for a solid oxide fuel cell working on demand for a public utility building

The idea of control strategy of SOFC operating to meet demand of a public utility building was presented. The strategy was formulated with the support of Artificial Neural Network. The network was used to predict the demand for electricity. The calculations were carried out on the example of a building of the Institute of Heat Engineering Warsaw University of Technology. The control strategy is influenced by various factors depending on changes in market conditions and operating characteristics of the cell. We can define different objective functions eg: working for own needs, for maximum profit and maximum service life. The article presents a simulation of SOFC operation for demand profile of the IHE building from the selected time period. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.