Residential fuel cell energy systems performance optimization using “soft computing” techniques

Stationary residential and commercial fuel cell cogeneration systems have received increasing attention by the general public due to their great potential to supply both thermal and electrical loads to the dwellings. The reported number of field demonstration trials with grid connected and off-grid applications are under way and valuable and unique data are collected to describe the system’s performance. While the single electricity mode of operation is relatively easy to introduce, it is characterized with relatively low efficiency performance (20–35%). The combined heat and power generation mode is more attractive due to higher efficiency +60%, better resources and fuel utilization, and the advantage of using a compact one box/single fuel approach for supplying all energy needs of the dwellings. While commercial fuel cell cogeneration applications are easy to adopt in combined mode of operation, due to the relatively stable base power/heat load throughout the day, the residential fuel cell cogeneration systems face a different environment with uneven load, usually two peaks in the morning and in the evening and the fact that the triple load: space, water and power occur at almost the same time. In most of the cases, the fuel cell system is not able to satisfy the triple demand and additional back up heater/burner is used. The developed ‘’soft computing” control strategy for FC integrated systems would be able to optimize the combined system operation while satisfying combination of demands. The simulation results showed that by employing a generic fuzzy logic control strategy the management of the power supply and thermal loads could be done appropriately in an optimal way, satisfying homeowners’ power and comfort needs.