6. Conclusions
The development of an optimal fuzzy logic controller for a grid in dependent photovoltaic system has been presented using particle swarm optimization. PSO is able to optimize the membership functions and develop optimal rules for a fuzzy system based controller.
Results show more of the critical loads are met most of the time (around 2.5% more in the case of Caribou, ME) after optimizing the FLC, and around 11.3% more when comparing the PV-priority controller to the optimized FLC (again, in the Caribou, ME area). Additionally, the number of complete discharges of the battery is lowest for the optimized FLC (by visual inspection of Figs. 13–15), which serves to lengthen the life of the battery as other researchers have found as well. In this study, the average battery state of charge for each controller can be compared and the expected battery life increase approximated. For the case of Caribou, ME, the average battery state of charge is 75.3% (this leads to an average depth of discharge (DOD) of 24.7%) for the optimal FLC, but only 63.87% (36.13% average DOD) for the PV-priority controller. This leads to approximately a 5% increase in battery life expectancy. Of course, a more realistic evaluation depends on hour-by-hour evaluation of the battery state of charge (not just average depth of discharge). As a result, it is possible that a smaller (and cheaper) overall PV system utilizing such an optimal energy dispatch controller would be suitable for meeting the same loads as a larger more expensive system not using an optimal controller. The maintenance and replacement cost of the battery is also reduced by approximately