An intelligent load manager for PV powered off-grid residential houses

This paper proposes a management system based on certain rule set implemented by Modified Mild Intrusive Genetic Algorithm (MMIGA) that will optimize the load allocation to match the house owner affordable solar system inverter. The algorithm optimized load allocation in real time in both sufficient and insufficient supplies of energy. A daily load discrimination profile is first established followed by the development of priority matrix for the respective time of the day; MMIGA is then used to intelligently evolve a sequence of bits, which are then implemented by the hardware while observing certain set of rules. The result shows that about 98.88% allocation was obtained in the sufficient case scenario while 99.84% allocation was achieved in the insufficient scenario. The proposed algorithm meets the objective of being cost effective, smart, simple to use and can be severally applied to different load profiles. (C) 2015 International Energy Initiative. Published by Elsevier Inc. All rights reserved.