In developing countries, half of the world’s population lives without electric power. Hybrid power systems, consisting of photovoltaic (PV) modules, battery banks, and backup diesel generators, have the potential to become a cost-effective solution for delivering power to many of these remote villages where grid extension is cost-prohibitive. In this paper, we show that improved dispatch
... [Show full abstract] strategies can significantly decrease the cost of a hybrid power system. We propose using a genetic algorithm (GA) in combination with novel load and insolation predictive strategies to reduce the operating costs over the present state-of-the-art methods. Realistic simulations demonstrate that this technique provides an average cost savings of 20.9% over the Set Point Strategy and 13.8% over the Load Following Strategy. We show that this strategy is a viable means of reducing the cost of hybrid power system operation.