System Sizing and Energy Management Optimization using a Hybrid Model

Nowadays, the word knows an increase in energy demand and a scarcity in energy sources. Renewable energy sources are promising alternatives in the actual conditions. Particularly, several efforts are spent in system sizing and energy management strategies' development to make application as much profitable as possible in terms of autonomy and benefits. Genetic algorithm is widely used in these fields and demonstrated high performances in optimization processes. On the other hand, linear programming algorithm is known by its simplicity and its high performances in energy management strategies optimization. In this paper, we propose a combined model composed by genetic algorithm and linear programming method to optimize both the sizing of the installation and the energy management strategy optimization.