Optimal management of power sharing based on hybrid fuzzy logic-genetic algorithm of water desalination system integrated with renewable energy

Abstract Coupling renewable energy sources with reverse osmosis desalination systems offers a suitable solution to freshwater scarcity problem, especially in regions suffering from hydraulic and electrical crisis. In this context, design, feasibility and performance evaluation of a standalone brackish water reverse osmosis desalination unit powered with hybrid PV/Wind sources in isolated community have been investigated. In order to reduce the cost of investment and maintenance, the proposed system was based on hydraulic storage in a water tower instead of electrochemical storage. This study aims to optimize the power sharing of the generated power between the motor-pumps while respecting constraints and maximize the produced freshwater quantity. For this purpose, a genetic algorithm optimization of the fuzzy-logic membership functions is proposed. First, a simple fuzzy logic system was used to improve the power sharing between the hydro mechanical processes. Then, an offline optimization of the developed fuzzy-logic using genetic algorithm was applied. Finally, to validate the developed optimal energy management strategy performance, single fuzzy-logic and hybrid fuzzy logic-genetic algorithm energy management system results are compared for a real power profiles. The optimized fuzzy-logic energy management strategy demonstrated its high performance in improving the system energy efficiency with the reduction of the consumed energy (gain of 7.1% in October (Autonm)), and enhance the permeate water production (gain of 2.96% during a week) compared with the energy management based only fuzzy-logic strategy.