An imperialist competitive algorithm approach for multi-objective optimization of direct coupling photovoltaic-electrolyzer systems

In the context of sustainable clean hydrogen production pathways, photovoltaic-electrolyzer systems are one of the most promising alternatives for acquiring hydrogen from renewable energy sources. t, determining the optimal set of design and operating variables are always a key issue while coupling directly renewable electricity sources to PEM electrolyzers. Few previous studies have attempted to find the optimal size and operational condition of directly coupled photovoltaic-electrolyzer (PV/El) systems in order to maximize the hydrogen production or to minimize energy transfer loss between photovoltaic devices and the electrolyzer. Nevertheless an easy and efficient approach still remains to be found. Because of the nonlinear nature of the system, in this framework, multi-objective nonlinear optimization is employed, an approach based on the method of imperialist competitive algorithm (ICA). It considers the effect of ambient temperature and radiation weather data during a whole year. objective optimization provides a wide range of optimal design and operating conditions, from which these variables can be selected based on objectives with different weight values. This allows performing the system optimization by considering two different objectives, namely, minimization of energy transfer loss and maximization of hydrogen production. timum system that focuses solely on maximum hydrogen production can produce 2.2% more hydrogen than with its objective being minimum energy transfer loss. However, it results in 68% more energy transfer loss in the process. The values can be adjusted with options that include a combination of the two objectives. Additionally, optimal variables can be found through the ICA method.