# Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems
###### Abstract
However, insufficient efforts focused on investigating the integration of the two systems, configuration optimization, and systems operation strategy were found. Therefore, a new distributed energy system that combines hybrid energy storage was proposed, and the configuration of the system optimization and the operation strategy of the new system were considered simultaneously [9]. The studied hybrid system contained thermal storage and two forms of energy storage, that is, supercapacitors and a lithium battery. The impact of hybrid energy storage on distributed energy systems was fully considered. Then, a two-layer cooperative optimization method for the new system was introduced, taking into account energy efficiency, economy, and environmental protection. The new system was applied to an almost energy-free society. The results indicate that the energy-saving and equivalent pollutant-equivalent primary emission reduction rates for the new system were evaluated to be 54.8% and 63.6%, respectively, under the low-pass filter operating strategy combined with secondary feedback modulation of the supercapacitor charge state. System configuration and operating strategy can be optimized simultaneously by the two-layer collaborative optimization method. Renewable energy resources often suffer from challenges, such as erratic energy generation, as a consequence of weather and seasonal changes. Hybrid renewable energy systems are a solution for efficient energy densification of renewable resources as several of them are combined to overcome challenges arising from operating them in a stand-alone mode. A study by [PERSON] et al. proposed multitarget dynamic optimization of candidate hybrid renewable energy systems using a genetic algorithm in which the operating cost of hybrid renewable energy systems, nonrenewable energy use, and fuel emissions were simultaneously reduced over a limited period [10]. In optimization, three strategies are evaluated by considering the profiles of wind, solar, and 24 h load (Strategy 1), past and 1 h ahead (Strategy 2), and 1 h ahead (Strategy 3). A comparison of the results shows that the energy to be purchased from the network for Strategy 1 is 8.7% and 10.7% lower compared with Strategies 2 and 3, and also the energy sold to the network is 19% and 22% higher than for Strategies 2 and 3, respectively, while meeting the specified load profile of 100 households. One of the most important applications of the renewable energy system is installing a well-designed HES in remote areas where grid extension is complicated and expensive. However, the proper design of such a system is a difficult task, such as coordination between different energy sources. Energy storage and load are very complex. Hybrid renewable energy system optimization is selecting appropriate components, scaling, and control strategies to provide efficient, reliable, and cost-effective alternative energy to society. A work by [PERSON] and [PERSON] presents a design of a hybrid renewable energy system consisting of photovoltaic cells and a wind generator with a battery and an inverter [11]. The system was optimally simulated using the HOGA (Hybrid Optimization by Genetic Algorithms) tool developed by the Department of Electrical Engineering of the University of Zaragoza, Spain. In the same context, a work by [PERSON] et al. is concerned with the application of modern optimization methods to devote the optimal configuration of hybrid renewable energy sources, which include photovoltaic panels, wind turbines with battery storage systems, and diesel generators [12]. The cost function of the optimization problem was chosen to be the energy cost and energy supply potential loss for the hybrid renewable energy system, where the main function of the optimization algorithms is to reduce this cost function. However, the optimal configuration cannot be achieved without meeting system reliability and operational limitations. A comparison of their results was made in order to determine the most effective method.