Extended method for the sizing, energy management, and techno-economic optimization of autonomous solar Photovoltaic/Battery systems: Experimental validation and analysis

Abstract

The solar Photovoltaic/Battery system is one of the famous widely used renewable energy systems adopted to electrify isolated areas worldwide. However, the autonomous Photovoltaic/Battery system, like all other renewable energy systems, has the same design and operating challenges: appropriate size and energy management. In this regard, the Electric systems Cascade Extended Analysis method is offered to overcome the design challenges of the system. The method includes two algorithms: the first is used to scale the system by determining the ideal battery capacity and the number of Photovoltaic panels required to fulfill a load profile. The first algorithm also includes techno-economic optimization based on the Life Cycle Cost and the Levelized Cost of Electricity as economic parameters and the Loss of Power Supply Probability as a technical indicator. The first algorithm is based on the study site’s climatic data (solar irradiation & temperature) and the economic and technical of the panel and battery selected for the study. The second algorithm is used for optimal management. Each of the electrical load and the battery is electrically connected to the management system, which makes instant comparisons between the real-time load power and the desired load power to fix the intensity of the charge/discharge current of the battery by controlling the duty cycles of the bi-directional converter linked to the battery. The simulation and the experimental assembly of the system showed the method's high efficiency in optimally designing and operating Photovoltaic/Battery systems.