An efficient photovoltaic power system for renewable energy with hybrid approach

Abstract

Renewable energy sources are seen as the key to future energy needs because they are clean and sustainable. Solar photovoltaic (PV) energy is a widely used and accessible renewable source. This research introduces a new way to enhance the efficiency and reliability of PV power systems. The study focuses on using high-performance, grid-tied hybrid DC-DC converters in PV systems. These converters can minimize power loss during energy conversion. Various well-known existing MPPT (Maximum Power Point Tracking) algorithms are used to obtain maximum power output from the PV modules. However, owing to their operational characteristics, it takes them longer to track MPP. Additionally, they provide oscillation near MPP. An improved MPPT algorithm based on the pelican optimization method is developed to ensure optimal power from the PV source by reducing tracking time and minimizing fluctuations around MPP. The research also discusses the causes of power loss, including those caused by parasitic resistance in components. It then proposes design strategies to reduce these losses. Mathematical simulations show that the proposed system attains high efficiency across a wide range of power levels. The design also minimizes the impact on voltage gain and voltage stress caused by load and parasitic resistance changes. Theoretical models are developed for component resistances, efficiency, voltage gain, and voltage stress. To address challenges like the intermittent output and irregular voltage of PV power generation, this research presents a system that combines a high-performance DC voltage conditioner with an efficient inverter. A prototype system is built and tested employing simulations (MATLAB/Simulink) and theoretical calculations to verify the effectiveness of the proposed design. This method effectively maximizes energy production and ensures compatibility with the power grid by maintaining low Total Harmonic Distortion (THD) and high power factor. Additionally, the system optimizes power conversion at each stage through advanced mathematical modeling. The findings from this research, including the proposed system design and data results, are valuable for professionals and researchers in renewable energy and battery management systems (BMS) for electric vehicles. This paves the way for further advancements in these fields.