ABSTRACT
This study aims to perform a comprehensive evaluation of a battery-inverter system for hybrid energy storage in the context of renewable energy applications. The focus of this study is to assess the performance of a 2400W battery-inverter system, and this evaluation is driven by specific objectives. These objectives aim at developing a mathematical model to evaluate the performance of a battery-inverter hybrid storage system for renewable energy applications, utilizing MATLAB for simulating the model to analyze dynamic system behavior and energy flow, and validating the simulation results to ensure their accuracy and reliability.
The research methodology is grounded in a systematic approach to evaluating the battery-inverter system's performance. The model development takes inspiration from the crucial parameters identified which encompass the state of charge, battery charge/discharge rates, inverter efficiency, and operating battery temperature. The study delves into the Peukert equation, which assesses battery capacity. It scrutinizes battery charge and discharge rates by considering variables such as efficiency, time intervals, and energy storage. The state of charge (SOC) is analyzed during both charging and discharging phases, while battery temperature's impact is assessed using mathematical equations. The comprehensive model aligns with the system's operational efficiency by using the harmonized performance evaluation model.
The study yields several noteworthy results that underscore the potential of the 2400W battery-inverter hybrid storage system. The battery exhibits a dynamic energy capacity, ranging from an average of 2386.87Wh to a peak of 2392.95Wh, with occasional temporary dips to 2380.85Wh. The variability in battery capacity hints at extended energy autonomy, a crucial feature for renewable energy systems. Validation using the Root Mean Square Error (RMSE) produces an error metric of 7.5020, indicating a moderate level of variation in predictions compared to actual observations. Meanwhile, the Mean Absolute Percentage Error (MAPE) yields an error of 3.6459%, signifying a reasonably accurate model. With an efficiency rating exceeding 84%, as determined by the harmonized performance evaluation model, the system appears robust. These findings point towards the potential of this system in renewable energy applications, suggesting opportunities for enhancing energy storage and distribution devices. Recommendations for improvement include optimizing battery management algorithms and implementing advanced thermal management strategies to boost efficiency and longevity.
