In the dynamic world of energy distribution, reliability is the lifeblood of modern societies. Ensuring a steady power supply is not just about keeping the lights on; it’s about powering industries, hospitals, and homes with minimal disruption. This is where hybrid energy storage (HES) systems come into play, and a groundbreaking study led by Qian Li from the Office of Comprehensive Support at Renmin University of China, is set to revolutionize how these systems are selected and implemented.
The challenge with HES systems lies in their complexity. Different energy storage technologies have unique charging and discharging characteristics, making it difficult to evaluate and compare them effectively. Li’s research, published in the journal ‘Energy Informatics’ (which translates to ‘Energy Information Science’), addresses this issue head-on. The study introduces an innovative method that combines the analytic hierarchy process (AHP), criteria importance through intercriteria correlation (CRITIC), and the technique for order preference by similarity to ideal solution (TOPSIS). This integrated approach allows for a more accurate evaluation of HES schemes, regardless of the number of energy storage types involved.
One of the key innovations in Li’s work is the development of enhanced utility combination rules. These rules, which include distance, replacement, addition, and multiplication, help eliminate the impact of the number of energy storage types on the combination result. “By establishing these rules, we can effectively eliminate the impact of the number of energy storage types on the combination result,” Li explains. “This enables us to accurately calculate the technical characteristics of HES schemes with varying numbers of energy storage technologies, providing a more reliable basis for scheme comparison and selection.”
But Li didn’t stop there. The research also introduces a secondary screening method based on TOPSIS evaluation results. This method mitigates the influence of subjective coefficients by evaluating HES schemes under different conditions and selecting optimal and sub-optimal schemes. This ensures that the evaluation process is as objective as possible, reducing the risk of bias and increasing the reliability of the results.
The practical implications of this research are immense. In the energy sector, where every decision can have far-reaching commercial impacts, having a reliable and efficient method for selecting HES schemes can lead to significant cost savings and improved power supply reliability. “This can effectively improve the reliability of power supply, reduce construction costs, and promote the efficient operation of distribution networks,” Li notes. This means fewer blackouts, lower operational costs, and a more resilient energy infrastructure.
The study’s findings are not just theoretical; they have been tested in real-world scenarios. Using the IEEE-33 node as an example, the researchers configured the optimal scheme and demonstrated the high reliability of the evaluation process. This practical application underscores the potential of Li’s method to shape future developments in the field.
As the energy sector continues to evolve, with a growing emphasis on renewable energy sources and smart grids, the need for efficient and reliable energy storage solutions will only increase. Li’s research provides a valuable reference for the wide-scale application of HES in the power industry, paving the way for more innovative and effective energy storage solutions. This could mean a future where energy distribution is not just reliable but also sustainable and cost-effective, benefiting both utility companies and consumers alike.
