Constructing renewable energy sphere for efficient search

Abstract

In the field of renewable energy (RE), traditional methods for understanding, development, and education have heavily relied on 2D table formats for data retrieval and presentation. However, these formats suffer from inefficiency and an inability to fully capture the relationships between variables. In response to this challenge, Li et al. (2022) demonstrated that their therapeutic 3D sphere system significantly outperformed the therapeutic 2D table in query processing time. Furthermore, Shih et al. (2020) utilized a T-test to underscore the superiority of the TED Talks sphere over the TED Talks 2D table format website in terms of convenience, query processing efficiency, usefulness, and intuitiveness. Building upon this foundation, this study referenced and enhanced the work of Li et al. by introducing a three-dimensional spherical visualization model driven by cluster-based binary integer programming (BIP). This novel approach resulted in a 58% reduction in information retrieval time and achieved an impressive 86.4% user satisfaction rating. It is worth noting that compared to the previous Systematic Review and Synthesis (SRS), user satisfaction experienced a significant 19% improvement. This improvement enhances the search efficiency for RE information, thereby fostering public awareness and development of RE. Taking energy supply-demand balance sheets as an example, this study demonstrates that the spherical retrieval system (SRS) constructed by the visualization 3D spherical model resolves the issue of inefficient retrieval in 2D table formats, and the newly added functionality of highlighting objects on the spherical surface intuitively illustrates the one-to-many relationships between individual RE supply and demand. To optimize hardware and software performance, data mining techniques are employed to cluster supply data, reducing complexity, and improving optimization efficiency. The experiment is that testers search for the same targets and compared the proposed 3D SRS with the Taiwan Power Company (Taipower) 2D website in terms of retrieval speed and accuracy. The statistical results of the T-test indicate that the proposed 3D SRS is more effective and accurate than the Taipower 2D website. The research findings indicate: 1. The new 3D SRS reduces query time by 58%. 2. Adopting the k-means algorithm for clustering and batch optimization can transform from an initially infeasible solution to finding the optimal solution within 12 s. This method also reduces computer software and hardware costs, providing effective solutions for relevant applications. These technologies can be used for the education, promotion, publicity, and dissemination of RE.