A Power-System Economic Dispatching Based on Enhanced Group Search Optimizer

Smart Innovation, Systems and Technologies(2023)

引用 0|浏览0
暂无评分
摘要
Economic dispatch (ED) is one of the critical tasks in a power system’s optimization issues, but its characteristics with non-convex, high-dimensional, non-linear, and non-differentiable, so that caused solutions are more challenging in reality. This paper suggests an enhanced group search optimizer (EGSO) for solving the ED model with the valve-point effect and the different fuels. The EGSO adopts the original group search optimizer (GSO) by changing polar to Cartesian coordinate’s conversion and adding cyclic translation operators to the search behavior of the finder and walker to avoid falling into local optimal and slow convergence of the GSO. In the experiment section, the testing power systems of the ED model are used to validate the EGSO performance. The experimental results reveal that EGSO outperformed the other algorithms regarding convergence speed, the time required to complete calculations, and impacts with lower fuel cost. Additionally, with excellent outcomes in optimization issues involving multiple local optimal values show the EGSO is practical, quick, and efficient in addressing the challenging ED model.
更多
查看译文
关键词
group,power-system
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要