浙江电力2024，Vol.43Issue(8)：12-19,8.DOI:10.19585/j.zjdl.202408002
基于灰狼优化算法的虚拟惯量分配方法
A virtual inertia allocation method based on grey wolf optimization
摘要
Abstract
To address the optimal inertia allocation after replacing the moment of inertia with virtual inertia in power systems,a method for virtual inertia allocation based on grey wolf optimization(GWO)is proposed.Firstly,the de-mand for inertia in high-proportion renewable energy power systems is determined.Secondly,considerations include factors such as frequency stability and investment cost of virtual inertia.An optimal model for virtual inertia alloca-tion is constructed with critical inertia,rate of change of frequency(RoCoF),and maximum frequency deviation as constraints,as well as with the objective of minimizing the frequency safety index and investment cost.The GWO is employed to solve the model.Finally,simulation analysis is conducted using the modified WSCC 9-bus system and IEEE 39-bus system as examples.The results validate the effectiveness and universality of the proposed method.关键词
虚拟惯量/临界惯量/频率稳定/投资成本/灰狼优化算法Key words
virtual inertia/critical inertia/frequency stability/investment cost/GWO引用本文复制引用
南东亮,段玉,张路,毋根柱,朱子民..基于灰狼优化算法的虚拟惯量分配方法[J].浙江电力,2024,43(8):12-19,8.基金项目
国家自然科学基金(52267009) （52267009）
国网新疆电力有限公司电力科学研究院科学技术项目(5230DK230001) （5230DK230001）
