基于灰狼优化算法的虚拟惯量分配方法OACSTPCD
A virtual inertia allocation method based on grey wolf optimization
针对电力系统中虚拟惯量替代转动惯量后的最优分配问题,提出一种基于灰狼优化算法的虚拟惯量分配方法.首先,确定高比例新能源电力系统对惯量的需求;其次,综合考虑频率稳定性以及虚拟惯量投资成本等因素,以临界惯量、频率变化率、最大频差作为约束条件,以频率安全指标最小化与投资成本最低为目标构建虚拟惯量优化分配模型,并采用灰狼优化算法求解;最后,以修改后的WSCC 9节点系统与IEEE 39节点系统为例进行仿真分析,结果验证了所提方法的有效性与普适性.
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.
南东亮;段玉;张路;毋根柱;朱子民
国网新疆电力有限公司电力科学研究院,乌鲁木齐 830000||新疆大学 电气工程学院,乌鲁木齐 830046国网新疆电力有限公司电力科学研究院,乌鲁木齐 830000新疆大学 电气工程学院,乌鲁木齐 830046
虚拟惯量临界惯量频率稳定投资成本灰狼优化算法
virtual inertiacritical inertiafrequency stabilityinvestment costGWO
《浙江电力》 2024 (008)
12-19 / 8
国家自然科学基金(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)
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