| 引用本文: | 李世春,黄森焰,李惠子,罗 颖,田冰杰.考虑厂用旋转负荷贡献的发电厂惯量修正估计[J].电力系统保护与控制,2022,50(18):61-71.[点击复制] |
| LI Shichun,HUANG Senyan,LI Huizi,LUO Ying,TIAN Bingjie.Correction estimation of the inertia of a power plant considering the contribution of rotating load[J].Power System Protection and Control,2022,50(18):61-71[点击复制] |
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| 摘要: |
| 在传统的电网惯量和频率稳定评估中，忽略了发电厂内部异步电动机负荷的惯量贡献，可能导致评估结果产生偏差。基于此，研究了常态下、考虑旋转负荷贡献的发电厂惯量修正估计方法。将发电厂及内部电动机负荷等效为一个整体，利用出口母线的有功/频率常态化小扰动数据估计发电厂等效惯量。针对发电厂等效惯量为时变参数的特点，提出应用受控自回归模型和基于可变遗忘因子的递推最小二乘辨识算法估计惯量参数。算例验证结果表明：所提出的辨识模型精度较高，能适应小扰动输入/输出数据的参数辨识。考虑电动机旋转负荷的惯量贡献时，发电厂等效惯量和系统等效惯量均存在差异，并具有时变特性，获得的修正惯量能更客观地评估发电厂惯量和系统惯量。 |
| 关键词: 发电厂等效惯量 电动机旋转负荷 时变参数辨识 受控自回归模型 递推最小二乘算法 可变遗忘因子 |
| DOI：DOI: 10.19783/j.cnki.pspc.211740 |
| 投稿时间：2021-12-22修订日期：2022-02-25 |
| 基金项目:国家自然科学基金项目资助(51907104) |
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| Correction estimation of the inertia of a power plant considering the contribution of rotating load |
| LI Shichun,HUANG Senyan,LI Huizi,LUO Ying,TIAN Bingjie |
| (1. School of Electrical and New Energy, China Three Gorges University, Yichang 443002, China; 2. Hubei Provincial Key
Laboratory of Cascade Hydropower Station Operation and Control (China Three Gorges University), Yichang 443002, China;
3. Huaihua Power Supply Branch of State Grid Hunan Electric Power Co., Ltd., Huaihua 418000, China) |
| Abstract: |
| In traditional grid inertia and frequency stability evaluation, the inertia contribution of the asynchronous motor load in the power plant is ignored. This may lead to deviations in the evaluation results. Given this, a method for estimating the inertia correction of power plants under normal conditions and considering the contribution of rotating load is studied. The power plant and the internal motor load are equivalent to a whole, and the equivalent inertia of the power plant is estimated by using the active/frequency normalized small disturbance data of the export bus. Noting the characteristic that the equivalent inertia of the power plant is a fast time-varying parameter, a controlled autoregressive model and a recursive least squares identification algorithm based on a variable forgetting factor are proposed to estimate the inertia parameters. The verification results of a test system show that the proposed identification model has high accuracy and can adapt to the parameter identification of small disturbance input/output data. When considering the inertia contribution of the rotating load, there are differences between the equivalent inertia of the power plant and the equivalent inertia of the system. Also they have time-varying characteristics, and the obtained modified inertia can more objectively evaluate the inertia of the power plant and the system inertia.
This work is supported by the National Natural Science Foundation of China (No. 51907104). |
| Key words: power plant equivalent inertia motor rotating load time-varying parameter identification controlled autoregressive model recursive least square algorithm variable forgetting factor |
