基于改进粒子滤波的综合能源系统预测辅助状态估计  

Forecasting-aided state estimation of integrated energy systems based on improved particle filter

作　　者：杨德昌[1,2] 王雅宁 李朝霞 龚雪娇 余建树 李玲 YANG Dechang;WANG Yaning;LI Zhaoxia;GONG Xuejiao;YU Jianshu;LI Ling(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;College of Electrical Engineering,Tibet Agricultural and Animal Husbandry University,Linzhi 860000,China)

机构地区：[1]中国农业大学信息与电气工程学院,北京100083 [2]西藏农牧学院电气工程学院,西藏自治区林芝860000

出　　处：《电力工程技术》2022年第6期172-181,共10页Electric Power Engineering Technology

基　　金：国家自然科学基金资助项目(51977212)。

摘　　要：高效准确的状态估计是综合能源系统安全稳定的基础。粒子滤波具有精度高、对非线性系统适应性强的优点,已应用于电力系统的状态估计中。为提高综合能源系统的状态估计精度,文中提出一种基于改进粒子滤波的综合能源系统预测辅助状态估计方法。首先,构建包含电-热-气网络的区域综合能源系统模型;然后,将粒子滤波算法拓展到电-热-气网络,在粒子滤波相关理论的基础上,针对传统粒子滤波算法存在的跟踪误差问题对粒子滤波的预测步进行改进;最后,利用经典的综合能源系统算例对文中提出的改进粒子滤波算法进行验证。结果证明该方法能够有效解决传统粒子滤波算法的跟踪误差问题,提高系统的估计精度。Efficient and accurate state estimation is the basis for the safety and stability of the integrated energy system(IES).Particle filter has high precision and strong adaptability to nonlinear systems,and it has been applied to state estimation of power systems.To improve the precision of state estimation in IES,a forecasting-aided state estimation method based on improved particle filter is proposed.Firstly,a regional IES model including an electricity-heat-gas network is constructed.Secondly,the particle filter algorithm is applied to the electricity-heat-gas network.The prediction step of the particle filter is improved because of the tracking error problem of traditional particle filtering algorithm,which is based on particle filter theory.Finally,the improved particle filter algorithm is verified by using the classical IES example.The results show that this method can effectively solve the tracking error problem of the traditional particle filter algorithm,which can improve the precision of state estimation in IES.

关 键 词：综合能源系统 状态估计 粒子滤波算法 电-热-气网络 跟踪误差 预测辅助 

分 类 号：TM732[电气工程—电力系统及自动化]