基于时域模型的电-气综合能源系统分布式鲁棒状态估计

Distributed Robust State Estimation of Integrated Electricity-Gas System Based on Time-domain Model

高效准确的状态估计(SE)技术是电-气综合能源系统(IEGS)安全稳定运行的关键。现有的IEGS-SE方法常采用有限元差分模型描述气网动态特性。该模型需引入冗余的时空微元,难以兼顾SE精度和计算复杂度。为此,提出一种基于时域模型的IEGS分布式鲁棒SE方法,在保证精度的前提下提升计算效率。首先,基于时域模型推导出以真实节点压强为状态量的气网状态空间模型,实现气网模型的简化和降维。在此基础上,以卡尔曼滤波算法为框架,提出有限边界信息交互的分布式IEGS-SE策略,以解决不同子系统多管理主体之间的信息壁垒问题。最后,利用噪声自适应算法准确跟踪时变噪声参数,提升所提方法的鲁棒性。仿真算例证明,所提方法在保护各子系统隐私的条件下,有效提高了SE精度,抑制了坏数据影响,且计算效率远高于传统有限元差分法。

Efficient and accurate state estimation(SE)technology is the key to the safe and stable operation of the integrated electricity-gas system(IEGS).The existing IEGS-SE methods often use the finite difference models to describe the dynamic characteristics of the gas network.The models need to introduce redundant space-time microelements,so it is difficult to take into account SE accuracy and computational complexity.Therefore,a distributed robust IEGS-SE method based on the time-domain model is proposed to improve the computational efficiency while ensuring accuracy.First,the state space model of the gas network with the real node pressure as the state variables is derived based on the time-domain model,realizing the simplification and dimension reduction of the gas network model.On this basis,taking the Kalman filter algorithm as a framework,a distributed IEGS-SE strategy with limited boundary information interaction is proposed to solve the problem of information barriers between multiple management agents in different subsystems.Finally,the noise adaptive algorithm is used to accurately track the timevarying noise parameters and improve the robustness of the proposed method.The simulation case demonstrates that the proposed method can effectively improve the SE accuracy and suppress the influence of bad data under the condition of protecting the privacy of each subsystem,and its computational efficiency is much higher than that of traditional finite difference methods.