Zhigang Li;Wenjian Zheng;Junbo Zhao;J. H. Zheng;Q. H. Wu
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引用次数: 0
Abstract
Observability analysis (OA) is vital to obtaining the available input measurements of state estimation (SE) in an integrated electricity and heating system (IEHS). Considering the thermal quasi-dynamics in pipelines, the measurement equations in heating systems are dependent on the estimated results, leading to an interdependency between OA and SE. Conventional OA methods require measurement equations be known exactly before SE is performed, and they are not applicable to IEHSs. To bridge this gap, a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency. As its core procedure, the observable state identification and observability restoration are formulated in terms of integer linear programming. Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.
可观测性分析(OA)对于获得综合电力和供热系统(IEHS)中状态估计(SE)的可用输入测量值至关重要。考虑到管道中的热准动力学,供热系统中的测量方程取决于估计结果,从而导致 OA 和 SE 之间的相互依存关系。传统的 OA 方法要求在执行 SE 之前准确知道测量方程,因此不适用于 IEHS。为了弥补这一缺陷,我们为 IEHS 设计了一种基于情景的 OA 方案,该方案可为一组预定义的时延情景提供可靠的分析结果,以应对这种相互依赖关系。作为其核心程序,可观测状态识别和可观测性恢复是通过整数线性规划来实现的。为证明所提方案的有效性和优越性,进行了数值测试。
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.