State Estimation for Integrated Energy System Containing Electricity, Heat and Gas

Man, Linkun; Wang, Tao; Li, Yuanyuan

doi:10.1109/ei2.2018.8582371

Cited by 11 publications

(2 citation statements)

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“…1. Flow continuity equation: The continuity of flow is shown as the flow that enters into a node is equal to the flow that leaves the node plus the flow consumed at the node: (8) whereṁ in andṁ out are the mass flow rate within a pipe coming into and leaving the node respectively;ṁ qi is the mass flow through each node injected from a source or discharged to a load.…”

Section: Hydraulic Modelmentioning

confidence: 99%

“…2. State estimation methods: In [8], the weighted least squares (WLS) method is used to estimate the state of the electricheat-gas coupled IES multi-energy flow model, but this method is complicated and not applicable to large-scale integrated energy system. In [9], a comprehensive mathematical analysis is presented to obtain accurate distribution network state estimation by using weighted least square estimation to find the most important factors affecting the accuracy of voltage curve.…”

Section: Introductionmentioning

confidence: 99%

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Robust state estimation of electricity‐gas‐heat integrated energy system based on the bilinear transformations

Chen

Yang

Wang

et al. 2020

IET Generation Trans & Dist

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A comprehensive energy system state estimation is of great significance to promote efficient, stable and reliable operation of the system. Based on coupling characteristics of electricity-gas-heat multi-energy flow and bilinear transformation method, this paper proposes a robust state estimation method suitable for integrated energy systems. First, the state estimation models of electricity, gas and heat energy subsystems and coupling components are constructed. Then, by introducing pseudo state variables and intermediate variables, the nonlinear state estimation process is divided into four stages. Among them, the first and third stages are solved by WLAV method and WLS method respectively, and the second and fourth stages are simple nonlinear transformation processes. Finally, the robust state estimation method is verified on a 40-node simulation example. The bilinear robust state estimation method proposed not only solves the difficulty of selecting initial values of heterogeneous networks and the problem of non-convergence of algorithms, but also can search and identify various types of bad data, and has high computational efficiency and good robustness.

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Section: Hydraulic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%