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

Chen, Qiuyue; Yang, Dechang; Wang, Yaning; Rehtanz, Christian; Pandžić, Hrvoje

doi:10.1049/gtd2.12037

Cited by 16 publications

(10 citation statements)

References 13 publications

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“…Weighted least squares (WLS) is a common SE method, but it is susceptible to system redundancy. In [5] and [6], robust SE based on weighted least absolute value (WLAV) can guarantee accuracy when the measurements contain bad data. A robust SE method that uses second-order cones and targeting WLAV is proposed, which significantly improves the accuracy of nonlinear IES compared to WLS [7].…”

Section: Introductionmentioning

confidence: 99%

A dynamic state estimation method for integrated energy system based on radial basis kernel function

Chen,

Luo,

Foo

et al. 2024

Meas. Sci. Technol.

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For state estimation of dynamic electro-thermal gas coupled systems, measurements usually assume that the measurement noise obeys a Gaussian distribution. The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are some of the widely used estimation methods in state estimation. However, the measurement noise does not always follow Gaussian distribution in practice. When the measurement noise is non-Gaussian, the performance of these methods may not be satisfactory. In this paper, we propose an unscented Kalman filtering method based on minimising radial basis kernel function criterion (MRBFC-UKF), which explores the optimal values of the shape parameters of the kernel function instead of using the widely used Gaussian and exponential kernal functions. Simulations are run dynamically in an integrated energy system which comprises an IEEE 14-bus, a 20-node natural gas network and a 32-node local thermal network. The results show that the proposed method has good robustness and accuracy, and can effectively cope with the presence of unexpected bad data inputs.

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Section: Introductionmentioning

confidence: 99%

A dynamic state estimation method for integrated energy system based on radial basis kernel function

Chen,

Luo,

Foo

et al. 2024

Meas. Sci. Technol.

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“…Kong built a green mixed integer linear programming model in order to construct an integrated optimised gas system considering economics, energy consumption, and environment [14]. Based on coupling characteristics of electricity-gas-heat multi-energy flow and bilinear transformation method, Chen et al proposed a robust state estimation method suitable for integrated energy systems [15]. Wang et al proposed a multi-objective expansion planning model for park-level integrated energy system [16].…”

Section: Introductionmentioning

confidence: 99%

“…Based on coupling characteristics of electricity‐gas‐heat multi‐energy flow and bilinear transformation method, Chen et al. proposed a robust state estimation method suitable for integrated energy systems [15]. Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Coordination optimisation of energy and manufacturing flow for industry integrated energy system

Liu

Gao

2022

IET Generation Trans & Dist

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With the breaking down of information barriers between energy flow with manufacturing flow, the coordination between them is an effective way to relieve the dual pressure from energy and environment industrial integrated energy system. The authors develop a scenario‐based coordination model for energy flow and manufacturing flow to make full use of the flexibilities of energy supply and production process to reduce energy cost. To capture the flexibility in the energy flow, the authors enhance an electricity‐steam‐product gas–gas storage coupling energy flow model considering multi‐uncertainties. The authors also develop a batch process model to formulate the flexibility in the production process. Based on the batch energy consumption constraints, the energy flow model and the batch process model are integrated as a coordination model. To ensure the feasibility of hard budget constraints under all possible random realisations, we add all‐scenario‐feasibility robust constraints which are infinite‐dimensional constraints into the model. To solve the model, a vertex scenario set based on the characteristics of convex optimisation is constructed to equivalently convert infinite‐dimensional constraints to finite‐dimensional constraints. In this way, the coordination model is transformed to a mixed integer linear programming and can be solved using CPLEX. Finally, numerical test based on a real iron and steel plant is analysed. The results show that coordination between energy with manufacturing flow is effective to reduce the energy cost and carbon emission. Compare with only optimising energy flow, the coordination model can reduce total cost about 221.6 thousand RMB and 304.44t coal every day.

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“…Both static state estimation and dynamic state estimation are essential tools for IES situational awareness. Reference [11] proposes a static state estimation method for heat gas and electricity coupled systems based on WLS and weighted least absolute value (WLAV). WLAV is also employed to establish a bilinear IES state estimation framework in [12] to improve robustness.…”

Section: Introductionmentioning

confidence: 99%

A real‐time state estimation framework for integrated energy system considering measurement delay

et al. 2022

IET Generation Trans & Dist

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The increasingly close connections between multiple heterogeneous energy subsystems, the integrated energy system (IES) will play a critical role in ensuring future energy generations and distributions. As an essential function of the energy management system, state estimation provides data support for energy management of IES. Unfortunately, the existing IES state estimation method does not consider the measurement delay, which is inconsistent with the measurement delay characteristics caused by the multi‐timescale characteristics of IES. Driven by this motivation, this paper proposes a real‐time state estimation framework for the gas‐electricity coupled system. Considering the characteristics of the gas pipelines and coupling elements, the dynamic model of the natural gas system is established. A dynamic state estimation algorithm to enhance numerical stability is adopted to solve the problem that real‐time estimation based on the traditional Kalman filter suffers from the curse of dimensionality. Finally, a modified unscented Kalman filter (UKF) based estimation method is designed based on unified time processing and delay noise synthesizing. The IEEE 39‐bus electrical system and the 20‐node Belgian gas system are coupled to form the test system in this paper. The case study shows the advantages of the proposed method in efficiency and accuracy compared with the existing methods.

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

Cited by 16 publications

References 13 publications

A dynamic state estimation method for integrated energy system based on radial basis kernel function

A dynamic state estimation method for integrated energy system based on radial basis kernel function

Coordination optimisation of energy and manufacturing flow for industry integrated energy system

A real‐time state estimation framework for integrated energy system considering measurement delay

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