Determination of key transmission section and strong correlation section based on matrix aggregation algorithm

Wu, Wei; Yang, Dongsheng; Yu, Ziyang; Zhou, Bowen; Lv, Chen; Gu, Jie

doi:10.1016/j.ijepes.2023.109387

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…In practical engineering, after calculating the converged power flow, the system operator still needs to adjust the power of key transmission sections [29] and analyze the transient stability to determine the safe and stable operation boundary of the power grid.…”

Section: Actual Engineering Needsmentioning

confidence: 99%

Typical Power Grid Operation Mode Generation Based on Reinforcement Learning and Deep Belief Network

Wang,

Zhou,

et al. 2023

Sustainability

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With the continuous expansion of power grids and the gradual increase in operational uncertainty, it is progressively challenging to meet the capacity requirements for power grid development based on manual experience. In order to further improve the efficiency of the operation mode calculation, reduce the consumption of manpower and material resources, and consider the sustainability of energy development, this paper proposes a typical power grid operation mode generation method based on Q-learning and the deep belief network (DBN) for the first time. Firstly, the operation modes of different generator combinations located in different regions are obtained through Q-learning intelligent generation. Subsequently, the generated operation modes are clustered as different operation mode sets according to the data characteristics. Furthermore, comprehensive evaluation indexes are proposed from the perspectives of the steady state, transient state, and the economy. These multi-dimensional indexes are integrated via the analytical hierarchy process–entropy weight method (AHP-EWM) to enhance the comprehensibility of the evaluation system. Finally, DBN is introduced to construct a rapid operation mode evaluation model to realize the evaluation of operation mode sets, and typical operation mode sets are obtained accordingly. In this way, the system calculator only needs to compare the composite values to obtain the typical operation modes. The proposed method is validated by the Northeast Power Grid in China. The experimental results show that the proposed method can quickly generate typical power grid operation modes according to actual demand and greatly improve the efficiency of operation mode calculation.

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Section: Actual Engineering Needsmentioning

confidence: 99%

Typical Power Grid Operation Mode Generation Based on Reinforcement Learning and Deep Belief Network

Wang,

Zhou,

et al. 2023

Sustainability

Self Cite

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“…For the numerous transmission sections resulting from partitions, Liang et al (2022) employed N-1 and N-2 fault verification to identify sections at risk of exceeding limits as KTS. Wu et al (2023) utilized comprehensive indicators based on the line outage distribution factor and line load rate to determine KTS. The aforementioned methodology transforms the process of grid partitioning into a graph partitioning process.…”

Section: Introductionmentioning

confidence: 99%

The search method for key transmission sections based on an improved spectral clustering algorithm

Lin,

Liu

2024

Front. Energy Res.

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With the increased complexity of power systems stemming from the connection of high-proportion renewable energy sources, coupled with the escalating volatility and uncertainty, the key transmission sections that serve as indicators of the power grid’s security status are also subject to frequent changes, posing challenges to grid monitoring. The search method for key transmission sections based on an improved spectral clustering algorithm is proposed in this paper. A branch weight model, considering the impact of node voltage and power flow factors, is initially established to comprehensively reflect the electrical connectivity between nodes. Subsequently, a weighted graph model is constructed based on spectral graph theory, and an improved spectral clustering algorithm is employed to partition the power grid. Finally, a safety risk indicator is utilized to identify whether the partitioned sections are key transmission sections. Results from case studies on the IEEE39-node system and actual power grid examples demonstrate that the proposed method accurately and effectively searches for all key transmission sections of the system and identifies their security risks. The application in real power grid scenarios validates its ability to screen out some previously unrecognized key transmission sections.

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A novel fault diagnosis method for key transmission sections based on Nadam-optimized GRU neural network

Hu,

Lu,

Shi

et al. 2024

Electric Power Systems Research

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Determination of key transmission section and strong correlation section based on matrix aggregation algorithm

Cited by 3 publications

References 18 publications

Typical Power Grid Operation Mode Generation Based on Reinforcement Learning and Deep Belief Network

Typical Power Grid Operation Mode Generation Based on Reinforcement Learning and Deep Belief Network

The search method for key transmission sections based on an improved spectral clustering algorithm

A novel fault diagnosis method for key transmission sections based on Nadam-optimized GRU neural network

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