Improving Power System State Estimation Based on Matrix-Level Cleaning

Yang, Haosen; Qiu, Robert C.; Chu, Lei; Mi, Tiebin; Shi, Xin; Liu, Chaoyuan Mary

doi:10.1109/tpwrs.2020.2984926

Cited by 25 publications

(6 citation statements)

References 31 publications

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“…There are two different approaches providing the solution. The first one is the vector space transformation by means of different methods [23].…”

Section: A Obtaining Nodal Power Distribution Probabilitiesmentioning

confidence: 99%

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Distribution Grid Future Planning Under Uncertainty Conditions

Samoylenko¹,

Firsov²,

Pazderin³

et al. 2024

RE&PQJ

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The paper presents an approach for making decisions about the future development of a distribution grid under uncertainty conditions. The levels of a grid hosting capacity and adequacy are examined using probabilistic approach compared to the conventional deterministic fit-andforget approach. It is shown that the probabilistic approach according to the 99 % confidence probability saves significant costs in comparison with the deterministic approach. The probabilistic calculations prove the use of an equipment rated capacity downsized by 2 points of a typical IEC scale, and in some cases to refuse the construction of a parallel circuit. The main contribution of the paper is a method for choosing an effective rated voltage of a distribution grid in a probabilistic interpretation based on the conventional formulas of Still, Zalessky and Illarionov. The technique includes obtaining the probability of loads location at different distances from power supply centre and the probability of load power distribution in a given range of values. It is shown that the calculation using the developed method makes possible to prefer grid rated voltage at least 1 point downsized by IEC scale with sufficient savings due to the difference in the equipment price compared with the deterministic fit-and-forget approach.

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“…There are two different approaches providing the solution. The first one is the vector space transformation by means of different methods [23].…”

Section: A Obtaining Nodal Power Distribution Probabilitiesmentioning

confidence: 99%

“…Further calculations can be made using one of the steadystate calculation methods [23]. This work uses current balance-based equations of state parameters.…”

Section: A Obtaining Nodal Power Distribution Probabilitiesmentioning

confidence: 99%

Distribution Grid Future Planning Under Uncertainty Conditions

Samoylenko¹,

Firsov²,

Pazderin³

et al. 2024

RE&PQJ

View full text Add to dashboard Cite

show abstract

“…State estimation (SE) provides a view of real-time power system conditions for the system operator to efficiently and reliably operate the power grid [1][2][3], plays an important role in the monitoring and management of the power system. The requirements of data privacy in each control center and the heavy calculation load make it more and more difficult for integrated state estimation (ISE) to adapt to large-scale network.…”

Section: Introductionmentioning

confidence: 99%

A Robust Distributed State Estimation of AC/DC System With LCC-HVDC Tie Line

Zhang,

Qi,

Wang

2023

IEEE Access

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A robust distributed state estimation algorithm for AC/DC system with AC tie lines and high voltage direct current (LCC-HVDC) tie lines is proposed. The proposed algorithm consists of robust DC state estimation in the coordinator and robust distributed AC state estimation, and implements sequential solving by exchanging coupling variables of the AC/DC system. For AC state estimation, a distributed state estimation algorithm based on the bilinear algorithm is designed, which can achieve the same accuracy as the centralized algorithm. Robust state estimator based on the exponential absolute value function and exponential square function is suitable for reducing the influence of outliers and can reduce the operation scale by simplifying the nonlinear iterative process in distributed state estimation. Finally, the correctness and effectiveness of the algorithm is verified by simulation of three IEEE 118 bus systems interconnected through AC/DC hybrid tie lines.

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“…Yet, this approach may not be apt for intricate distribution networks operating autonomously. Reference [25] presents a method rooted in stochastic matrix theory for data-driven matrix level measurement error cleansing. This approach employs WLS to construct a two-tiered state estimation scheme.…”

Section: Introductionmentioning

confidence: 99%

A Distribution Network State Estimation Method With Non-Gaussian Noise Based on Parallel Particle Filter

Ma,

Sheng,

Liu

2023

IEEE Access

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The particle filter (PF) algorithm is a powerful method for tackling non-Gaussian noise interference in distribution network state measurement. However, this algorithm suffers from slow solving speed and lengthy calculation time. To overcome this, a state estimation method based on parallel particle filter (PPF) is proposed, which leverages the independent computation features of each particle in the PF model to improve computational efficiency. This study utilizes the parallel architecture of Compute Unified Device Architecture (CUDA) and General Purpose Graphics Processing Units (GPGPU) to establish a oneto-one correspondence between particles and computing threads. An improved rejecting-resampling method is introduced to solve the problem of low execution efficiency caused by unmerged access to GPGPU memory. In addition, according to the relationship between the particle number and estimation accuracy of state variable of the PPF, the optimal particle number suitable for parallel computation is solved. Ultimately, the simulation results indicate that the proposed method can be used to effectively filter the non-Gaussian-colored noises from the collected data, which meets the requirements of the distribution network state estimation for the accuracy and real-time performance.

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Improving Power System State Estimation Based on Matrix-Level Cleaning

Cited by 25 publications

References 31 publications

Distribution Grid Future Planning Under Uncertainty Conditions

Distribution Grid Future Planning Under Uncertainty Conditions

A Robust Distributed State Estimation of AC/DC System With LCC-HVDC Tie Line

A Distribution Network State Estimation Method With Non-Gaussian Noise Based on Parallel Particle Filter

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