Hybrid Measurements-Based Fast State Estimation for Power Distribution System

He, Xi; Chang, Li Fung; Du, Min; Dong, Heng; Li, Peng

doi:10.1109/access.2021.3055223

Cited by 16 publications

(15 citation statements)

References 30 publications

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“…The measured data are collected up to the rate of 60 samples per second and transmitted to the control centre Amplitude: up to 0.1% Degree: up to 0.02% for the phase [8][9][10][18][19][20][21] Measurement of distributed generation…”

Section: Challenges and Statement Of The Problemmentioning

confidence: 99%

“…To model short-term load variations and the changes resulting from waiting in the processing queue in the proposed method, the values of standard deviation and mean are first calculated based on the old data. Whenever the ADSSE process is performed, the variance of each measurement is calculated and corrected by Equations ( 15)- (18). Hence, the R matrix is updated.…”

Section: Voltage Phasor Measured By Pmusmentioning

confidence: 99%

“…The data are measured, recorded, and transmitted hourly, daily, weekly or monthly Between 10% and 20% [6,7,18,20,21] Phasor measurement unit Installed at the network bus bars, measured via signal synchronizer, the voltage phasor of the bus bars and current phasor of the lines connected to the bus bars…”

Section: Challenges and Statement Of The Problemmentioning

confidence: 99%

“…Then, a robust SE model based on weighted least absolute values (WLAV) for IEHS is proposed. In [18] is proposed the incorporation and process of the multi‐source measurements and a fast three‐phase SE based on the hybrid measurements scheme. By the process of Micro Phasor Measurement Unit (μPMU) measurements, pseudo voltage measurements are added, which significantly increases the estimation redundancy.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Improving state estimation accuracy in active distribution networks by coordinating real‐time and pseudo‐measurements considering load uncertainty

Ajoudani

Shiekholeslami

Zakariazadeh

2022

IET Generation Trans & Dist

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Measurements at the level of active distribution networks can be classified into three major groups. Data collection and transmission involve the time interval of several seconds for the first category, several minutes to 24 h for the second category, and finally, several weeks to several months for the third category. Considering this three-level classification of the measurements, state estimation by these data should deal with three kinds of heterogeneous data, but it has undesirable effects on the state estimation process, such as lower accuracy of the results. Despite the existence of heterogeneous data and different time rates, this study presents a state estimation model for updating measurement devices in each of the categories, aiming at establishing coordination among the measured data and increasing the accuracy of the estimation. The opportunities and limitations of the proposed model are compared to those of the conventional models. To illustrate the effectiveness of the proposed method, two IEEE standard systems 34-bus and 123-bus, have been used. The experimental network includes various load patterns, as well as distributed generation sources whose uncertainty is considered in the proposed model. 1Various measurement devices are currently installed on distribution networks. They are compared in Table 1.

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Section: Challenges and Statement Of The Problemmentioning

confidence: 99%

Section: Voltage Phasor Measured By Pmusmentioning

confidence: 99%

Section: Challenges and Statement Of The Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improving state estimation accuracy in active distribution networks by coordinating real‐time and pseudo‐measurements considering load uncertainty

Ajoudani

Shiekholeslami

Zakariazadeh

2022

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…The hybrid weighted least squares state estimation algorithm based on PMU and SCADA is proposed in the study by Skok et al (2016), Silva et al (2017), and Santos and Orillaza (2018) for the three-phase unbalanced distribution network system, which not only ensures the global observability of the system, but also satisfies the economy and improves the accuracy of state estimation. A fast three-phase state estimation method based on hybrid measurements is proposed in He et al (2021). The redundancy of state estimation is significantly increased by increasing the voltage pseudo-measurements through μPMU measurements.…”

Section: Introductionmentioning

confidence: 99%

Research on μPMU Configuration Optimization Considering Multiple Operation Modes of Distribution Network

Liang

Wang

et al. 2022

Front. Energy Res.

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A micro-phasor measurement unit (μPMU) configuration optimization approach is proposed in this article, considering the numerous operation modes of distribution network reconfiguration. The PSO algorithm with dynamic adaptability is used to optimize the setup of μPMU and improve the accuracy of state estimation for each distribution network operation mode. The configuration nodes of various operation modes are grouped and assessed by K-means according to the shortest distance, and the weights of the evaluation indexes are calculated by the AHP-CRITIC subjective and objective combination weighting method. The node with the highest comprehensive evaluation index is selected as the configuration node. The probability of multiple operation modes is then introduced. Finally, using the IEEE 118-bus distribution system as an example, the simulation demonstrates the proposed method’s effectiveness in improving distribution network state estimate.

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Low and medium voltage distribution network planning with distributed energy resources: a survey

Pham,

Shah,

Dao

et al. 2024

Electr Eng

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The penetration of distributed energy resources (DERs) such as photovoltaic systems, energy storage systems, and electric vehicles is increasing in the distribution system. The distinct characteristics of these resources, e.g., volatility and intermittency, introduce complexity in operation and planning of the distribution system. This paper first summarized the physical characteristics and morphological evaluation of the current and future distribution networks. Then, the impact of these changes on system operation and planning is outlined. Next, the tools, methods, and techniques for energy forecasting, optimal planning, and distribution system state estimation are reviewed and discussed, along with the challenges. As the main contributions, this research systematically organized the published works and assessed the relevant milestones regarding distribution system planning with DERs and emerging technologies. Finally, the key research directions in this domain are outlined. Graphical abstract

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Hybrid Measurements-Based Fast State Estimation for Power Distribution System

Cited by 16 publications

References 30 publications

Improving state estimation accuracy in active distribution networks by coordinating real‐time and pseudo‐measurements considering load uncertainty

Improving state estimation accuracy in active distribution networks by coordinating real‐time and pseudo‐measurements considering load uncertainty

Research on μPMU Configuration Optimization Considering Multiple Operation Modes of Distribution Network

Low and medium voltage distribution network planning with distributed energy resources: a survey

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