An improved TPM-based distribution network state estimation considering loads/DERs correlations

Abedi, Bahman; Ghadimi, Ali Asghar; Abolmasoumi, Amir Hossein; Miveh, Mohammad Reza

doi:10.1007/s00202-020-01185-2

Cited by 6 publications

(7 citation statements)

References 49 publications

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“…Reference [28] considered the uncertainty of loads and renewable energy resources and the correlation between them in the distribution network SE, to estimate the states of a distribution network with high accuracy. Reference [29] described an approach for probabilistic SE modelling that captures both the uncertainties of loads/generations and the network.…”

Section: Literature Reviewmentioning

confidence: 99%

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A robust state estimation by optimal placement of measurement units considering loads/renewable generations and measurements uncertainty

Asadzadeh,

Tousi,

Galvani

et al. 2024

IET Renewable Power Gen

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The supervisory control and data acquisition (SCADA) system is one of the key requirements for monitoring the power systems state. The power system state is estimated from the state estimation (SE) function, which uses the measurements results from different points. Inaccurate estimation may cause inefficient management of power systems and making decisions. Usually, the number of measurement units (MUs) is limited so the optimal location of MUs is very important in successful and accurate state estimation. The optimal placement of MUs gets more complicated when the actual state of the power system is uncertain due to the high penetration of renewable generation and load uncertainties. Considering the power system's actual state uncertainty and measurement units’ inherent error, this work presents a probabilistic model for the uncertainty of measuring based on the K‐medoids data clustering technique. Then the probabilistic optimal placement of MUs is solved by a binary particle swarm optimization (PSO) method. Considering the mentioned uncertainties makes the obtained solution robust against all the probable scenarios. The proposed technique is implemented on the IEEE 14‐bus test system and the results are discussed. Results show the effectiveness of the proposed method in improving the accuracy of power system state estimation.

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Section: Literature Reviewmentioning

confidence: 99%

“…Also, a transformer between two ith and j th buses with active and reactive power flow measuring adds two expressions into (23). The corresponding expressions for X k, est i is according to ( 27) and (28).…”

Section: Conflict Of Interest Statementmentioning

confidence: 99%

A robust state estimation by optimal placement of measurement units considering loads/renewable generations and measurements uncertainty

Asadzadeh,

Tousi,

Galvani

et al. 2024

IET Renewable Power Gen

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show abstract

“…This represents the 13,88% where it can be found the analysis of uncertainties and correlations detailed in [9]. As well as load forecasting proposals with methods of load estimation [10] and allocating profiles [11], Markov model [9]. Finally, it must be mentioned criteria based on learning such as Artificial Neural Networks [12][13][14], Relevance Vector Machine (RVM) [15], and clustering techniques [16].…”

Section: Pseudo-measurementsmentioning

confidence: 99%

Bibliometric study of distribution system state estimation: advances and challenges

Lara-Sánchez,

Samper,

Colomé

2024

DYNA

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An active distribution network with a large amount of distributed energy resources (DER) requires knowledge of the operational status of the network. In this sense, state estimation is one of the most widely used techniques and a well-developed concept in transmission systems. DERs have some monitoring, protection, and control devices. But due to the large size of the network and the number of users, the massive installation of meters is not yet economically feasible. Therefore, it is necessary to generate artificial measurements to perform all stages of distribution system state estimation (DSSE). DSSE is currently the subject of active research, so this article performs a descriptive bibliometric study, which qualitatively and quantitatively analyzes the topics found in the specialized literature in the period from 2000 to 2022 and part of the 2023. It also identifies the advances, challenges, and proposals for future lines of research in DSSE.

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“…When it comes to transmission network operation, power flow [1], optimal power flow [2], optimal power flow [3], security analysis [4] and state estimation [5] are indispensable and important computational tools. Reference [1] proposed a robust and efficient LF solver based on the Bulirsch-Stoer algorithm, which solves the load-flow (LF) problem of super-large-scale systems and improves computational performance.…”

Section: Introductionmentioning

confidence: 99%

“…2021, 11, 7649 2 of 24 switching methodology to alleviate overloads with look-ahead capability, which provides a set of high-quality line switching solutions and improves speed (online application) and accuracy. Reference [5] proposed an improved probabilistic load and distributed energy resources (DERs) modeling as pseudo-measurements, which has the ability to estimate the states of the power grid with high accuracy and short computational time. These improved new technologies (especially the method proposed in reference [5]) enable the dispatching center to monitor and estimate the operating status of the entire power grid more accurately and quickly, providing feasibility for fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis System of Power Grid Based on Multi-Data Sources

Chen

Jin

et al. 2021

Applied Sciences

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In order to complete the function of power grid fault diagnosis accurately, rapidly and comprehensively, the power grid fault diagnosis system based on multi-data sources is proposed. The integrated system uses accident-level information, warning-level information and fault recording documents and outputs a complete diagnosis and tracking report. According to the timeliness of three types of information transmission, the system is divided into three subsystems: real-time processing system, quasi-real-time processing system and batch processing system. The complete work is realized through the cooperation between them. While a real-time processing system completes fault diagnosis of elements, it also screens out incorrectly operating protections and circuit breakers and judges the loss of accident-level information. Quasi-real-time system outputs reasons for incorrect actions of protections and circuit breakers under the premise of considering partial warning-level information missing. The batch processing system corrects diagnosis results of the real-time processing system and outputs fault details, including fault phases, types, times and locations of faulty elements. The simulation results and test show that the system can meet actual engineering requirements in terms of execution efficiency and fault diagnosis and tracking effect. It can be used as a reference for self-healing and maintenance of power grids and has a preferable application value.

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An improved TPM-based distribution network state estimation considering loads/DERs correlations

Cited by 6 publications

References 49 publications

A robust state estimation by optimal placement of measurement units considering loads/renewable generations and measurements uncertainty

A robust state estimation by optimal placement of measurement units considering loads/renewable generations and measurements uncertainty

Bibliometric study of distribution system state estimation: advances and challenges

Fault Diagnosis System of Power Grid Based on Multi-Data Sources

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