μμ΄λμ΄: νμμ & μμ°¨μ μμ΄ νμ
μμ΄λμ΄: κ΅μ μ΅λκ° κΈ°λ° μ΄μ§νλ₯Ό μ μ©ν μ΄μ° 곡κ°μ λν λ² μ΄μ§μ μ΅μ ν
To-Do-List
Issues
Related Work
Experimental Results
References
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A three-phase state estimation in active distribution networks, International Journal of Electric Power & Engergy Systems, 2014.
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Formulation of Three-Phase State Estimation Problem Using a Virtual Reference, IEEE Transactions on Power Systems, 2020.
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Identification of the phase connectivity in distribution systems through constrained least squares and confidence-based sequential assignment, International Journal of Electric Power & Engergy Systems, 2022.
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Three-phase state estimation in the medium-voltage network with aggregated smart meter data, International Journal of Electric Power & Engergy Systems, 2018.
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Three-Phase State Estimation of a Low-Voltage Distribution Network with Kalman Filter, Energies, 2021.
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Verification and estimation of phase connectivity and power injections in distribution network, Electric Power Systems Research, 2017.
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F. Olivier, A. Sutera, P. Geurts, R. Fonteneau, D. Ernst, Phase identification of smart meters by clustering voltage measurements, in: 2018
Power Systems Computation Conference (PSCC), IEEE, 2018, pp. 1β8
μ°Έκ³ λ¬Έν: μ μλ³
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(Olivier 2017) Automatic phase identification of smart meter measurement data, CIRED-Open Access Proceedings Journal
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(Deshwal 2022) Bayesian Optimization over Permutation Spaces, In AAAI.
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μμ΄ κ³΅κ°μμμ λ² μ΄μ§μ μ΅μ ν μκ³ λ¦¬μ¦ μ μ
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(Hashmi 2023) Consensus based phase connectivity identification for distribution network with limited observability.Β arXiv preprint arXiv:2301.03938.
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Consensus based optimization λ°©
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κ²μ¦μ μν΄ μ νλ κ΄μΈ‘ λ°μ΄ν°μ μ μ© κ°λ₯ν Monte Carlo Simulationμ μ μ©
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μ μλ³ κ΄λ ¨ μ°κ΅¬λ€μ 체κ³μ μΌλ‘ μ 리
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(Pezeshki 2012) Consumer phase identification in a three phase unbalanced lv distribution network, in ISGT Europe
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(Zhou 2020) Consumer phase identification in low-voltage distribution network considering vacant users
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vacant users(μΌμμ μΌλ‘ μ λ ₯ μ¬μ©μ μ€μ§νκ±°λ, μ¬μ© λ°μ΄ν°κ° λλ½λ κ³ κ°)λ₯Ό κ³ λ €ν μ μλ³ λ¬Έμ λ₯Ό λ€λ£Έ
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μκ³μ΄ μ°¨μ΄ μ ν λ³ μ ν©ν μ μ¬λ μΈ‘μ λ°©λ² μ μ
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(Izadi 2021) Improving Real-world Measurement-based Phase Identification in Power Distribution Feeders with a Novel Reliability Criteria Assessment, ISGT-Europe
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μμΆ κΈ°λ° μκ³μ΄ μ μ¬λ μΈ‘μ λ°©λ²
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(Hoogsteyn 2022) Low voltage customer phase identification methods based on smart meter data, arXiv preprint arXiv:2204.06372
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(Hosseini 2020) Machine learning-enabled distribution network phase identification.Β IEEE Transactions on Power Systems.
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(Wang 2016) Phase Identification in Electric Power Distribution Systems by Clustering of Smart Meter Data, 15th IEEE International Conference on Machine Learning and Applications.
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(Padullaparti 2022) Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data. InΒ 2022 IEEE Power & Energy Society General Meeting (PESGM)
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(Arya 2011) Phase Identification in Smart Grids, InΒ 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm)
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Load matching approach: Aggregated electricity consumptions of all customers 
Electrical loads of substation
Electrical loads of substationβ’
(Vycital 2019) Phase identification in smart metering pilot project komorany, in Int. Conf. on Electricity Distribution
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(Olivier 2018) Phase identification of smart meters by clustering voltage measurements, in Power Systems Computation Conference
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(Blakely 2020) Phase Identification Using Co-Association Matrix Ensemble Clustering, IET Smart Grid
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μ μλ³ λ°©λ²: Spectral Clustering + Co-association matrix
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(Xu 2016) Phase identification with incomplete data, IEEE Transactions on Smart Grid
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(Blakely 2019) Spectral Clustering for Customer Phase Identification Using AMI Voltage
Timeseries, In IEEE Power and Energy Conference at Illinois
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μ μλ³ λ°©λ²: Spectral Clustering κΈ°λ²
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(Kota 2015) Voltage Correlations in Smart Meter Data, in ACM SIGKDD.
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λ³μκΈ°, feeder (μ κ° μ λ‘?), μ κ°μ κ³μΈ΅μ μκ΄μ± λΆμμ ν΅ν μ μλ³ λ°©λ²
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(μ μ¬μ± 2019) Unit Root Testλ₯Ό κΈ°λ°μΌλ‘ ν μ₯κΈ° μκ³μ΄ λ°μ΄ν°μ Non-Stationary λ°μμ λ°λ₯Έ ꡬ쑰 λ³ν κ²μ λ° μκ°ν μ°κ΅¬, μ 보μ²λ¦¬νν λ
Όλ¬Έμ§
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ꡬ쑰 λ³ν κ²μ β μΆμΈ λ³ν ꡬκ°μ μλ³ β μ μλ³ κΈ°λ²μ μ μ© for ν¨μ¨μ κ³μ°
