Open Access
Issue |
MATEC Web Conf.
Volume 208, 2018
2018 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018)
|
|
---|---|---|
Article Number | 03002 | |
Number of page(s) | 4 | |
Section | Modern Electronic System & Measurement and Control Technology | |
DOI | https://doi.org/10.1051/matecconf/201820803002 | |
Published online | 26 September 2018 |
- A. Pazderin, V. Samoylenko, Localization of non-technical energy losses based on the energy flow problem solution. Proceedings of the 6th IASTED Asian Conference on Power and Energy Systems, AsiaPES 2013, pp.100–103, (2013). [Google Scholar]
- A. Egorov, E. Kochneva, A. Pazderin, Detection of systematical errors of AMR system complexes, Advanced Materials Research 960-961, pp 1342–46, (2014). [Google Scholar]
- A. Monticelli, F. F. Wu, M. Yen, Multiple Bad Data Identification for State Estimation by Combinatorial Optimization. Proceesings of the PICA Conference, pp. 452–460, (1985) [Google Scholar]
- X. Nian-De, W. Shi-Ying, Y. Er-Keng, A new approach for Detection and Identification of Multiple Bad Data in Power System State Estimation. IEEE Transactions on Power Systems, PAS-101, no. 2, pp.454–462, (1982). [CrossRef] [Google Scholar]
- F. Schweppe, J. Douglas, D. Rom, Power System State Estimation, Part I Exact Model, IEEE Transactions on Power Apparatus and Systems, PAS-89, pp. 120–125, (1970). [Google Scholar]
- A. Pazderin, S. Kokin, A. Egorov, E. Kochneva, Solution of energy flow problem using state estimation technique, ECON Proceedings (Industrial Electronics Conference), pp. 1736–41. [Google Scholar]
- Abur A, Exposito A G, Power System State Estimation. Marcel Dekker inc., New York, (2004) [Google Scholar]
- A. Gamm, I. Kolosok, Bad data detection in measurements in electric power system. Nauka, Novosibirsk, Sib. Enterpr. RAS, (in Russian), (2000). [Google Scholar]
- F. Schweppe, J. Douglas, D Rom, Power System State Estimation, Part II Approximate Model, IEEE Transactions on Power Apparatus and Systems, PAS-89, pp. 125–130, (1970). [CrossRef] [Google Scholar]
- A. Monticelli, Electric Power Syaytem State Estimation. Proceedings of the IEEE, vol. 88, no.2, pp. 262–282, (February 2000). [CrossRef] [Google Scholar]
- P. Chusovitin, I. Polyakov, A. Pazderin, Three-phase state estimation model for distribution grids. Proceedings of International Conference on the Science of Electrical Engineering ICSEE, (2016). [Google Scholar]
- E. Plesniaev, A. Pazderin, Data acquisition system faults detection. Proceedings of IEEE Conference on Contril Applications, pp.1390–94, (2003). [Google Scholar]
- E. Plesniaev, A. Pazderin, Analysis of the computation techniques for energy flow problem solving. Proceedings of the International Conference on Computer as a Tool II EUROPCON, pp.1469–1472, (2005). [Google Scholar]
- A. Pazderin, A. Egorov, S. Eroshenko. The energy meters allocation in electric systems on the basis of observability theory, Proceedings of 9th Conference on Environment and Electrical Engineering, EEEIC, pp. 167–170, (2010). [Google Scholar]
- A. Pazderin, E. Kochneva, Bad data validation on the basis of a posteriori analysis. Proceedings of the IEEE International Energy Conference ENERGYCON, pp. 386–391, (2014). [Google Scholar]
- RD 34.09.101-94. Typical instruction for electricity metering in its generation, transmission and distribution. M. ORGRES, S. (in Russian) (1995). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.