High-Performance Sequential Analysis in Grid Automated Systems of Distributed-Generation Areas

This paper analyzes the electrical parameters of areas that contain distributed generation facilities. It demonstrates the necessity of stricter requirements to the performance of energy system automated systems, especially in island operation. It is noted that implementing a special procedure for t...

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Vydáno v:	Russian electrical engineering Ročník 92; číslo 2; s. 90 - 96
Hlavní autoři:	Kulikov, A. L., Ilyushin, P. V., Loskutov, A. A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Moscow Pleiades Publishing 01.02.2021 Springer Nature B.V
Témata:	Algorithms Automation Decision analysis Decision making Distributed generation Engineering Load shedding Machines Manufacturing Processes Sequential analysis power area distributed generation modified algorithm energy system automated system underfrequency load-shedding Wald sequential analysis
ISSN:	1068-3712, 1934-8010
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Abstract	This paper analyzes the electrical parameters of areas that contain distributed generation facilities. It demonstrates the necessity of stricter requirements to the performance of energy system automated systems, especially in island operation. It is noted that implementing a special procedure for truncating the standard sequential analysis (Wald analysis) for automated decision-making is a time-consuming process. By ensuring the constancy of first- and second-kind errors at each step of the Wald analysis, one can generate adaptable settings. The paper uses evidence from an automated underfrequency load shedding unit to show that a modified sequential analysis algorithm performs twice as fast. The authors present guidelines on how to adopt this modified algorithm in existing or newly developed energy system automated systems.
AbstractList	This paper analyzes the electrical parameters of areas that contain distributed generation facilities. It demonstrates the necessity of stricter requirements to the performance of energy system automated systems, especially in island operation. It is noted that implementing a special procedure for truncating the standard sequential analysis (Wald analysis) for automated decision-making is a time-consuming process. By ensuring the constancy of first- and second-kind errors at each step of the Wald analysis, one can generate adaptable settings. The paper uses evidence from an automated underfrequency load shedding unit to show that a modified sequential analysis algorithm performs twice as fast. The authors present guidelines on how to adopt this modified algorithm in existing or newly developed energy system automated systems.
Author	Kulikov, A. L. Ilyushin, P. V. Loskutov, A. A.
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Cites_doi	10.1007/BF00587355 10.1137/1110078 10.1214/aoms/1177705996 10.1109/EPEPEMC.2014.6980544 10.1109/CVPR.2005.373
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Copyright	Allerton Press, Inc. 2021. ISSN 1068-3712, Russian Electrical Engineering, 2021, Vol. 92, No. 2, pp. 90–96. © Allerton Press, Inc., 2021. Russian Text © The Author(s), 2021, published in Elektrotekhnika, 2021, No. 2, pp. 34–41.
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References	Bussgang, J.J. and Marcus, M.B., Truncated Sequential Hypothesis Tests: Memorandum RM-4268-APRA, Santa Monica, CA: Rand Corp., 1964. WaldA.Sequential Analysis1947New YorkWiley0029.15805 Aivazyan, S.A., Distinguishing of close hypotheses about the fensity of the distribution in the scheme of the generalized sequential criterion, Teor. Veroyatn. Ee Primen., 1965, vol. 10, no. 4. Anderson, T.W., A modification of the sequential probability ratio tests to reduce the sample size, Ann. Math. Stat., 1960, vol. 31. Davarifar, M., Rabhi, A., Hajjaji, A., and Daneshifar, Z., Real-time diagnosis of PV system by using the sequential probability ratio test (SPRT), Proc. 16th Int. Power Electronics and Motion Control Conf. and Exposition, Antalya, Turkey, September 21–24, 2014, Piscataway, NJ: Inst. Electr. Electron. Eng., 2014. Lorden, G., Structure of sequential tests minimizing an expected sample size, Z. Wahrscheinlichkeitstheor. Verw. Geb., 1980, vol. 51, no. 3. Kulikov, A.L. and Ilyushin, P.V., Application of the Wald sequential procedure for automatic control of the modes of power districts with distributed generation facilities, Energetik, 2019, no. 6. Basharinov, A.E. and Fleishman, B.S., Metody statisticheskogo posledovatel’nogo analiza i ikh radiotekhnicheskie prilozheniya (Statistical Sequential Analysis and Its Radio Engineering Application), Moscow: Sovetskoe Radio, 1962. Shiryaev, A.N., Statisticheskii posledovatel’nyi analiz. Optimal’nye pravila ostanovki (Statistical Sequential Analysis. Optimal Terminal Rules), Moscow: Nauka, 1976. Sochman, J. and Matas, J., Waldboost-learning for time constrained sequential detection, Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Piscataway, NJ: Inst. Electr. Electron. Eng., 2005, vol. 2. FuK.-S.Sequential Methods in Pattern Recognition and Machine Learning1968AmsterdamElsevier0188.52303 K.-S. Fu (1360_CR11) 1968 A. Wald (1360_CR1) 1947 1360_CR7 1360_CR6 1360_CR10 1360_CR9 1360_CR8 1360_CR3 1360_CR2 1360_CR5 1360_CR4
References_xml	– reference: Anderson, T.W., A modification of the sequential probability ratio tests to reduce the sample size, Ann. Math. Stat., 1960, vol. 31. – reference: Lorden, G., Structure of sequential tests minimizing an expected sample size, Z. Wahrscheinlichkeitstheor. Verw. Geb., 1980, vol. 51, no. 3. – reference: Basharinov, A.E. and Fleishman, B.S., Metody statisticheskogo posledovatel’nogo analiza i ikh radiotekhnicheskie prilozheniya (Statistical Sequential Analysis and Its Radio Engineering Application), Moscow: Sovetskoe Radio, 1962. – reference: FuK.-S.Sequential Methods in Pattern Recognition and Machine Learning1968AmsterdamElsevier0188.52303 – reference: Sochman, J. and Matas, J., Waldboost-learning for time constrained sequential detection, Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Piscataway, NJ: Inst. Electr. Electron. Eng., 2005, vol. 2. – reference: Bussgang, J.J. and Marcus, M.B., Truncated Sequential Hypothesis Tests: Memorandum RM-4268-APRA, Santa Monica, CA: Rand Corp., 1964. – reference: Kulikov, A.L. and Ilyushin, P.V., Application of the Wald sequential procedure for automatic control of the modes of power districts with distributed generation facilities, Energetik, 2019, no. 6. – reference: WaldA.Sequential Analysis1947New YorkWiley0029.15805 – reference: Davarifar, M., Rabhi, A., Hajjaji, A., and Daneshifar, Z., Real-time diagnosis of PV system by using the sequential probability ratio test (SPRT), Proc. 16th Int. Power Electronics and Motion Control Conf. and Exposition, Antalya, Turkey, September 21–24, 2014, Piscataway, NJ: Inst. Electr. Electron. Eng., 2014. – reference: Aivazyan, S.A., Distinguishing of close hypotheses about the fensity of the distribution in the scheme of the generalized sequential criterion, Teor. Veroyatn. Ee Primen., 1965, vol. 10, no. 4. – reference: Shiryaev, A.N., Statisticheskii posledovatel’nyi analiz. Optimal’nye pravila ostanovki (Statistical Sequential Analysis. Optimal Terminal Rules), Moscow: Nauka, 1976. – ident: 1360_CR4 – ident: 1360_CR6 – ident: 1360_CR2 – volume-title: Sequential Methods in Pattern Recognition and Machine Learning year: 1968 ident: 1360_CR11 – ident: 1360_CR8 doi: 10.1007/BF00587355 – ident: 1360_CR9 doi: 10.1137/1110078 – volume-title: Sequential Analysis year: 1947 ident: 1360_CR1 – ident: 1360_CR5 doi: 10.1214/aoms/1177705996 – ident: 1360_CR10 – ident: 1360_CR3 doi: 10.1109/EPEPEMC.2014.6980544 – ident: 1360_CR7 doi: 10.1109/CVPR.2005.373
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SubjectTerms	Algorithms Automation Decision analysis Decision making Distributed generation Engineering Load shedding Machines Manufacturing Processes Sequential analysis
Title	High-Performance Sequential Analysis in Grid Automated Systems of Distributed-Generation Areas
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