The use of regression models for estimating the standards of electric power losses in its transfer by territorial network companies


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Abstract

The paper deals with the issue of forecasting electric power losses for a five-year period in conditions of RAB-regulation. The use of multicriteria regression analysis and systems of visualisation of the obtained data in order to take well-founded decisions is proposed.

About the authors

V. Goldshtein

Samara State Technical University

Author for correspondence.
Email: aees@rambler.ru

Doctor of Science (Engineering), Professor

Automated Electrical Power Systems Department

Russian Federation

Yu. Kubarkov

Samara State Technical University

Email: tsara.cuba@yandex.ru

Candidate of Science (Engineering), Associate Professor

Power Plants Department

Russian Federation

A. Rygalov

Samara State Technical University

Email: alexeixox@gmail.com

Postgraduate student

Power Plants Department

Russian Federation

E. Revyakina

Samara State Technical University

Email: aees@rambler.ru

Student

Automated Electrical Power Systems Department

Russian Federation

V. Stepanov

Samara State Technical University, Samara, Russian Federation

Email: aees@rambler.ru

Postgraduate Student

Automated Electrical Power Systems Department

Russian Federation

References

  1. The Federal law of 26.03.2003 N 35-FZ (an edition of 06.12.2011) «About power industry» (with amendment and addi-tions, coming into force from 06.01.2012).
  2. No. 347-e/4 order FST of 04.12.2009.
  3. Methodical instructions on the cal-culation of adjustable tariffs and prices of electric (thermal) energy in the retail market. Resolution of Federal Energy Regulatory Commission of the Russian Federation of 31.07.2002 No. 49-E/8. List of changes and additions. Resolution of Federal Energy Regulatory Commission of Russia of May 14, 2003. No. 37-E/1.
  4. Strizhov V.V., Krymova E.A. Metody vybora regressionnykh modeley [Methods of a choosing regression models]. Moscow: VTs RAN Publ, 2010. 60 p.
  5. Dreyper N., Smith G. Prikladnoy regressionnyy analiz [Applied regression analysis]. Moscow: Vilyams publishing house. 2007.

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