Reliability assessment of power systems with wind power generation

Author

Wang, S. ; Baran, M.E.

Author_Institution

ABB Grid Syst., Raleigh, NC, USA

fYear

2010

fDate

25-29 July 2010

Firstpage

1

Lastpage

8

Abstract

The paper focuses on reliability assessment of power systems with wind power generation. A Monte Carlo based production cost simulation model is introduced in the paper. The model closely simulates actual system operation processes and takes system random behaviors into account. A simplified unit commitment method is created to fit the simulation for reliability evaluation purpose. The effects of wind forecast error is addressed in the model by applying forecasted value in day-ahead unit commitment and actual value in real-time operation. An Auto-Regressive Moving Average (ARMA) based process is designed to automatically perform day-ahead hourly wind generation forecasting through the simulation period. Numerical results of a 50-unit system case study are presented.

Keywords

Monte Carlo methods; autoregressive moving average processes; power generation dispatch; power generation reliability; power generation scheduling; wind power plants; ARMA based process; Monte Carlo simulation model; autoregressive moving average process; day-ahead hourly wind generation forecasting; day-ahead unit commitment; power system reliability assessment; production cost simulation model; reliability evaluation simulation; system random behaviors; unit commitment method; wind forecast error effect; wind power generation; Auto-Regressive Moving Average; Monte Carlo Simulation; Power System Reliability; Unit Commitment; Wind Power Generation;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Society General Meeting, 2010 IEEE

Conference_Location

Minneapolis, MN

ISSN

1944-9925

Print_ISBN

978-1-4244-6549-1

Electronic_ISBN

1944-9925

Type

conf

DOI

10.1109/PES.2010.5590079

Filename

5590079