[Poster Presentation]Power System Reliability Assessment With Offshore Wind Farms

Power System Reliability Assessment With Offshore Wind Farms
ID:36 Submission ID:105 View Protection:ATTENDEE Updated Time:2021-12-03 10:31:17 Hits:407 Poster Presentation

Start Time:2021-12-17 15:00 (Asia/Shanghai)

Duration:5min

Session:[Z] Poster Session » [Z1] Poster Session 1: Renewable energy system

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Abstract
Wind power is one of the more effective ways to solve the energy crisis and environmental pollution problems. Compared with onshore wind power, offshore wind power has a good prospect for development because of its advantages of saving land resources and stable and abundant wind energy. As the installed capacity of offshore wind power is gradually increasing in the power system, it is especially important to analyze the reliability of power systems containing offshore wind power farms. The method first predicts the wind speed of offshore wind farms based on historical data using ARMA algorithm, and establishes an offshore wind farm output model. Then, a sequential Monte Carlo method and a modified RBTS test system are used to analyze and compare the reliability of the power system with offshore wind power system under the influence of wind speed characteristics, offshore wind turbine and cable failure, onshore unit failure, and onshore load. Finally, the correctness and practicality of the proposed method are verified by simulation. The simulation and analysis results show that the proposed method can provide some reference for offshore wind farm planning.

 
Keywords
reliability assessment, sequential Monte Carlo algorithm, multiple influencing factors, offshore wind farm, onshore grid
Speaker
Feixiang Ying
Shanghai University of Electric Power

Submission Author
Feixiang Ying Shanghai University of Electric Power
Lingling Huang Shanghai University of Electric Power
Jintao Yan Shanghai University of Electric Power
Yang Liu Shanghai University
Qiguo Wang Shanghai University of Electric Power
Yuzhi Miao Shanghai University of Electric Power
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