NDLI: Optimal reliability evaluation method of bulk power system based on IGA

Content Provider	IEEE Xplore Digital Library
Author	Song Yunting Wang Quan Zhang Wenjuan
Copyright Year	2009
Description	Author affiliation: Nanjing Sino-German Protection & Substation Control System Ltd, Nanjing, 210003, China (Zhang Wenjuan) \|\| Power system department of China Electric Power Research Institute (CEPRI), Beijing, 100192, China (Song Yunting) \|\| China Electric Power Research Institute (CEPRI), Beijing, 100192, China (Wang Quan)
Abstract	Combined with risk indices of comprehensive reliability assessment and economic assessment theory, there may be trade-off between system installations cost and power interruption cost in the competitive power market environment. To coordinate reliability and economy, this paper proposed an overall framework of optimal reliability algorithm for bulk power system based on total owning cost (TOC). Interruption cost can be obtained through quantitative reliability indices of probabilistic security and probabilistic adequacy comprehensive evaluation based on Monte-Carlo simulation. Through applying improved genetic algorithm (IGA) to solving these kinds of complex discontinuous reliability optimization problems, the optimal reliability indices of components are obtained, which minimize the total owning cost comprising apparatus investment cost and interruption cost. A case study of the IEEE-RTS test system is presented to demonstrate the effectiveness and feasibility of the proposed algorithm. The proposed method is a valuable and powerful tool for power system planning, and it makes research results of reliability evaluation become more practical in the competitive market environment.
Starting Page	1
Ending Page	7
File Size	448954
Page Count	7
File Format	PDF
ISBN	9781424449347
DOI	10.1109/SUPERGEN.2009.5348326
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power system economics Power generation economics Reliability theory Power system security Environmental economics Monte-Carlo simulation Genetic algorithms Bulk power system Power system simulation Cost function Power markets Power system reliability Improved genetic algorithm Optimal reliability
Content Type	Text
Resource Type	Article

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