An Improved Differential Evolution algorithm for congestion management in the presence of wind turbine generators. (January 2018)

• Record Type: Journal Article
• Authors: Suganthi, S.T.; Devaraj, D.; Ramar, K.; Hosimin Thilagar, S.
• Is Part Of: Renewable & sustainable energy reviews. Volume 81:Part 1(2018)
• Page Start: 635
• Page End: 642
• Publication Date: 2018-01
• Subjects: Congestion management -- Generation rescheduling -- Wind Availability Factor -- Bus Sensitivity Factor -- Improved Differential Evolution; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2017.08.014
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: Congestion management is imperative for reliable and secure system operation in restructured power systems. Since the installation of wind farms at proper locations offers the possibility of congestion relief, this paper investigates congestion management in power systems with specific consideration of wind energy sources. The optimal location of a wind farm is determined by the Bus Sensitivity Factor and the Wind Availability Factor. Differential Evolution is a population-based heuristics algorithm used for solving non-linear optimization problems. We propose an Improved Differential Evolution based approach to ease congestion in transmission lines by generator rescheduling and installation of new wind farms. In this approach, an enhanced mutation operator is introduced to improve the performance of the Differential Evolution algorithm. A standard IEEE-30 bus system is used to evaluate the proposed algorithm under critical line outages. The simulation results show that the proposed approach is more effective than other approaches.