A Randomized Algorithm for Chance Constrained Optimal Power Flow with Renewables. Issue 4 (1st July 2017)

• Record Type: Journal Article
• Authors: Wada, Takayuki; Morita, Ryosuke; Asai, Toru; Masubuchi, Izumi; Fujisaki, Yasumasa
• Is Part Of: SICE journal of control, measurement, and system integration. Volume 10:Issue 4(2017)
• Page Start: 303
• Page End: 309
• Publication Date: 2017-07-01
• Subjects: Randomized algorithms -- optimal power flow -- chance constrained programming -- renewable power sources
• DOI: 10.9746/jcmsi.10.303
• Languages: English
• ISSNs: 1882-4889

Abstract

Abstract : A chance constrained AC optimal power flow is to find the optimal economic operation plan whose probability satisfying AC power flow equations and various inequality constraints on operating limits of the power system is greater than a specified probability level. Even if a constraint condition for each uncertain power supply value is convex with respect to decision variables, the chance constrained problem is not convex in general. Thus, it is difficult to solve the problem within reasonable computational time. Employment of randomization techniques for this issue is proposed in this paper. A main advantage of the framework leads to a solution with a theoretical guarantee. Its sample complexities are of polynomial order for parameters of a given accuracy. The efficiency of this algorithm is demonstrated by applying it to the Japanese power system models.