COMPUTATIONALLY EFFICIENT METHOD FOR MULTI-OBJECTIVE RISK-LIMITING OPTIMAL POWER FLOW PROBLEMS
Shin-Yeu Lin, Yu-Syuan Cheng
Pages: 20-27
Published: 6 Sep 2018
Views: 1,471
Downloads: 222
Abstract: To balance the non-renewable power generation cost and the risk of violating security constraints in the presence of uncertain renewable power generation, a multi-objective risk-limiting optimal power flow (MORLOPF) problem is presented in this paper. To tackle this problem, a curve fitting based computationally efficient method is proposed. Simulation and comparison results show that the proposed method is computationally much faster than the previously developed golden section method based two-level algorithm, and the obtained results are almost the same.
Keywords: renewable energy, security constraints, optimal non-renewable power generation, multi-objective risk-limiting optimal power flow, golden section metho
Cite this article: Shin-Yeu Lin, Yu-Syuan Cheng. COMPUTATIONALLY EFFICIENT METHOD FOR MULTI-OBJECTIVE RISK-LIMITING OPTIMAL POWER FLOW PROBLEMS. Journal of International Scientific Publications: Materials, Methods & Technologies 12, 20-27 (2018). https://www.scientific-publications.net/en/article/1001679/
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