کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
764084 1462884 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improved gravitational search algorithm for parameter identification of water turbine regulation system
ترجمه فارسی عنوان
بهبود الگوریتم جستجوی گرانشی برای شناسایی پارامترهای سیستم تنظیم توربین آب
کلمات کلیدی
سیستم تنظیم توربین آب، شناسایی پارامتر، الگوریتم جستجوی گرانشی، بهینه سازی ذرات ذرات، جهش هرج و مرج
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی


• We propose an improved gravitational search algorithm (IGSA).
• IGSA is applied to parameter identification of water turbine regulation system (WTRS).
• WTRS is modeled by considering the impact of turbine speed on torque and water flow.
• Weighted objective function strategy is applied to parameter identification of WTRS.

Parameter identification of water turbine regulation system (WTRS) is crucial in precise modeling hydropower generating unit (HGU) and provides support for the adaptive control and stability analysis of power system. In this paper, an improved gravitational search algorithm (IGSA) is proposed and applied to solve the identification problem for WTRS system under load and no-load running conditions. This newly algorithm which is based on standard gravitational search algorithm (GSA) accelerates convergence speed with combination of the search strategy of particle swarm optimization and elastic-ball method. Chaotic mutation which is devised to stepping out the local optimal with a certain probability is also added into the algorithm to avoid premature. Furthermore, a new kind of model associated to the engineering practices is built and analyzed in the simulation tests. An illustrative example for parameter identification of WTRS is used to verify the feasibility and effectiveness of the proposed IGSA, as compared with standard GSA and particle swarm optimization in terms of parameter identification accuracy and convergence speed. The simulation results show that IGSA performs best for all identification indicators.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Conversion and Management - Volume 78, February 2014, Pages 306–315
نویسندگان
, , , ,