کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
400148 1438777 2010 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Load frequency stabilization by coordinated control of Thyristor Controlled Phase Shifters and superconducting magnetic energy storage for three types of interconnected two-area power systems
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Load frequency stabilization by coordinated control of Thyristor Controlled Phase Shifters and superconducting magnetic energy storage for three types of interconnected two-area power systems
چکیده انگلیسی

In this paper, automatic generation control with interconnected two-area multi-unit all-hydro power system and two more test systems as all-thermal and thermal-hydro mixed haves been investigated. The transfer function of hydro turbine having non-minimum phase characteristics makes it different from the steam turbine. Upon application of small load perturbation to such all-hydro system, the frequency is severely disturbed and the system eventually becomes unstable. To stabilize the system for such load disturbance, comparative transient performance of two cases as (a) Thyristor Controlled Phase Shifter (TCPS) installed in series with the tie-line in coordination with Superconducting Magnetic Energy Storage (SMES) and (b) SMES located at each terminal of both areas are analyzed. It is observed that the case (b) i.e. SMES located at each terminal of both areas suppresses the frequency oscillations more effectively in integral controller assisted AGC of two-area multi-unit all-hydro system and the other two systems as well. In addition, the effectiveness of proposed frequency stabilizers is guaranteed by analyzing the transient responses of the system with different system parameters, various load patterns and in the event of temporary and permanent tie-line outage. Gains of the integral controller in AGC loop and parameters of TCPS and SMES are optimized with the help of a relatively novel particle swarm optimization, developed by the authors, called as craziness-based particle swarm optimization (CRPSO). The optimizing performance has been compared to that of real-coded genetic algorithm (RGA) to establish its superiority.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 32, Issue 10, December 2010, Pages 1111–1124
نویسندگان
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