Multi-agent Model Predictive Control of Nonlinear Interconnected Hydro-Thermal System Load Frequency Control Based on Bat Inspired Algorithm
International Journal of Scientific Research Engineering Technology • 2015
معلومات البحث
المؤلفون
M. Elsisi, M. A. S. Aboelela, M. Soliman, W. Mansour
الكلمات المفتاحية
Bat Inspired Algorithm (BIA), Load Frequency Control (LFC), Multi-agent Model Predictive Control (MPC)
المجلة العلمية
International Journal of Scientific Research Engineering Technology
الناشر
International Journal of Scientific Research Engineering Technology
المجلد
1
العدد
5
الصفحات
90-99
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
Bat Inspired Algorithm (BIA) has recently been explored to develop a novel algorithm for distributed optimization
and control. This paper proposes a multi-agent Model Predictive Control (MPC) of Load Frequency Control (LFC) based on
BIA to enhance the damping of oscillations in a two-area power system. A two-area hydro-thermal system is considered to be
equipped with multi-agent MPC. The proposed power system model considers generation rate constraint (GRC), dead band,
and time delay imposed to the power system by governor-turbine, thermodynamic process, and communication channels. BIA is
utilized to search for optimal controller parameters by minimizing a time-domain based objective function. The performance of
the proposed controller has been evaluated with the performance of the conventional PI controller based integral square error
technique , and PI controller tuned by GA in order to demonstrate the superior efficiency of the proposed multi-agent
MPC tuned by BIA
and control. This paper proposes a multi-agent Model Predictive Control (MPC) of Load Frequency Control (LFC) based on
BIA to enhance the damping of oscillations in a two-area power system. A two-area hydro-thermal system is considered to be
equipped with multi-agent MPC. The proposed power system model considers generation rate constraint (GRC), dead band,
and time delay imposed to the power system by governor-turbine, thermodynamic process, and communication channels. BIA is
utilized to search for optimal controller parameters by minimizing a time-domain based objective function. The performance of
the proposed controller has been evaluated with the performance of the conventional PI controller based integral square error
technique , and PI controller tuned by GA in order to demonstrate the superior efficiency of the proposed multi-agent
MPC tuned by BIA
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