Automatic Generation Control of Multi-Area Hydro Power System using Moth Flame Optimization Technique

被引:0
作者
Chatterjee, Shamik [1 ]
Shiva, Chandan Kumar [2 ]
Mukherjee, Vivekananda [3 ]
机构
[1] Lovely Profess Univ, Sch Elect & Elect Engn, Phagwara, Punjab, India
[2] SR Engn Coll, Dept Elect Engn, Warangal, Andhra Pradesh, India
[3] Indian Sch Mines, Indian Inst Technol, Dept Elect Engn, Dhanbad, India
来源
2019 3RD INTERNATIONAL CONFERENCE ON RECENT DEVELOPMENTS IN CONTROL, AUTOMATION & POWER ENGINEERING (RDCAPE) | 2019年
关键词
Automatic generation control (AGC); hydro power system; moth-flame optimization (MFO); proportional-integral-derivative (PID) controller; Sugeno fuzzy logic (SFL); FREQUENCY CONTROL; PID CONTROLLER; LOAD; PERFORMANCE; ALGORITHM; AGC;
D O I
10.1109/rdcape47089.2019.8979090
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The novel moth-flame optimization (MFO) algorithm has been employed for the automatic generation control (AGC) mechanism of a three-area hydro power system model. This work is to suppress the damped oscillations, subjected to perturbation of load, for the studied model. The present aspect investigates the responses, which is dynamic in nature, in respect of area frequency and power of tie-line oscillations (the two main AGC indices). The constrained optimization problems that play key roles in the design of controller gains are formulated by implementing the propounded MFO algorithm. System AGC responses with the designed controller parameters are studied with two different natures of load profiles. The proposed MFO algorithm based fast acting Sugeno fuzzy logic (SFL) technique is applied for the investigated model of power system to obtain AGC responses for on-line, off-nominal operating condition. In both the off-line as well as the on-line normal operating conditions, robustness of the proposed MFO-SFL controllers is checked by varying some important physical parameters that deviate by +/- 25% from their rated values. The simulation based outcomes reveal that the propounded MFO based PID controller exhibit more dynamic control with robust performance as juxtaposed to the studied genetic algorithm based approach.
引用
收藏
页码:395 / 403
页数:9
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