JAYA Optimized Generation Control Strategy for Interconnected Diverse Source Power System with Varying Participation

ABSTRACT

A new Artificial Intelligence (AI) technique known as Jaya algorithm is used to design Proportional-Integral-Derivative (PID) structured regulators of Optimized Generation Control (OGC) strategy for interconnected two control areas of diverse-source power system. Each control area includes reheat thermal, hydro, and gas power sources. Jaya algorithm is formed with the concept of victory, i.e., approaching the best result and discarding the worst result. The superiority of proposed Jaya OGC has been demonstrated by contrasting its dynamic response, performance index value, and performance parameters in terms of settling time, peak time, and peak absolute value with BAT and recently published Bacterial Forging Optimization (BFO) technique. The study is further extended to analyze the effect of varying participation of diverse sources. Further, a comparative analysis has been done to show a significant impact of varying participation of diverse source on the dynamic response in terms of frequency deviation and power tie-line deviation, settling time, peak absolute value, and the performance index value of the system. It has been shown that the sluggishness of dynamic response at 1% step load disturbance in one of the control areas is due to the use of hydro source which can be significantly improved by decreasing the participation of hydro source and increasing the participation of thermal and gas source in an interconnected power system.

KEYWORDS:

• Reheat thermal-hydro-gas power system
• automatic generation control
• Jaya algorithm
• BAT algorithm
• proportional-integral-derivative