AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment. (February 2016) - Arya, Yogendra; Kumar, Narendra
Highlights: We model AGC of a two-area multi-source restructured hydrothermal power system. Two-areas are interconnected via AC/DC parallel links under deregulated environment. Optimal control theory is applied to design PI structured AGC regulators. The system performance is compared with single-source restructured thermal system. Study is also extended to two-area non-reheat thermal system with GDB nonlinearity. Abstract: This paper proposes the automatic generation control (AGC) of an interconnected multi-area multi-source hydrothermal power system under deregulated environment. The two equal control areas with hydro and thermal generating power sources are interconnected via AC/DC parallel links. The optimal proportional integral (PI) regulators are designed for the proposed power system to simulate all power market transactions which are possible in a restructured power system. The concept of DISCO participation matrix (DPM) is harnessed to simulate the transactions. Eigenvalue study is conducted to assess the effect of AC/DC parallel links on system performance. The study is also conducted, considering appropriate generation rate constraints (GRCs) for thermal and hydro generating sources. Further, the dynamic responses of the proposed multi-source hydrothermal power system are compared with single-source thermal–thermal power system and it has been ascertained that the responses of proposed power system are sluggish with large overshoots and settling times. Finally, the study is extended to frame and implement optimal PI regulators for the first time for the AGC of a conventional two-area non-reheat thermal power system with governor dead-band nonlinearity. The superiority of the optimal PI regulators has been established by comparing the results with recently published best claimed craziness based particle swarm optimization (CRAZYPSO) and hybrid bacterial foraging optimization algorithm-particle swarm optimization (hBFOA-PSO) algorithms based PI controller tuned for the same interconnected power system.