Abstract
As a first attempt this article investigates the load frequency regulation, an automatic generation control (AGC) problem of an interconnected multi-area multi-source hybrid power system (MAMS-HPS) with demand response contribution (DRC) using the teaching learning-based optimisation (TLBO) algorithm. Here, the MAMS-HPS is configured containing the micro-hydro, biogas, biodiesel, solar-thermal, and wind turbine generating units arranging in interconnected two-unequal areas. Due to the increased presence and penetration of RES in power system, a high degree of unpredictability and dependence on the nature significantly introduces the difficulty in balancing the generation and load demand. To address this problem, an approach is taken to optimize proportional-integral-derivative (PID) controller gains using optimisation algorithms namely the particle swarm optimisation (PSO) and TLBO to accessing the responses under various realistic scenarios of availability and variations of RES as well as load variations. The responses are accessed by adding a DRC system also. The MATLAB-Simulink model is developed for the system simulation and comparative performance analysis of control schemes in terms of time domain specifications observing the responses of the system states.