distributed multi-agent load frequency control for a large-scale power system optimized by grey wolf optimizer

This paper aims to design an optimal distributed multi-agent controller for load frequency control and optimal power flow purposes. the controller parameters are optimized using grey wolf optimization (gwo) algorithm. the designed optimal distributed controller is employed for load frequency control in the ieee 30-bus test system with six generators. the controller of each generator is considered as one agent. the controllers of agents are implemented in a distributed manner that is control rule of each agent depends on the agents’ own state and the states of their neighbors. three other types of controllers including centralized controller, decentralized controller, and optimal centralized controller are considered for comparison. the performances of decentralized and distributed controllers are compared with two centralized controllers. in the optimal centralized controller and optimal distributed controller, the objective function is considered to achieve the objective of load frequency control as well as minimize power generation. simulation results using matlab/simulink show that although there is no global information of system in the optimal distributed controller, it has suitably reduced the frequency deviation. meanwhile the power is optimally generated in the three scenarios of load increasing, load reduction and generator outage.