A multi-agent system-based intelligent steady-state model for a power plant

A large-scale power system is required to have a new strategy to operate at a higher level of automation, flexibility, and robustness. It is a challenge to get the steady-state model for a high order complex nonlinear power plant. Moreover, the model should be adaptive under the changing environment. In this paper, a multi-agent system-based intelligent steady-state model (MAS-ISSM) is presented as an alternative methodology to identify the steady-state model in a large-scale 600 MW thermal power plant. Design of architectures for single agents and an organization of the multi-agent system will be described as the foundation of the intelligent steady-state model (ISSM). The MAS-ISSM will be utilized in the evaluation process and the set-point scheduler to map various control inputs to power and pressure set-points for multiobjective optimization in the power plant. The procedure is presented through a case study, and its feasibility is demonstrated with the simulation results