Multi-agent Systems Using Model Predictive Control for Coordinative Optimization Control of Microgrid

According to controllability theory of nonlinear coordinated control with multi-agent, this paper proposes a coordinative optimization method based on the model predictive control (MPC) to achieve the coordination control of energy allocation. Between the micro sources with the incremental cost of consistency algorithm for leader-follower, using an interactive algorithm to achieve the exact optimal solution to the optimization problem based on MPC, each micro source as an intelligent agent through the interaction between the adjacent micro sources, while achieving coordinated optimization control in microgrid to meet the incremental cost. The obtained results show that multi-agent systems (MAS) using MPC for coordinative optimization control of microgrid can effectively manage the micro source, to fully explore the key role of individual intelligence in group cooperative behavior. The effectiveness of distributed consistency algorithm & MPC algorithm are verified by examples.