Hierarchical and distributed optimization of energy management for microgrid

A hierarchical and distributed optimization of energy management is proposed based on multi Agent system for microgrid, which takes the economy, environmental protection and power-supply reliability as its objectives. It converts the traditional centralized energy optimization into four sub-optimizations: the distributed computing of micro-sources to refine the domain of each variable, the GA-based optimization of central controller, the distributed parallel regulation to modify the optimization solution and the global coordination to generate the final solution, in which, the operational features and control objectives of different micro-sources are implemented as constraints. The special tasks of diverse Agents and the collaborative relationship among them are described respectively for the single-objective and multi-objective optimizations of microgrid. A microgrid optimization model for next 24 hours is built based on MATLAB and JADE. Numerical results demonstrate that, the proposed strategy of hierarchical and distributed optimization has higher optimization efficiency and better optimization results, weakening the dependence on the performance of central controller.