Supervision control for optimal energy cost management in DC microgrid: Design and simulation

Abstract

The development of microgrids could facilitate the smart grid feasibility which is conceived to improve instantaneous grid power balancing as well as demand response. It requires microgrid control functions as power balancing, optimization, prediction, and smart grid and end-user interaction. In literature, these aspects have been studied mostly separately. However, combining them together, especially implementing optimization in real-time operation has not been reported. The difficulty is to offer resistance to optimization uncertainties in real-time power balancing. To cover the research gap, this paper presents the supervision design with predicted powers flow optimization for DC microgrid based on photovoltaic sources, storage, grid connection and DC load. The supervision control, designed as four-layer structure, takes into account forecast of power production and load power demand, storage capability, grid power limitations, grid time-of-use tariffs, optimizes energy cost, and handles instantaneous power balancing in the microgrid. Optimization aims to reduce the microgrid energy cost while meeting all constraints and is carried out by mixed integer linear programming. Simulation results, show that the proposed control is able to implement optimization in real-time power balancing with resistance to uncertainties. The designed supervision can be a solution concerning the communication between loads and smart grid.