Abstract

The development of microgrids could facilitate the smart grid feasibility that is conceived to improve instantaneous grid power balancing and demand response. It requires microgrid control functions as power balancing, optimization, prediction, and smart grid and end-user interaction. The difficulty is to offer resistance to optimization uncertainties in real-time power balancing. On the basis of direct current (DC) microgrid power system modeling, this chapter presents the supervisory design with predicted power flow optimization for a DC microgrid. The supervisory control, designed as a four-layer structure, takes into account the forecast of power production and load power demand, storage capability, grid power limitations, and 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 performed by mixed integer linear programming. This is an optimization under constraints seen such as offset between prediction uncertainties and planning on the one hand and operational reality and utility grid requirements on the other hand. The real-time operation layer is developed to control the DC microgrid power balance taking into account the considered constraints. Simulation results validate the feasibility of DC microgrid supervisory design and show that the proposed control is able to implement optimization in real-time power balancing with resistance to uncertainties. The designed supervisory control can be a solution concerning the communication between loads and the smart grid.

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