Robust Day-Ahead Operation Planning of Unbalanced Microgrids

The optimal energy management of microgrids in the face of uncertainty is a challenging task. It requires practical modeling of the microgrid along with an efficient decision-making tool to effectively improve the economical operation and power quality. This paper presents a robust optimization framework for the day-ahead operation planning of unbalanced three-phase microgrids. The operation planning problem is formulated in detail as a mixed-integer nonlinear programming model. This model includes the operational constraints pertaining to voltage unbalance, synchronous generator unbalance operation, and power unbalance at the point of common coupling. Linearization techniques are proposed to transform this problem into a mixed-integer linear programming model for which efficient solvers are available. Two-stage robust optimization is used to obtain a robust operation planning decision against realizations of uncertain renewable generation, real-time market price, and voltage-dependent load parameters. This problem is solved using the column and constraint generation algorithm. The IEEE 37-bus and a 60-bus feeders are used to validate the performance of the robust solution.