Operation Optimization of Microgrids with Renewables

To reduce energy costs and emissions of microgrids, the daily operation is critical. The problem is to commit and dispatch distributed energy devices with renewable generation to minimize the total energy and emission cost while meeting the forecasted energy demand (both electrical and thermal). Without considering power flows, it is usually formulated as a Mixed-Integer Linear Programming (MILP, with discrete and continuous variables and a linear structure) problem, and is believed to be NP-hard. The problem is challenging because of the intermittent nature of renewables. To efficiently operate microgrids with renewables, the generation uncertainties (take photovoltaic (PV) as an example) are modeled by a Markovian process. For effective coordination among the microgrid, other devices are modeled as Markov processes with states depending on PV states. The entire problem is Markovian, and the resulting combinatorial problem is solved using a powerful MILP method, i.e. branch-and-cut.