Enhanced real-time scheduling algorithm for energy management in a renewable-integrated microgrid

The day-ahead energy management scheme (EMS) of a microgrid faces different uncertainties due to the inaccuracy of predictions. Moreover, offline EMS assumes that renewable generation and load demand predictions are perfect, which is practically difficult to achieve. Although real-time EMS (RT-EMS) can overcome these uncertainties by employing online measurements, utilization of storage units in RT-EMS needs further investigation because the solution does not achieve the global optimal. In this study, a multi-objective RT-EMS is proposed by considering the costs and life cycle environmental impacts of energy sources. The suggested RT-EMS is designed using Lyapunov optimization method and then enhanced through the proposed adaptive utilization of the storage units. The charging and discharging of the storage units are scheduled adaptive to the time-of-use market price, resulting in lower environmental impacts because the life cycle environmental impact of energy storage is significant. Therefore, the proposed RT-EMS is a multi-objective problem, and a Pareto front is derived from compromising between the operational cost and the environmental impacts. The proposed market price-based RT-EMS is evaluated using numerical studies on the modified IEEE 33-bus test system and real-world data.