An uncertainty reduction strategy to schedule and operate microgrids with renewable energy sources

As the renewable energy in microgrids exhibits inherent intermittence and volatility, their forecasts are subject to a high level of uncertainty even for a few hours. To deal with the uncertainty in microgrids, new energy management strategies are necessary to be developed. This paper presents a strategy to optimally schedule and operate a microgrid while mitigating the impact of the uncertainty. Uncertainty in load, and renewable energy such as wind and photovoltaic systems is considered in this paper. The load minus the power output of renewable energy is viewed as equivalent load, whose distribution is described as a forecast range at a given confidence level. The forecast range is divided into several sub-ranges, and each sub-range is assigned a schedule by performing an optimization. In this way, corresponding scheme is implemented when the real value falls into the sub-range at real-time operation. The proposed strategy is tested on a radical microgrid. Numerical simulation indicates that the strategy is effective to produce an accurate generation schedule while maintaining an economic performance of the system. In addition, it is able to reduce the uncertainty, which lowers the reserve requirement for compensating the deviations and reduces the risk of overcharging and overdischarging of energy storage systems.