Coordination of energy storage systems and DR resources for optimal scheduling of microgrids under uncertainties

Wind energy integration into microgrids, has introduced new challenges to energy management systems because of its intermittent behaviour. Owing to continuous changes in generation and consumption, the energy price is volatile. This study proposes a new two-stage stochastic framework for day-ahead scheduling of microgrids. Uncertainties associated to wind power generation, real-time electricity price and load demand are considered. Different scenarios are generated using autoregressive moving-average method and then are reduced using fast-forward technique. On the first stage, the microgrid master controller determines the procured energy from the day-ahead market and commitment states of distributed energy resources (DERs). In the second stage, the purchased energy from the real-time market and schedules of committed DERs are obtained. The problem is modelled using mixed-integer linear programming approach and is solved via CPLEX® optimizer. Both grid-connected and stand-alone modes of operation are investigated. Despite of high operation cost in island mode, coordination of energy storage systems, incentive-based and price-based demand response (DR) programmes affect economy of microgrids. The framework is examined on a test microgrid. Results show that both of the releasing the microgrid master controller authority and DR resources result in significant saving in operating; especially in emergency conditions such as islanded mode.