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In this paper, an energy management system (EMS) has been developed based on model predictive control (MPC) to optimally dispatch the power units and particularly handle the duck curve fast ramping events. The methodology is specifically developed considering higher penetration of solar photovoltaic power subjected to realistic physical constraints. Battery energy storage, load shedding and solar curtailment have been utilized to effectively control the duck curve fast ramping events. The proposed system has been assessed with the help of a case study using a 24-bus RTS system. Consequently, detailed flexibility analyses were carried out and it has been proven that the given energy management and control system is capable of handling fast ramping events of duck curve. Furthermore, it has been observed that the overall operation cost of the system is also minimized. The performance of the developed model is compared with traditional non-MPC based mixed-integer linear programming approaches and it has been concluded that MPC-based optimization is more economical and effective in handling the duck curve challenges.

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