Model Predictive Control Approach for Optimal Power Dispatch and Duck Curve Handling Under High Photovoltaic Power Penetration
This research proposes an energy management system (EMS) 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 will be utilized to effectively control the duck curve fast ramping events. The proposed system will be assessed with the help of a case study using a 24-bus RTS system. A detailed flexibility analyses will be carried out to assess the given energy management and control systems capability to handle fast ramping events of the duck curve. Furthermore, the overall operation cost of the system will be minimized. The performance of the developed model will be compared with traditional non-MPC based mixed-integer linear programming approaches in order to show the effectiveness of the MPC-based optimization. The predictive control approach as proposed in this proposal presents a series of advantages for the problem considered in this application over other control methods: such as 1) systems with constraints can be handled directly; 2) implementation in real-time is easier; 3) when future references and/or disturbances are known, the controller can use this information for performance improvement, and 4) multi-input multi outputs can be handled very easily including predictions. Finally, MPC has already been used in the domain of renewable energy systems and emerged as a very effective approach especially in economic dispatch problems.