459989 Economic Model Predictive Control for Integrating Scheduling and Dispatch of Microgrid Power Systems
A case study is considered for a prototype microgrid consisting of a bi-directional connection to the macrogrid, photovoltaics, microturbines, a battery bank, flexible air conditioning, and an auxiliary electric boiler. This microgrid regulates indoor air temperature, supplies electricity, and generates hot water for a medium office building. A scheduling problem is considered for meeting these energy demands and coordinating energy exchange with the macrogrid. However, the inherent time scales involved in microgrid scheduling (i.e. hours to days) are not significantly separated from the time scales involved in control (i.e. seconds to minutes). Thus, a mixed integer linear E-MPC problem which incorporates low order process models is formulated for scheduling this microgrid on an hourly basis. Chance constraints are used to reduce the probability of commitment violations due to uncertainties in weather processes and local demands. Within each hour, frequent recourse optimization is used to update microgrid dispatch as uncertain conditions are realized.
The performance of this control approach is analyzed with respect to the operational cost, curtailment of renewable power, frequency and magnitude of commitment violations, and satisfaction of thermal demands. Computation time and differences between realized dispatch decisions and scheduling predictions are also considered. In addition, this presentation will highlight some of the important differences between integration of scheduling and control in traditional chemical systems and in these small power systems.
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