Optimization of economic aspects of microgrid operation in both grid-connected and islanded mode leads to contradictive definitions of optimality for both modes. There is no general agreement on how to cope with this duality. To address this issue, as well as modern energy market requirements and a better renewable energy utilization necessity in the case of large facilities, a comprehensive control solution utilizing the appropriate model is needed. In response, the authors propose a hybrid microgrid model covering fundamental features and designed to work in conjunction with two switched receding horizon control laws. A relevant controller is chosen according to the current microgrid operation mode and its cost function tailored to specific demands of the islanded or grid-connected operation. Performed research led to a new switched hybrid model predictive control approach focused on microgrid economic optimization. This approach utilizes an appropriate hybrid microgrid model also contributed by the authors. The introduced solution turned out to be effective in overall energy cost reduction in the case of large commercial facilities, regardless of grid-connection and renewable generation scenarios. Furthermore, it also provides satisfactory renewable energy and storage capabilities utilization in changing grid connection conditions.

MPC Driven control systems very often are requiring the introduction of a mechanism predicting the state of the object unavailable for measurements. Depending on the case, a different number of state variables will be unobtainable. Widely used systems to obtain essential data of the condition of an object are Luenberger state observer and different types of Kalman filters. The authors propose a new method of Luenberger observer synthesis based on Luenberger gain optimization using performance index corresponding to generalized system performance. The developed method allows us to obtain better-performing observer from the point of view of the adopted criterion, compared to similar estimators derived from the Sylvester equation and classic Kalman filters, even despite the occurrence of disturbances. The developed method will be presented on an example of an active suspension system with MPC.