Modeling and simulation of a microgrid as a Stochastic Hybrid System

Microgrids (MGs) are small-scale local energy grids. While dedicated to cover local power needs, their structure and operation is usually quite complex. Complexity arises due to a number of factors: in the first instance, a variety of operational modes - among them, MGs can be considered to be operated autonomously whenever the main distribution grid is not available; furthermore, the heterogeneity of energy types in a MG - not exclusively electrical energy, but also thermal for instance; also, the different functions that a MG energy management system has to fulfill - like coordination and dispatching of multiple generation, transfer, transformation and storage devices; finally, the external and internal random factors that affect operations. All these aspects make control and scheduling of a MG quite a challenging task. On the other hand, this widespread complexity leaves much room for improvement on the current state of the art. An advancement on the state of the art requires the development of a realistic model of the system at hand. This work puts forward a model of a MG that is based on the framework of Stochastic Hybrid Systems (SHS). SHS models can capture the interaction between probabilistic elements and discrete and continuous dynamics, and thus promise to be able to tame the complexity of the systems discussed above. This work displays the outcomes of model simulations and discusses potential development of general analysis and synthesis approaches over SHS models (e.g., based on model checking and on approximate dynamic programming) for typical challenges in MGs.