Hybrid Context-awareness Modelling and Reasoning Approach for Microgrid's Intelligent Control

Abstract

Modern microgrids are promoting the integration of the information and communication technologies (ICT) in order to enhance the emerging advanced power management functionalities such as the integration of renewable energy sources, distributed storage optimization, demand-response strategies, electric vehicles charging, power generation rate forecasting and scheduling, etc. For this, sophisticated sensing and smart metering infrastructures are incorporated in the used equipment as well as in the involved subsystems. Hence many contextual data are become more and more available and its taking into consideration in the control tasks are likely to provide promising results. However, making the microgrid control system understand the data and take the proper decisions based on the identified context is not an easy task to perform. In fact, recognizing the relations and meanings of the sensed data is difficult and complex due to the heterogeneity and intricacy of the involved parts. Hence , providing context-aware modelling and reasoning mechanisms for microgrids becomes necessary. In this context, this paper contributes with two main solutions. First, a microgrid’s formalized design providing an easy and understandable view of the system is provided. This definition respects the separation of concerns principle in order to tame the complexity of the complicated system. Second, an ontology-based context modelling and a rule-based context reasoning in the framework of microgrids are provided. To show the suitability of the proposed processes, a formal case study is carried out. The proposed processes are proved to be less resources consuming compared to some of the existing works.