Digital Twinning of Village-scale Microgrids for Remote Maintenance of Power Equipment

Village-scale microgrids are considered one of the most promising enabling technologies for reliable and cost-effective electrical power generation in developing nations. Besides, deploying effective corrective and predictive maintenance policies for these facilities is challenging due to the need for in-situ expertise, the limited economic resources, and the complexities of supply chain management. All these issues dramatically affect the fault reparation times of power equipment, which are significantly larger than those observed in conventional microgrids. To try and overcome these limiting issues, this paper explores the potential role of digital twins in supporting the development of decision support tools for remote maintenance of village microgrids. Several experimental results obtained by deploying a digital twin on a real-time microgrid simulator are presented and discussed to demonstrate the effectiveness of this tool in enabling the development of remote training sessions and supporting information exchange between power system experts and local operators.