Gerenciamento de recursos energéticos distribuídos em redes inteligentes com base na norma IEEE 1547 e no protocolo IEEE 2030.5

Abstract

The increasing integration of Distributed Energy Resources (DERs) into smart grids poses significant challenges to operational stability and efficiency, such as voltage fluctuations, power factor degradation, and management complexities. This dissertation addresses these challenges through the evaluation and implementation of the IEEE 2030.5 protocol as a solution for DER control and monitoring. The main objective was to analyze the performance of IEEE 2030.5 in mitigating operational problems in distribution networks with high penetration of distributed generation, focusing on voltage and power factor control. For this purpose, an experimental control architecture was developed at the photovoltaic plant of the Federal University of Technology - Paraná (UTFPR), Pato Branco Campus, with a capacity of 420 kWp of active power and 277 kVAr of reactive power. The implemented system performs cyclical readings of inverters and meters via IEEE 2030.5, with control decisions based on moving averages and in compliance with the IEEE 1547 standard. The methodology details data collection (Modbus RTU/TCP), communication via local and aggregator gateways (Raspberry Pi, D-Bus), conversion to the IEEE 2030.5 standard, and interaction with a cloud server. A reactive power controller was implemented, utilizing the Metering and EndDeviceControl resources of IEEE 2030.5. The results demonstrated the controller’s ability to mitigate overvoltages, maintaining the grid voltage within normative limits through dynamic reactive power adjustment. The proportional distribution of reactive effort among inverters was verified. It is concluded that the IEEE 2030.5 protocol is a viable and effective approach for DER management, offering flexibility, scalability, and interoperability in a real operational environment, validating its practical use and providing insights for future implementations in more resilient and intelligent power grids.