A microservice-based frontend software for a distributed energy resource management platform under Grid Artificial Intelligence (GridAI) framework

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Date
2024-12
Authors
Gupta, Peeyush
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Gelli, Ravikumar
Trajcevski, Goce
Mitra, Simanta
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This thesis presents the development of the Frontend Component of a comprehensive platform for Distributed Energy Resource Management Systems (DERMS) designed to manage, monitor, and optimize distributed energy resources (DERs) effectively. As DER adoption grows, with technologies like solar panels, electric vehicles, and smart appliances are becoming increasingly integrated into power systems, the need for robust management platforms becomes critical. This research introduces an innovative DERMS solution that supports cloud and on-premises deployment and combines a map-based user interface, real-time collaboration, and custom widget-based dashboards to empower Distribution System Operators (DSOs) and stakeholders with enhanced data visibility and operational control. The proposed system leverages a modular architecture to efficiently handle high-frequency, high-volume data from diverse DERs, employing technologies such as IndexedDB for data management, Web Workers for client-side computation, for data visualization. Key platform components include a map interface for geospatial data visualization, a collaborative project editor for managing grid files, and a customizable dashboard for data analysis. The platform’s security is strengthened by a multi-tenant architecture, allowing for granular role-based data access. Evaluations demonstrate the platform’s capacity to handle large datasets and provide timely, accurate updates with minimal latency, supporting improved grid resilience and sustainability. This thesis contributes to the field by addressing critical challenges in DER integration and control, offering a scalable, adaptable solution that promotes efficient grid management for both industry and academic research.
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