Study and Design of a SCADA System with AI-Based Predictive Maintenance for Renewable Energy Plants

Department

Automation department — Project 06/06 of the Integration Objects PFE Book 2026–2027.

Project

Design and implement a SCADA/HMI system for monitoring and controlling a renewable energy plant, integrating an AI-based agent that analyzes real-time and historical operational data to detect anomalies, predict potential equipment failures, and recommend maintenance actions. The objective is to reduce downtime and improve equipment reliability, plant availability, and overall operational performance.

Objectives and responsibilities

• Analyze the plant architecture, functional requirements, and maintenance needs of the main equipment.
• Define the SCADA architecture, I/O list, tag database, and industrial communication network using protocols such as Modbus TCP and OPC UA.
• Configure real-time data acquisition, historical data archiving, and operational data management.
• Develop SCADA/HMI synoptic displays, alarm management, trends, and key performance indicators.
• Integrate an AI-based model into the SCADA system to analyze real-time telemetry data, detect anomalies, and identify abnormal operating patterns.

Keywords

SCADA, OPC UA, PLC, Modbus TCP, Python, Machine Learning, Java scripting.