Advanced Energy Forecasting Using IoT - Enabled SCADA Systems

Abstract

With the substantial increase in global renewable energy production, real-time data has become essential for the efficient management of these resources particularly offshore and distant installations. A supervisory control and data acquisition system is a system that sends individual messages or directives to the external world. In this research paper, we introduce a SCADA system integrated with the Internet of Things (IoT) to monitor a hybrid system that includes hydropower, solar energy, wind, and tidal power. It provides a range of control functions for supervisors to manage and configure settings effectively. The goal is to achieve energy autonomy and promote sustainable economic growth. This technology makes it easier to administer the warning system, data logging, data monitoring and control system, and generated capacity, among other features of the station’s information. Additionally, a data packet and WiFi analyzer are used to measure the communication parameters and overall performance of the Internet of Things-based SCADA system. In addition, historical energy generation data is used to evaluate and identify what factors are impacting the output of hydropower stations. This data is then utilized to forecast the production levels for the upcoming year through the application of time series analysis.