A Framework for Data Quality Analysis and Enhancement in SCADA Systems for Electric Power Transmission

The energy sector is undergoing a structural transformation, driven by the imperative to reinforce safety, security, and continuity of electricity supply while integrating increasing proportions of renewable energy sources. This paradigm shift poses substantial challenges for transmission system operators (TSOs), particularly with regard to maintaining secure and reliable grid operation under evolving conditions. A central challenge arises from the exponential growth in data generated at the transmission level, where accuracy, consistency, and timeliness are indispensable to achieving credible system state estimation and ensuring network observability. High-quality data is essential for monitoring key operational parameters including voltage, frequency, and power in real time, thereby enabling prompt anomaly detection and the initiation of corrective measures. This paper presents a comprehensive framework describing the end-to-end data transformation chain, spanning from the process level through to the SCADA environment, with a focus on the critical interfaces that preserve data quality. Furthermore, current data-processing methodologies at the SCADA level are examined, highlighting inherent limitations. Building upon these insights, the paper introduces a framework for SCADA level post-processing designed to enhance data precision, improve reliability, and support robust system operation.