Enhancing Frequency Containment Reserve Monitoring Using Phasor Measurement Units

Abstract In an increasingly dynamic power system with growing integration of renewable energy sources, real-time monitoring of primary frequency regulation—or Frequency Containment Reserve (FCR)—is essential for maintaining system stability and operational reliability. This paper presents a comprehensive approach to FCR monitoring based on high-resolution, time-synchronized measurements provided by Phasor Measurement Units (PMUs), with a focus on hydropower plants as primary FCR providers due to their flexibility and rapid response capabilities. The need for accurate and granular FCR monitoring arises from the limitations of traditional SCADA-based systems, which often lack sufficient temporal resolution and synchronization to capture dynamic frequency response behaviour. By contrast, PMUs enable precise tracking of frequency deviations, generator reaction times, and control characteristics such as droop and deadband. This enables a signal-based evaluation of each unit’s contribution to FCR, offering valuable insights into underperformance, delays, or asymmetric responses. However, signal analysis alone is not sufficient to fully evaluate FCR compliance. Therefore, the proposed monitoring framework integrates PMU-based detection performed within the WAMSTER platform with operational data collected from generating units via the PI AVEVA system. While WAMSTER verifies actual frequency response using synchrophasor data, PI AVEVA provides contextual information including production schedules, temporary limitations, and technological constraints. Based on this data, the expected FCR contribution is calculated for each unit, allowing for a comparison between expected and actual response. The monitoring architecture is realized through standardized protocols: IEEE C37.118 for real-time synchrophasor exchange between WAMSTER and PI AVEVA, and IEC 60870-5-104 for communication between local plant systems and PI AVEVA. The result is a scalable and modular system capable of providing system operators and analysts with an integrated, data-driven platform for comprehensive FCR evaluation and reporting. This paper outlines the development of the monitoring solution, including the design of the application, integration of PMU and plant data, and a case study focused on hydropower implementation. The findings highlight how combining PMU technology with contextual operational data provides a more complete understanding of FCR delivery, improves transparency, and supports compliance with regulatory requirements in modern, decarbonizing power systems.

Authors

Institutions

Publication Details

Journal
B&H eletrical engineering
Published
2025-11-16
DOI
https://doi.org/10.2478/bhee-2025-0014
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Frequency Containment Reserve Monitoring Using Phasor Measurement Units

Igor Ivanković, Krešimir Mesić, Renata Rubeša, Marko Rekić et al.
B&H eletrical engineering
Power System Optimization and Stability
article

Enhancing Frequency Containment Reserve Monitoring Using Phasor Measurement Units

Igor Ivanković, Krešimir Mesić, Renata Rubeša, Marko Rekić, Dalibor Brnobić, Ana Kekelj
article en

Abstract

Abstract In an increasingly dynamic power system with growing integration of renewable energy sources, real-time monitoring of primary frequency regulation—or Frequency Containment Reserve (FCR)—is essential for maintaining system stability and operational reliability. This paper presents a comprehensive approach to FCR monitoring based on high-resolution, time-synchronized measurements provided by Phasor Measurement Units (PMUs), with a focus on hydropower plants as primary FCR providers due to their flexibility and rapid response capabilities. The need for accurate and granular FCR monitoring arises from the limitations of traditional SCADA-based systems, which often lack sufficient temporal resolution and synchronization to capture dynamic frequency response behaviour. By contrast, PMUs enable precise tracking of frequency deviations, generator reaction times, and control characteristics such as droop and deadband. This enables a signal-based evaluation of each unit’s contribution to FCR, offering valuable insights into underperformance, delays, or asymmetric responses. However, signal analysis alone is not sufficient to fully evaluate FCR compliance. Therefore, the proposed monitoring framework integrates PMU-based detection performed within the WAMSTER platform with operational data collected from generating units via the PI AVEVA system. While WAMSTER verifies actual frequency response using synchrophasor data, PI AVEVA provides contextual information including production schedules, temporary limitations, and technological constraints. Based on this data, the expected FCR contribution is calculated for each unit, allowing for a comparison between expected and actual response. The monitoring architecture is realized through standardized protocols: IEEE C37.118 for real-time synchrophasor exchange between WAMSTER and PI AVEVA, and IEC 60870-5-104 for communication between local plant systems and PI AVEVA. The result is a scalable and modular system capable of providing system operators and analysts with an integrated, data-driven platform for comprehensive FCR evaluation and reporting. This paper outlines the development of the monitoring solution, including the design of the application, integration of PMU and plant data, and a case study focused on hydropower implementation. The findings highlight how combining PMU technology with contextual operational data provides a more complete understanding of FCR delivery, improves transparency, and supports compliance with regulatory requirements in modern, decarbonizing power systems.

B&H eletrical engineeringVol. 19(2)
Croatian Veterinary Institute (HR), HOPE Clinic (US)
Openalex Percentile: Top 65%
Power System Optimization and Stability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.