Empowering Elia’s Adequacy and Flexibility Study: A Deep Dive into Forced Outage Rates

N-SIDE contributed to Elia's Adequacy Flexibility Study for Belgium 2024-2034 with our StudyForced Outage Rate (FOR) Study
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Sergio Z. Perilla

Transmission System Operators (TSOs) such as Elia play a crucial role in ensuring the security of energy supply through adequacy and flexibility studies. These studies ensure sufficient capacity to meet demand, a responsibility that has gained complexity given recent changes in the energy sector such as economic crises, unstable loads, and the rise of renewable energy sources (RES). To address these challenges, Elia conducted an Adequacy and Flexibility Study for Belgium 2024-2034, and N-SIDE was proud to contribute to this important research with our Forced Outage Rate (FOR) study.


Forced outages – which are unplanned, unexpected power plant shutdowns – pose a significant challenge when it comes to ensuring the security of the energy supply. Historical data on forced outages has been traditionally used to compute outage parameters, but this direct computation has proved challenging due to its nature. To address this challenge, N-SIDE developed a comprehensive solution tailored to address the specific hurdles of gathering historical data and calculating forced and planned outage rates of power generation units in Belgium and neighboring countries.


Our aim with this study was not only to deliver an in-depth analysis of historical outage data and industry practices but also to empower Elia with a robust tool to continually monitor and calculate both planned and forced outage rates. Collaborating closely with Elia's experts, we identified, analyzed, and processed relevant historical time-series data from Belgium and numerous European countries. This data was processed, validated, and then used to compute Key Performance Indicators (KPIs) relevant to outage rates of generation units. Our analytical approach provided insights into KPIs per country and at the EU level, the impact of different generation technologies, the dependency of forced outage rates on unit age, the effects of seasonality, and the evolution of KPIs over time.


In addition to our analysis, we conducted a review and comparison of current practices among different energy actors regarding the computation of forced outage KPIs. This benchmarking exercise enabled us to understand trends, analyze different scenarios, identify the most effective KPIs, and explain the significant differences in computed KPIs between countries.

Our solution, crafted with our deep knowledge of energy and data analysis and our robust software capabilities, effectively addressed Elia’s challenges. It not only provided insights into current outage rates but also equipped them with the ability to continuously monitor and calculate these rates, ensuring their adequacy studies remain accurate and reliable.


Our contribution to Elia’s study is a testament to our commitment to using our expertise in energy and data analysis to help TSOs, and other stakeholders in the energy sector, ensure a secure and reliable energy supply. We are proud of the work we have done with Elia and look forward to contributing to future energy studies and projects, and continuing our partnership with TSOs in securing the future of energy supply.


We invite you to learn more about this and the broader implications of our findings on Elia’s Adequacy and Flexibility Study for Belgium 2024-2034


Each TSO has its unique challenges and needs. If you would like to know how N-SIDE can give you the upper hand with tailored solutions delivered with speed, please don't hesitate to get in touch with us

About the Author

Sergio holds a double master's degree in Smart Electrical Networks and Systems from KTH (Sweden) and TU/e (The Netherlands). He specializes in the development of applications for power grid planning and operation, leveraging mathematical programming and machine learning techniques. His areas of expertise encompass remedial actions optimization, maintenance optimization, and applied artificial intelligence tools.

Sergio Z. Perilla

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