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Outputs (11)

An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning (2025)
Presentation / Conference Contribution
Liu, J., Kazemtabrizi, B., Du, H., Matthews, P., & Sun, H. (2024, November). An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning. Presented at 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA

With the increasing integration of renewable energy sources into the power grid, accurate and reliable ultra-short-term forecasting of wind power is critical for optimizing grid stability and energy efficiency, especially for a highly dynamic and var... Read More about An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning.

Data-driven estimation of the amount of under frequency load shedding in small power systems (2024)
Journal Article
Rajabdorri, M., Troffaes, M. C. M., Kazemtabrizi, B., Sarvarizadeh, M., Sigrist, L., & Lobato, E. (2025). Data-driven estimation of the amount of under frequency load shedding in small power systems. Engineering Applications of Artificial Intelligence, 139(Part B), Article 109617. https://doi.org/10.1016/j.engappai.2024.109617

This paper presents a data-driven methodology for estimating under frequency load shedding (UFLS) in small power systems. UFLS plays a vital role in maintaining system stability by shedding load when the frequency drops below a specified threshold fo... Read More about Data-driven estimation of the amount of under frequency load shedding in small power systems.

Data-Driven Infrastructure Planning for Offshore Wind Farms (2024)
Presentation / Conference Contribution
Saxena, I., Kazemtabrizi, B., Troffaes, M. C., & Crabtree J., C. (2024, May). Data-Driven Infrastructure Planning for Offshore Wind Farms. Presented at Torque 2024, Florence, Italy

Offshore wind farms are one of the major renewable energy resources that can help the UK to reach its net zero target. Under the 10 point plan of the green revolution, the UK is set to quadruple its wind energy production by increasing its offshore w... Read More about Data-Driven Infrastructure Planning for Offshore Wind Farms.

Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning (2023)
Journal Article
Rajabdorri, M., Kazemtabrizi, B., Troffaes, M., Sigrist, L., & Lubato, E. (2023). Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning. Sustainable Energy, Grids and Networks, 36, Article 101161. https://doi.org/10.1016/j.segan.2023.101161

As the intention is to reduce the amount of thermal generation and to increase the share of clean energy, power systems are increasingly becoming susceptible to frequency instability after outages due to reduced levels of inertia. To address this iss... Read More about Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning.

Inclusion of Frequency Stability Constraints in Unit Commitment Using Separable Programming (2021)
Journal Article
Ferrandon-Cervantes, C., Kazemtabrizi, B., & Troffaes, M. (2022). Inclusion of Frequency Stability Constraints in Unit Commitment Using Separable Programming. Electric Power Systems Research, 203, Article 107669. https://doi.org/10.1016/j.epsr.2021.107669

In this paper we address the problem of frequency stability in the unit commitment (UC) optimisation process. We include a set of appropriately defined frequency stability constraints in the UC problem formulation for operational planning scenarios i... Read More about Inclusion of Frequency Stability Constraints in Unit Commitment Using Separable Programming.

An Economic Model for Offshore Transmission Asset Planning Under Severe Uncertainty (2020)
Journal Article
Bains, H., Madariaga, A., Troffaes, M. C., & Kazemtabrizi, B. (2020). An Economic Model for Offshore Transmission Asset Planning Under Severe Uncertainty. Renewable Energy, 160, 1174-1184. https://doi.org/10.1016/j.renene.2020.05.160

The inherent uncertainties associated with offshore wind are substantial, as are the investments. Therefore, investors are keen to identify and evaluate the risks. This paper presents a model to economically evaluate projects from an offshore transmi... Read More about An Economic Model for Offshore Transmission Asset Planning Under Severe Uncertainty.

Contingency Ranking in Power Systems via Reliability Rates (2018)
Presentation / Conference Contribution
Cervantes, C., Kazemtabrizi, B., & Troffaes, M. (2018, October). Contingency Ranking in Power Systems via Reliability Rates. Presented at 18th IEEE International Conference on Environment and Electrical Engineering, Palermo, Italy

This paper shows the scope of probabilistic contingency ranking algorithms when applied to transmission systems with high levels of renewable integration. Using our fast screening contingency ranking algorithm, a performance index is calculated throu... Read More about Contingency Ranking in Power Systems via Reliability Rates.

Qualitative comparison of techniques for evaluating performance of short term power system reliability management (2017)
Presentation / Conference Contribution
Heylen, E., Deconinck, G., Van Hertem, D., Troffaes, M. C., & Kazemtabrizi, B. (2017, September). Qualitative comparison of techniques for evaluating performance of short term power system reliability management. Presented at ISGT Europe 2017, Torino, Italy

Adequate performance evaluation of different short term reliability management approaches and criteria is crucial in order to convince transmission system operators to substitute or complement the currently used N-1 criterion with more efficient, alt... Read More about Qualitative comparison of techniques for evaluating performance of short term power system reliability management.