Staff profile

I am a Professor of Electrical Engineering at Durham University, where I develop mathematical optimisation and physics-informed artificial intelligence (AI) methods for future power systems. My research combines power-system modelling, optimisation, machine learning and uncertainty quantification to develop fast, reliable and scalable computational methods for increasingly complex, renewable-rich and flexible electricity networks.

A major focus of my current research is the development of physics-informed AI and surrogate models for computationally intensive power-system optimisation and security assessment. This includes physics-informed neural networks (PINNs), machine-learning-assisted optimisation and data-driven models for problems such as optimal power flow (OPF), security-constrained optimal power flow (SCOPF), unit commitment, power-system stability and flexibility deployment. The aim is to exploit the speed and adaptability of AI while retaining the physical consistency and reliability required for engineering applications.

My research builds on a longstanding interest in the mathematical modelling and optimisation of complex power systems. I have developed advanced formulations for AC and hybrid AC/DC networks, including the Universal Branch Model and Convex Flexible Branch Model, and have investigated optimisation and decision-making under uncertainty in renewable-rich power systems. More recently, my work has expanded towards AI-assisted methods for accelerating optimisation, assessing operational security and enabling the effective integration of renewable generation and distributed flexibility.

My broader research interests include AI for power systems, power-system optimisation, active distribution networks, flexibility and resilience, hybrid AC/DC networks, renewable energy integration, reliability assessment, uncertainty quantification and power-system dynamics.

I welcome applications from prospective PhD students with backgrounds in electrical engineering, computer science, applied mathematics, control, data science and related disciplines, particularly those interested in combining AI, optimisation and physical modelling to address challenges in future energy systems. Current research opportunities include physics-informed AI and surrogate modelling for OPF and SCOPF, AI-assisted power-system security and stability assessment, optimisation of flexible distribution networks, and computational methods for renewable-rich power-system planning and operation.

I also welcome opportunities for collaboration with academic and industrial partners working on the operation, planning and transformation of future electricity networks.

• Advanced Power Systems Modelling
• Decision Making under Uncertainty
• Flexibility and Resiliency in Future Power Systems
• Optimal Power Flows
• Artificial Intelligence and Machine Learning applied to Power Systems
• Reliability Evaluation of Power Systems
• Renewable Energy Integration (Wind Power)
• Power System Dynamics

Authored book

• Condition Monitoring of Rotating Electrical Machines, 4th Edition
  
  Tavner, P., Crabtree, C., Kazemtabrizi, B., & Ran, L. (2026). Condition Monitoring of Rotating Electrical Machines, 4th Edition. IET. https://doi.org/10.1049/PBPO288E
• VSC-FACTS-HVDC: Modelling, Analysis and Simulation in Power Grids
  
  Acha, E., Roncero-Sánchez, P., de la Villa Jaén, A., Castro, L., & Kazemtabrizi, B. (2019). VSC-FACTS-HVDC: Modelling, Analysis and Simulation in Power Grids. Wiley.

Chapter in book

• Assessment of operation and maintenance strategies
  
  Hogg, S., Kazemtabrizi, B., & Williams, R. (2017). Assessment of operation and maintenance strategies. In S. Hogg & C. Crabtree (Eds.), UK Wind Energy Technologies (pp. 259-282). Routledge.

Conference Paper

• Bi-Level Low-Carbon Scheduling of Active Distribution Networks with Multiple Technical Virtual Power Plants in the Integrated Electricity and Carbon Markets
  
  Liu, J., Ruan, J., Tang, H., Kazemtabrizi, B., Du, H., Matthews, P. C., & Sun, H. (2025). Bi-Level Low-Carbon Scheduling of Active Distribution Networks with Multiple Technical Virtual Power Plants in the Integrated Electricity and Carbon Markets. In 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe). IEEE. https://doi.org/10.1109/ISGTEurope64741.2025.11305692
• An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning
  
  Liu, J., Kazemtabrizi, B., Du, H., Matthews, P., & Sun, H. (2025). An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning. In IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society. IEEE. https://doi.org/10.1109/IECON55916.2024.10905784
• Data-Driven Infrastructure Planning for Offshore Wind Farms
  
  Saxena, I., Kazemtabrizi, B., Troffaes, M. C., & Crabtree J., C. (2024). Data-Driven Infrastructure Planning for Offshore Wind Farms. Journal of Physics: Conference Series, 2767(6), Article 062002. https://doi.org/10.1088/1742-6596/2767/6/062002
• Minimising the Impact of Contingency in Multiple-Period Short Term Operational Planning with RAS-FUBM For Wind Integration
  
  Khadijah Hamzah, S., Kazemtabrizi, B., & Shahbazi, M. (2024). Minimising the Impact of Contingency in Multiple-Period Short Term Operational Planning with RAS-FUBM For Wind Integration. In 13th International Conference on Power Electronics, Machines and Drives (PEMD 2024) (pp. 180-187). IET. https://doi.org/10.1049/icp.2024.2155
• Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators
  
  Adeniji, O., & Kazemtabrizi, B. (2023). Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators. In 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EEEIC/ICPSEUROPE57605.2023.10194840
• Multivariate CNN-LSTM model for wind power forecast and input variables correlation analysis based on SHAPLEY values
  
  Pina-Gongora, D. C., & Kazemtabrizi, B. (2023, May 23 – 2023, May 26). Multivariate CNN-LSTM model for wind power forecast and input variables correlation analysis based on SHAPLEY values [Conference paper]. Presented at Wind Energy Science Conference (WESC) 2023, Glasgow, UK.
• Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G
  
  Thomas, H., Sun, H., & Kazemtabrizi, B. (2023). Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G. In 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isgtmiddleeast56437.2023.10078520
• Comparison of ARIMA, FARIMA, and LSTM methods for day-ahead forecasting for scenario generation for wind power systems
  
  Parker, S., & Kazemtabrizi, B. (2023). Comparison of ARIMA, FARIMA, and LSTM methods for day-ahead forecasting for scenario generation for wind power systems [Conference paper]. Presented at Wind Energy Science Conference (WESC) 2023, Glasgow, UK.
• Optimum operational planning of wind-integrated power systems with embedded Multi-terminal High Voltage Direct Current Links using the Flexible Universal Branch Model
  
  Hamzah, S. K., & Kazemtabrizi, B. (2023). Optimum operational planning of wind-integrated power systems with embedded Multi-terminal High Voltage Direct Current Links using the Flexible Universal Branch Model. In 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194786
• Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks
  
  Higuera, G., & Kazemtabrizi, B. (2023). Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks. Presented at 27th International Conference on Electricity Distribution (CIRED 2023), Rome, Italy. https://doi.org/10.1049/icp.2023.0963
• Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts
  
  Pina-Gongora, D. C., Kazemtabrizi, B., & Crabtree, C. (2022). Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts. Presented at 21st Wind and Solar Integration Workshop (WIW 2022), The Hague, Netherlands. https://doi.org/10.1049/icp.2022.2777
• Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems
  
  Cruz Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2021). Price Forecast Methodologies Comparison for Microgrid Control with Multi-Agent Systems. Presented at 14th IEEE PES PowerTech Conference, Madrid, Spain. https://doi.org/10.1109/powertech46648.2021.9494970
• Distributed Real-Time Power Management in Microgrids using Multi-agent Control with Provisions of Fault Tolerance
  
  Cruz Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2020). Distributed Real-Time Power Management in Microgrids using Multi-agent Control with Provisions of Fault Tolerance. In 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) : proceedings. (pp. 108-113). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isie45063.2020.9152548
• Optimisation of Large Offshore Wind Farm Layout Considering Reliability and Wake Effect
  
  Li, X., Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2020, January 1). Optimisation of Large Offshore Wind Farm Layout Considering Reliability and Wake Effect. Presented at ASME Turbo Expo 2020, London. https://doi.org/10.1115/gt2020-15495
• Impacts of Reliability on Operational Performance and Cost of Energy Evaluation of Multimegawatt, Far-offshore Wind Turbines
  
  Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Impacts of Reliability on Operational Performance and Cost of Energy Evaluation of Multimegawatt, Far-offshore Wind Turbines. In Conference Proceedings: ASME 38th International Conference on Ocean, Offshore & Arctic Engineering (pp. OMAE2019-95561,V003T02A072). American Society of Mechanical Engineers. https://doi.org/10.1115/omae2019-95561
• Using interval dominance and Gamma-maximin for decision making in offshore power transmission
  
  Bains, H., Kazemtabrizi, B., Madariaga, A., & Troffaes, M. C. (2019, July 3 – 2019, July 6). Using interval dominance and Gamma-maximin for decision making in offshore power transmission [Conference paper]. Presented at ISIPTA 2019, Ghent, Belgium.
• Reliability and Economic Evaluation of High Voltage Direct Current interconnectors for large-scale renewable energy integration and transmission
  
  Thompson, A., Kazemtabrizi, B., Crabtree, C., Dao, C., Dinmohamdi, F., & Flynn, D. (2019). Reliability and Economic Evaluation of High Voltage Direct Current interconnectors for large-scale renewable energy integration and transmission. In 15th IET International Conference on AC and DC Power Transmission (ACDC 2019). IET. https://doi.org/10.1049/cp.2019.0010
• Modelling the Effects of Reliability and Maintenance on Levelised Cost of Wind Energy
  
  Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Modelling the Effects of Reliability and Maintenance on Levelised Cost of Wind Energy. Presented at ASME Turbo Expo 2019, Phoenix, AZ, USA. https://doi.org/10.1115/gt2019-90015
• The Impact of Offshore Transmission Regulatory Regimes on Technology Choices
  
  Bains, H., Madariaga, A., Kazemtabrizi, B., & Troffaes, M. C. (2019). The Impact of Offshore Transmission Regulatory Regimes on Technology Choices. In Proceedings of the Cigre Symposium Aalborg, 2019. CIGRE.
• Decentralised Real-time Optimisation of Power Management in Microgrids Using Multi-Agent Control
  
  Cruz Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2019). Decentralised Real-time Optimisation of Power Management in Microgrids Using Multi-Agent Control. In 9th International Conference on Power and Energy Systems (ICPES), Perth, Australia, 2019. (pp. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/icpes47639.2019.9105639
• Contingency Ranking in Power Systems via Reliability Rates
  
  Cervantes, C., Kazemtabrizi, B., & Troffaes, M. (2018). Contingency Ranking in Power Systems via Reliability Rates. In 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) : 12-15 June, 2018, Palermo, Italy . Conference proceedings. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/eeeic.2018.8493853
• Flexible General Branch Model Unified Power Flow Algorithm for Future Flexible AC/DC Networks
  
  Bustos, A., & Kazemtabrizi, B. (2018). Flexible General Branch Model Unified Power Flow Algorithm for Future Flexible AC/DC Networks. In 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) : 12-15 June 2018, Palermo, Italy. Conference proceedings. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/eeeic.2018.8493705
• An Optimal Differential Pricing in Smart Grid Based on Customer Segmentation
  
  Meng, F., Kazemtabrizi, B., Zeng, X., & Dent, C. (2017). An Optimal Differential Pricing in Smart Grid Based on Customer Segmentation. In 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) : Torino, Italy, 26-29 September 2017 ; conference proceedings. (pp. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isgteurope.2017.8260255
• Qualitative comparison of techniques for evaluating performance of short term power system reliability management
  
  Heylen, E., Deconinck, G., Van Hertem, D., Troffaes, M. C., & Kazemtabrizi, B. (2017). Qualitative comparison of techniques for evaluating performance of short term power system reliability management. In 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) : Torino, Italy, 26-29 September 2017 : conference proceedings. (pp. 333-339). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isgteurope.2017.8260148
• Pumped Thermal Electricity Storage for Active Distribution Network Applications
  
  Ibrahim, A., Kazemtabrizi, B., Bordin, C., Dent, C., McTigue, J., & White, A. (2017). Pumped Thermal Electricity Storage for Active Distribution Network Applications. In 2017 IEEE Manchester PowerTech : 18-22 June 2017, Manchester, England ; proceedings. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ptc.2017.7980837
• Operational Planning and Optimisation in Active Distribution Networks using Modern Intelligent Power Flow Controllers
  
  Ibrahim, A., Kazemtabrizi, B., & Dent, C. (2017). Operational Planning and Optimisation in Active Distribution Networks using Modern Intelligent Power Flow Controllers. In 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/isgteurope.2016.7856196
• Impact of high wind penetration on variability of unserved energy in power system adequacy
  
  Sheehy, S., Edwards, G., Dent, C., Kazemtabrizi, B., Troffaes, M., & Tindemans, S. (2016). Impact of high wind penetration on variability of unserved energy in power system adequacy. In 2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) : Beijing, China, 16-20 October 2016 ; proceedings. (pp. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/pmaps.2016.7764199
• A new voltage instability detection index based on real-time synchronophasor measurements
  
  Chappa, H., Thakur, T., & Kazemtabrizi, B. (2016). A new voltage instability detection index based on real-time synchronophasor measurements. In 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC) : 7-10 June 2016, Florence, Italy ; proceedings. (pp. 1-5). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/eeeic.2016.7555823
• Coordinated Control of DC Voltage Magnitudes and State of Charges in a Cluster of DC Microgrids
  
  Shahbazi, M., Kazemtabrizi, B., & Dent, C. (2016). Coordinated Control of DC Voltage Magnitudes and State of Charges in a Cluster of DC Microgrids. Presented at IEEE PES Innovative Smart Grid Technologies, Ljubljana, Slovenia.
• Analysis of Two Onshore Wind Farms with a Dynamic Farm Controller
  
  Ahmad, T., Girard, N., Kazemtabrizi, B., & Matthews, P. (2015, November 20). Analysis of Two Onshore Wind Farms with a Dynamic Farm Controller. Presented at EWEA 2015, Paris, France.
• Dynamic Wind Farm Controller
  
  Ahmad, T., Matthews, P., Kazemtabrizi, B., & Smith, C. (2015, September 30). Dynamic Wind Farm Controller. Presented at 11th EAWE PhD Seminar on Wind Energy in Europe., Stuttgart, Germany.
• Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects
  
  Ahmad, T., Smith, C., Matthews, P., Crabtree, C., & Kazemtabrizi, B. (2014, October 1). Determining the Wind Speed Distribution within a Wind Farm considering Site Wind Characteristics and Wake Effects. Presented at 10th PhD Seminar on Wind Energy in Europe, EAWE., Orléans, France.
• Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms
  
  Smith, C., Crabtree, C., Matthews, P., & Kazemtabrizi, B. (2014, October 1). Modelling and Evaluation of Wind Speed Time Series for Reliability Analysis of Offshore Wind Farms. Presented at 10th PhD Seminar on Wind Energy in Europe, EAWE., Orléans, France.
• A New Simulation and Control Model for a Variable Speed Variable Pitch Direct Drive Large Offshore Wind Turbine Generator With Integrated Energy Storage
  
  Kazemtabrizi, B., & Hogg, S. (2014). A New Simulation and Control Model for a Variable Speed Variable Pitch Direct Drive Large Offshore Wind Turbine Generator With Integrated Energy Storage. In Proceedings of ASME Turbo Expo 2014 : Turbine Technical Conference and Exposition, June 16-20, 2014, Düsseldorf, Germany. American Society of Mechanical Engineers. https://doi.org/10.1115/gt2014-25682
• Reliability Evaluation of New Offshore Wind Farm Electrical Grid Connection Topologies.
  
  Kazemtabrizi, B., Crabtree, C., & Hogg, S. (2013). Reliability Evaluation of New Offshore Wind Farm Electrical Grid Connection Topologies. In Proceedings of the ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. Volume 8: Supercritical CO2 Power Cycles; Wind Energy; Honors and Awards. San Antonio, Texas, USA, June 3–7, 2013. American Society of Mechanical Engineers. https://doi.org/10.1115/gt2013-94326
• A comparison study between mathematical models of Static VAR Compensators aimed at optimal power flow solutions
  
  Kazemtabrizi, B., & Acha, E. (2012). A comparison study between mathematical models of Static VAR Compensators aimed at optimal power flow solutions. Presented at 2012 16th IEEE Mediterranean Electrotechnical Conference. https://doi.org/10.1109/melcon.2012.6196626

Journal Article

• A novel day-ahead bidding method considering real-time operational characteristic and strategy for wind-hydro hybrid power systems
  
  Lai, C., & Kazemtabrizi, B. (2026). A novel day-ahead bidding method considering real-time operational characteristic and strategy for wind-hydro hybrid power systems. Applied Energy, 408, Article 127350. https://doi.org/10.1016/j.apenergy.2026.127350
• Decentralised consensus-based hierarchical control of a hybrid AC-DC microgrid robust to communication delays
  
  Tomás-Martín, A., Kazemtabrizi, B., García-Cerrada, A., Sigrist, L., & Bueno, E. J. (2026). Decentralised consensus-based hierarchical control of a hybrid AC-DC microgrid robust to communication delays. International Journal of Electrical Power & Energy Systems, 175, Article 111645. https://doi.org/10.1016/j.ijepes.2026.111645
• A novel two-stage framework to improve the flexibility of grid connected wind-hydro power system in real-time operation
  
  Lai, C., & Kazemtabrizi, B. (2025). A novel two-stage framework to improve the flexibility of grid connected wind-hydro power system in real-time operation. Applied Energy, 396, Article 126211. https://doi.org/10.1016/j.apenergy.2025.126211
• A Vector-Based Flexible-Complexity Tool for Simulation and Small-Signal Analysis of Hybrid AC/DC Power Systems
  
  Tomás-Martín, A., Zuluaga-Ríos, C. D., Suárez-Porras, J., Kazemtabrizi, B., García-Aguilar, J., Sigrist, L., & García-Cerrada, A. (2025). A Vector-Based Flexible-Complexity Tool for Simulation and Small-Signal Analysis of Hybrid AC/DC Power Systems. Sustainable Energy, Grids and Networks, 43, Article 101817. https://doi.org/10.1016/j.segan.2025.101817
• Under Frequency Load Shedding Aware Unit Commitment in Island Power Systems
  
  Sarvarizadeh, M., Rajabdorri, M., Lobato, E., Sigrist, L., Kazemtabrizi, B., & Troffaes, M. (2025). Under Frequency Load Shedding Aware Unit Commitment in Island Power Systems. International Journal of Electrical Power & Energy Systems, 170, Article 110884. https://doi.org/10.1016/j.ijepes.2025.110884
• Convex Flexible Branch Model (CFBM): Convex Model for solving AC/DC Hybrid Networks Optimal Power Flows
  
  Higuera-Gutiérrez, G., Kazemtabrizi, B., & Mahmoud, S. (2025). Convex Flexible Branch Model (CFBM): Convex Model for solving AC/DC Hybrid Networks Optimal Power Flows. International Journal of Electrical Power & Energy Systems, 170, Article 110785. https://doi.org/10.1016/j.ijepes.2025.110785
• Data-driven estimation of the amount of under frequency load shedding in small power systems
  
  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
• A novel data-driven tighten-constraint method for wind-hydro hybrid power system to improve day-ahead plan performance in real-time operation
  
  Lai, C., & Kazemtabrizi, B. (2024). A novel data-driven tighten-constraint method for wind-hydro hybrid power system to improve day-ahead plan performance in real-time operation. Applied Energy, 371, Article 123616. https://doi.org/10.1016/j.apenergy.2024.123616
• Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning
  
  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
• Real-time resilient Microgrid power management based on multi-agent systems with price forecast
  
  Cruz-Victorio, M., Kazemtabrizi, B., & Shahbazi, M. (2023). Real-time resilient Microgrid power management based on multi-agent systems with price forecast. IET Smart Grid, 6(2), 190-204. https://doi.org/10.1049/stg2.12089
• Statistical Evaluation of Wind Speed Forecast Models for Microgrid Distributed Control
  
  Cruz Victorio, M. E., Kazemtabrizi, B., & Shahbazi, M. (2022). Statistical Evaluation of Wind Speed Forecast Models for Microgrid Distributed Control. IET Smart Grid, 5(5), 347-362. https://doi.org/10.1049/stg2.12073
• Inclusion of Frequency Stability Constraints in Unit Commitment Using Separable Programming
  
  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
• Integrated condition-based maintenance modelling and optimisation for offshore wind farms
  
  Dao, C. D., Kazemtabrizi, B., Crabtree, C. J., & Tavner, P. J. (2021). Integrated condition-based maintenance modelling and optimisation for offshore wind farms. Wind Energy, 24(11), 1180-1198. https://doi.org/10.1002/we.2625
• Closest Energy Matching: Improving peer‐to‐peer energy trading auctions for EV owners
  
  Thomas, H., Sun, H., & Kazemtabrizi, B. (2021). Closest Energy Matching: Improving peer‐to‐peer energy trading auctions for EV owners. IET Smart Grid, 4(4), 445-460. https://doi.org/10.1049/stg2.12016
• Universal Branch Model for the Solution of Optimal Power Flows in Hybrid AC/DC Grids
  
  Alvarez-Bustos, A., Kazemtabrizi, B., Shahbazi, M., & Acha, E. (2021). Universal Branch Model for the Solution of Optimal Power Flows in Hybrid AC/DC Grids. International Journal of Electrical Power & Energy Systems, 126(Part A), Article 106543. https://doi.org/10.1016/j.ijepes.2020.106543
• An Economic Model for Offshore Transmission Asset Planning Under Severe Uncertainty
  
  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
• Offshore Wind Turbine Reliability and Operational Simulation under Uncertainties
  
  Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2020). Offshore Wind Turbine Reliability and Operational Simulation under Uncertainties. Wind Energy, 23(10), 1919-1938. https://doi.org/10.1002/we.2526
• Wind Turbine Reliability Data Review and Impacts on Levelised Cost of Energy
  
  Dao, C. D., Kazemtabrizi, B., & Crabtree, C. J. (2019). Wind Turbine Reliability Data Review and Impacts on Levelised Cost of Energy. Wind Energy, 22(12), 1848-1871. https://doi.org/10.1002/we.2404
• Security-constrained day-ahead operational planning for flexible hybrid AC/DC distribution networks
  
  Asrul Ibrahim, A., Kazemtabrizi, B., & Renedo, J. (2019). Security-constrained day-ahead operational planning for flexible hybrid AC/DC distribution networks. Applied Sciences, 9(21), Article 4685. https://doi.org/10.3390/app9214685
• Uncertainty-resistant Stochastic MPC Approach for Optimal Operation of CHP Microgrid
  
  Zhang, Y., Meng, F., Wang, R., Kazemtabrizi, B., & Shi, J. (2019). Uncertainty-resistant Stochastic MPC Approach for Optimal Operation of CHP Microgrid. Energy, 179, 1265-1278. https://doi.org/10.1016/j.energy.2019.04.151
• A simplified algorithm to solve optimal power flows in hybrid VSC-based AC/DC systems
  
  Renedo, J., Ibrahim, A., Kazemtabrizi, B., Garcia-Cerrada, A., Rouco, L., Zhao, Q., & Garcia-Gonzalez, J. (2019). A simplified algorithm to solve optimal power flows in hybrid VSC-based AC/DC systems. International Journal of Electrical Power & Energy Systems, 110, 781-794. https://doi.org/10.1016/j.ijepes.2019.03.044
• Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms
  
  Ahmad, T., Basit, A., Ahsan, M., Coupiac, O., Girard, N., Kazemtabrizi, B., & Matthews, P. (2019). Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms. Energies, 12(7), Article 1266. https://doi.org/10.3390/en12071266
• Fast Processing Intelligent Wind Farm Controller for Production Maximisation
  
  Ahmad, T., Basit, A., Anwar, J., Coupiac, O., Kazemtabrizi, B., & Matthews, P. (2019). Fast Processing Intelligent Wind Farm Controller for Production Maximisation. Energies, 12(3), Article 544. https://doi.org/10.3390/en12030544
• Field Implementation and Trial of Coordinated Control of Wind Farms
  
  Ahmad, T., Coupliac, O., Petit, A., Guignard, S., Girard, N., Kazemtabrizi, B., & Matthews, P. (2018). Field Implementation and Trial of Coordinated Control of Wind Farms. IEEE Transactions on Sustainable Energy, 9(3), 1169-1176. https://doi.org/10.1109/tste.2017.2774508
• An Advanced STATCOM Model for Optimal Power Flows Using Newton's Method
  
  Kazemtabrizi, B., & Acha, E. (2014). An Advanced STATCOM Model for Optimal Power Flows Using Newton’s Method. IEEE Transactions on Power Systems, 29(2), 514-525. https://doi.org/10.1109/tpwrs.2013.2287914
• A New VSC-HVDC Model for Power Flows Using the Newton-Raphson Method
  
  Acha, E., Kazemtabrizi, B., & Castro, L. (2013). A New VSC-HVDC Model for Power Flows Using the Newton-Raphson Method. IEEE Transactions on Power Systems, 28(3), 2602-2612. https://doi.org/10.1109/tpwrs.2012.2236109
• A New STATCOM Model for Power Flows Using the Newton–Raphson Method
  
  Acha, E., & Kazemtabrizi, B. (2013). A New STATCOM Model for Power Flows Using the Newton–Raphson Method. IEEE Transactions on Power Systems, 28(3), 2455-2465. https://doi.org/10.1109/tpwrs.2012.2237186

Presentation

• Prior Elicitation for wind turbine reliability analysis
  
  Saxena, I., Kazemtabrizi, B., Troffaes, M. C. M., & Crabtree, C. J. (2025, June 24 – 2025, June 27). Prior Elicitation for wind turbine reliability analysis. Presented at Wind Energy Science Conference, Nantes, France.

Report

• KDOTS Position Paper
  
  Saxena, I., Troffaes, M., & Kazemtabrizi, B. (n.d.). KDOTS Position Paper. Durham University, Kinewell Energy.