About Me
Paul McNamara is currently employed by Eirgrid, the Irish Transmission System Operator, as a Data Scientist with the Data Team. Previously he was a Senior Engineer in the Future Networks Dept, having started in Network Planning, and instigated and chairs Eirgrid's Automation and Scripting group. In Eirgrid Paul's work has involved a range of static and dynamic power systems analyses focusing on planning studies, such as the Shaping Our Electricity Future grid studies. He has been extensively involved in automation projects and more recently has focused on data projects within his role in the Data team.
Paul graduated with first class honours in the Bachelor of Electrical and Electronic Engineering (BEEE) from University College Cork (UCC), Cork, Ireland in 2007. He then pursued his PhD in UCC in centralized and distributed control of smart electrical grids which he completed in 2012.
From 2012-2015 he was a postdoc under Prof. Seán in Maynooth University as part of the University College Dublin (UCD) led Sustainable Electrical Energy Systems (SEES) cluster. This work focused on the application of distributed and hierarchical optimisation methods to Demand Response and frequency regulation on HVDC interconnected grids.
From 2015-2017 was a Senior Researcher under Prof. Federico Milano in UCD, where he worked on automating the process of setting up Model Predictive Control modules for power systems using the Python-based Dome power systems simulation package. The applications here were a large scale model of the Irish electrical grid, and a multi-terminal HVDC system. In 2017 Paul spent a period working for the London based consultancy decisionLab where he worked using AIMMS and Python in the development of MILP based water resource planning tools.
Technical Skills
Power Systems Modelling
PSSE
Python
Optimisation
Simulation and Control Theory
Matlab
Publications
- P. Mc Namara, F. Milano, “Efficient Implementation of MPC-based AGC for Real-World Systems with Low Inertia”, Electric Power Systems Research, Vol. 158, pp. 315-323, May 2018.
- Amini, M. H., P. Mc Namara, P. Weng, O. Karabasoglu, Y. Xu, “Hierarchical Electric Vehicle Charging Aggregator Strategy Using Dantzig-Wolfe Decomposition”, IEEE Design & Test, Vol. 35, Issue 6, Dec. 2018.
- P. Mc Namara, F. Milano, “Model Predictive Control based AGC for Multi-Terminal HVDC connected AC grids”, IEEE Transactions on Power Systems, Vol. 33, pp. 1036-1048, Jan. 2018.
- R. Meere, J. Ruddy, P. Mc Namara, T. O’Donnell, "Variable AC transmission frequencies for offshore wind farm interconnection", Renewable Energy, Volume 103, pp. 321-332, April, 2017.
- P. Mc Namara, R. Meere, T. O'Donnell, S. McLoone, "Control Strategies for Automatic Generation Control over Multi-Terminal HVDC Grids", Control Engineering Practice, Volume 54, pp. 129-139, Sept., 2016.
- P. Mc Namara, R.R. Negenborn, B. De Schutter, G. Lightbody, S. McLoone, "Distributed MPC for frequency regulation in multi-terminal HVDC grids", Control Engineering Practice, Volume 46, pp. 176-187, Jan., 2016.
- P. Mc Namara, S. McLoone, "Hierarchical Demand Response for Peak Minimisation using Dantzig-Wolfe Decomposition", IEEE Transactions on Smart Grid, Volume 6, Issue 6, pp. 2807-2815, Nov. 2015.
- M. Liu, P. Mc Namara, R. Shorten, S. McLoone, "Residential electric vehicle charging strategies: the good, the bad and the ugly", Special Issue on Electric Vehicles and Their Integration with Power Grid, Journal of Modern Power Systems and Clean Energy, Volume 3, Issue 2, pp. 190-202, June, 2015.
- P. Mc Namara, R.R. Negenborn, B. De Schutter, G. Lightbody, "Optimal coordination of a multiple HVDC link system using centralised and distributed control", IEEE Transactions on Control Systems Technology, Volume 21, Issue 2, pp. 302-314, March, 2013.
- P. Mc Namara, R.R. Negenborn, B. De Schutter, G. Lightbody, "Weight optimisation for iterative distributed model predictive control applied to power networks", Engineering Applications of Artificial Intelligence, Volume 26, Issue 1, Pages 532-543, January, 2013.
- P. McNamara, R.R. Negenborn, J.C. Cañizares, M. Farina, J.M. Maestre, P. Trodden, S. Olaru, "Life lessons from and for distributed MPC – Part 1: Dynamics of cooperation", 18th IFAC Conference on Technology, Culture, and International Stability, Baku, Azerbeijan, Sept. 2018.
- P. McNamara, R.R. Negenborn, J.C. Cañizares, M. Farina, J.M. Maestre, P. Trodden, S. Olaru, "Life lessons from and for distributed MPC – Part 2: Choice of Decision Makers", 18th IFAC Conference on Technology, Culture, and International Stability, Baku, Azerbeijan, Sept. 2018.
- P. Mc Namara, A. Órtega, F. Milano "Model Predictive Control Based AGC for Multi-Terminal DC Grids”, IEEE Power and Energy Systems General Meeting, Boston, USA, July, 2016.
- A. Órtega, P. Mc Namara, F. Milano "Design of MPC-based Controller for a Generalized Energy Storage System Model”, IEEE Power and Energy Systems General Meeting, Boston, USA, July, 2016.
- P. Mc Namara, F. Milano, S. McLoone "Feasibility assessment of Plug and Play Model Predictive Control for use in DC grids", Proceedings of the 15th International Conference on Environment and Electrical Engineering, Rome, Italy, June, 2015.
- P. Mc Namara, R. Meere, T. O'Donnell, S. McLoone "Distributed MPC for Frequency Regulation in Multi-Terminal HVDC Grids", Proceedings of the IFAC World Congress, Capetown, South Africa, August, 2014.
- M. Liu, P. Mc Namara, R. Shorten, S. McLoone "Distributed Consensus Charging for Current Unbalance Reduction", Proceedings of the IFAC World Congress, Capetown, South Africa, August, 2014.
- P. Mc Namara, S. McLoone "Hierarchical demand response using Dantzig-Wolfe decomposition", Proceedings of the IEEE ISGT Europe conference, Copenhagen, Denmark, October, 2013.
- M. Liu, P. Mc Namara, S. McLoone "Fair Charging Strategies for EVs Connected to a Low-Voltage Distribution Network", Proceedings of the IEEE ISGT Europe conference, Copenhagen, Denmark, October, 2013.
- P. Mc Namara, S. McLoone "Efficient Predictive Demand Response using Laguerre functions", Best Papers Section, Proceedings of the Power and Energy Systems General Meeting, Vancouver, Canada, July 2013.
- P. Mc Namara, R.R. Negenborn, B. De Schutter, G. Lightbody "Coordination of a Multiple Link HVDC System Using Local Communications Based Distributed Model Predictive Control", Proceedings of the IFAC World Congress, Milan, Italy, August, 2011.
- P. Mc Namara, G. Lightbody "PSO optimized PID parameters for coupled HVDC control", Proceedings of the Irish Signals and Systems Conference, Cork, 2010.
- P. Mc Namara, G. Lightbody "Improving Distributed Model Predictive Control Performance Via. Weight Optimization using PSO", Proceedings of the IFAC International Conference on Intelligent Control Systems and Signal Processing, Istanbul, Turkey, September, 2009.
Links
- "Numerical Optimisation" by Nocedal and Wright: a great starting point for learning about continuous optimisation.
- "AIMMS Optimization modelling" by AIMMS: a very handy manual produced by AIMMS. In particular chapters 5 and 6 contain a great summary of the primary tricks that can be used to incorporate a variety of objectives and constraints into optimization models.
- Pyomo is an open source Python-based optimization modelling tool developed by Sandia National labs. It is becoming increasingly popular and improving in terms of functionality, proving to be a viable open source alternative to GAMS, AIMMS, etc.
- Control Tutorials for MATLAB and Simulink: a range of worked examples using Matlab and Simulink.
- Control Systems Library for Python: The python-control library performs a range of basic control and analysis tools for Python.
- APMonitor: A highly advanced model based control tool available for use with Matlab or Python. Free for both academic and commercial use.
- Dome: the Python based power systems simulation tool developed by Federico Milano.
- Open Electrical Power Systems Analysis Software List: A fairly comprehensive list of available commercial and non-commercial power systems analysis tools.
- A Beginner's Python Tutorial: a good starting place for learning Python.
- Obey the testing goat: the free online version of the absolutely fantastic book "Test-Driven development with Python: obey the testing goat using Django, Selenium, and Javascript". This is effectively a whistlestop tour of Django & Selenium (primarily), HTML, CSS, and Javascript, and how all of these can be used to create highly interactive web-pages. Projects in this book are developed using test-driven development, and so shows aspiring developers how to develop programmes from user stories using custom made tests, and how to use git in tandem with all this. An incredibly comprehensive read, to say the least, and incredibly useful for anyone looking to develop web based user interfaces using Python.
- w3schools.com: An excellent one stop shop for all things basic web development such as HTML, Javascript, SQL, etc. An absolute abundance of worked examples so you can very quickly hack working examples together. This site, in fact, is based on one of the w3.css example templates from w3schools.com!
Contact Me
Dublin, Ireland