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Dr David McMillan

Strathclyde Chancellor'S Fellow

Electronic and Electrical Engineering


A decision support tool to assist with lifetime extension of wind turbines
Rubert T., McMillan D., Niewczas P.
Renewable Energy Vol 120, pp. 423-433, (2018)
Further investigation of the relationship between main-bearing loads and wind field characteristics
Hart E, Turnbull A, McMillan D, Feuchtwang J, Golysheva E, Elliott R
Journal of Physics: Conference Series, (2018)
Heuristic algorithm for the problem of vessel routing optimisation for offshore wind farms
Dawid Rafael, McMillan David, Revie Matthew
The Journal of Engineering Vol 2017, pp. 1159–1163, (2018)
The effect of upscaling and performance degradation on onshore wind turbine lifetime extension decision making
Rubert T, McMillan D, Niewczas P
Journal of Physics: Conference Series Vol 926, (2017)
Investigation of the relationship between main-bearing loads and wind field characteristics
Hart E, Turnbull A, McMillan D, Feuchtwang J, Golysheva E, Elliott R
Journal of Physics: Conference Series Vol 926, (2017)
On modelling insights for emerging engineering problems : a case study on the impact of climate uncertainty on the operational performance of offshore wind farms
Dinwoodie Iain, McMillan David, Lazakis Iraklis, Dalgic Yalcin, Revie Matthew
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, (2017)

more publications


  • wind power forecasting
  • distribution system load flow
  • small group tutorials

Research interests


+ Reliability Analysis
+ Decision Analysis
+ Probabilistic Modelling
+ Applied Statistics



+ Wind Energy

+ Asset Management

+ Energy Policy

+ Energy Security


Other areas of Interest

  • Reliability Engineering
  • Reliability Centred Maintenance
  • Wind Turbine Safety Systems
  • Operation and Maintenance Modelling
  • Decision Analysis
  • Probabilistic Modelling


Professional activities

Probabilistic Methods Applied to Power Systems PMAPS 2018 (Journal)
Peer reviewer
A Heavy Lift Decision Support Tool
Optimisation of Wind Energy O&M Decisions Making Under Uncertainty A Heavy Lift Decision Support Tool
EPSRC (Engineering and Physical Sciences Research Council) (External organisation)
Ocean and Coastal Management (Journal)
Peer reviewer
EPSRC (Journal)
Peer reviewer

more professional activities


TIC LCPE Automated Power System Asset Data Quality Improvement (WIND-06)
McMillan, David (Principal Investigator) Connor, Richard (Co-investigator)
Period 05-Mar-2018 - 31-Aug-2018
Impact Accelerator Secondment - Kite Power Solutions [£20,343]
McMillan, David (Principal Investigator) Warnock, John (Researcher) Mills, Peter (Researcher)
Traditional Danish concept wind turbines face many constraints when upscaling in order to access higher wind speeds, such as size, mechanical loading and weight. It is possible that some of these constraints could be circumvented through use of airborne wind energy systems (AWES). With research into AWES becoming more prominent the topic of launching and landing the system must be analysed in detail. Currently different companies and research groups will have a variety of protocols and procedures regarding their individual systems. This research focuses on a kite-based system and discusses the problem of the launching and landing policy with regards to the wind speed at operational height. The paper also discusses the use of airborne powered loitering phases and grounded loitering phases. A key consideration when analysing this problem is wind speed measurement uncertainty (including the degree of temporal averaging) and how to integrate this uncertainty into any launch & land policy. The present research concerns cost-benefit analysis with respect to generated and consumed energy cost functions for each flight phase. It is found that for any given AWES there will be an optimum airborne loiter time after which a system should be landed. This avoids landings due to short-duration low wind periods. Similarly, there will be an optimum grounded loitering time to avoid costs associated with launching in short-duration periods of acceptable wind conditions. This research will be followed up by further analysis of additional cost functions such as reliability and failure aspects associated with each of the above phases. Further research will also consider the impact of short term forecasting of various accuracy levels on the optimal control policy and performance of AWES.
Period 12-Mar-2018 - 31-Aug-2018
TIC LCPE: Wind Turbine Performance Benchmarking using Copula Models (WIND-05)
Stephen, Bruce (Principal Investigator) McMillan, David (Co-investigator)
Period 29-Jan-2018 - 01-Jun-2018
Reliability-Cost Analysis of Subsea Transmission Cables (with BVG) [£10,000]
McMillan, David (Principal Investigator) Warnock, John (Researcher)
The underpinning work focusses on offshore wind, concentrating on the field of subsea transmission links to offshore wind farms. The outcomes will include a database of reliability figures for current offshore wind farms as well as a tool to determine the reliability of prospective cables over their lifetime. This is a new capability unlocked by the research, which is needed because of the lack of any published data and models in this area. The IAA will build on the outcomes of the EPSRC research and look to build new capability in BVG to assess the reliability and quantify the risk of offshore transmission assets (OFTOs) by operationalizing the research as a desktop tool.
BVG Associates will benefit from the expansion of this work which will be developed into a tool which can be used by academia and industry in order to determine the failures that will be experienced. As such the respective costs can also be calculated, as BVGs consultancy business would utilize this when performing due diligence for investors.
BVG Associates are an engineering consultancy with a focus on the sustainable energy sector. They are involved in a range of activities from site assessment and owners engineer to due diligence on asset purchases and through life management particularly for wind assets. Their activities on Levelised cost of energy (LCoE) also relate to the longer term energy cost trajectory of wind.
Recently their OFTO (offshore transmission owner) work has focused on advisory work on acquisition of OFTO assets from project developers to strategic owners (hedge funds, pension pots etc). There is a need for this service to be more grounded in operational experience (of which there is little information in the public domain). One key challenge is the relative lack of operational data on live OFTOs, to condition risk in an asset purchase and to adequately size any contingency budget. We propose that this capability should be provided by Strathclyde who have extracted operational metrics from a diverse range of sources (including marine bulletins and other published sources). Such a new model would provide greater validity than the standard business as usual approach of using Cigre report metrics – representing assets working in completely different operating regimes (large inter-country cables at very high burial depths).
Period 01-Nov-2017 - 28-Feb-2018
Advanced Offshore Wind Farm Maintenance Scheduling (with Sennen) [£10,000]
McMillan, David (Principal Investigator) Dawid, Rafael (Researcher)
EP/P019544/1 focused on improved decisions in an operational context for wind power cost reduction.
One of the new areas for improvement identified on the project was the prioritisation of maintenance tasks for the offshore despatch teams. No standard approach exists, and in discussion with a major turbine OEM it became clear that there is no optimisation done (as current business as usual) to prioritise
jobs. Strathclyde has developed an optimisation approach which shows real promise [Dawid, R., McMillan, D., Revie, M. Time series semi-markov decision process with variable costs for maintenance planning, ESREL 2016, p. 183).
This IAA will facilitate the initial build of such an optimisation capability within Sennen (Primary job of the impact champion), who will then use it to optimise maintenance at their client sites (primarily London Array).
We have demonstrated a potential availability uplift of 0.1 – 0.4% by utilising such an optimised approach [Browell, J., Dinwoodie, I., McMillan, D.; Forecasting for day-ahead offshore maintenance scheduling under uncertainty, ESREL 2016, p. 182.]. This translates to a cost saving (in terms of yield uplift) of £40,000 - £160,000 for every 100MW of offshore wind capacity (assuming 40% capacity factor).
Sennen provide software and services direct to the renewables industry, principally offshore wind. Their software platform has been extensively used for marine operations at London Array. However, the vessel routing and task
prioritization aspects of the marine operations module are fairly basic, and they would look to work with the impact champion to integrate the optimization work through the KTP. The IAA would enable this work to begin, by facilitating the necessary training of the impact champion in the technology required to integrate the algorithms.
Period 01-Nov-2017 - 15-Mar-2018
KTP - Insight Analytics
McMillan, David (Principal Investigator) Browell, Jethro (Co-investigator) Stephen, Bruce (Co-investigator)
Period 04-Sep-2017 - 03-Sep-2020

more projects


Electronic and Electrical Engineering
Royal College Building

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