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Dr David McMillan

Senior Lecturer

Electronic and Electrical Engineering

Publications

Key innovations & research required for floating offshore wind turbines major repairs
Ugwu Jude, McMillan David, McDonald Alasdair
WindEurope Conference & Exhibition 2018, (2018)
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)
http://dx.doi.org/10.1016/j.renene.2017.12.064
Value from free-text maintenance records : converting wind farm work orders into quantifiable, actionable information using text mining
Salo Erik, McMillan David, Connor Richard
Analysis of Operating Wind Farms 2018, (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)
http://dx.doi.org/10.1049/joe.2017.0511
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)
http://dx.doi.org/10.1088/1742-6596/926/1/012013
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)
http://dx.doi.org/10.1088/1742-6596/926/1/012010

more publications

Teaching

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

Research interests

 

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

 

Applications

+ 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

Instituto de Hidráulica Ambiental de la Universidad de Cantabria (IHCantabria)
Visiting researcher
9/7/2018
IEA WIND TASK 26 COST OF ENERGY OFFSHORE WIND WORK PACKAGEINTERNATIONAL COMPARATIVE ANALYSIS (Peer Review) (Event)
Peer reviewer
2018
Probabilistic Methods Applied to Power Systems PMAPS 2018 (Journal)
Peer reviewer
2018
Reducing wind energy cost through O&M
Speaker
2018
A Heavy Lift Decision Support Tool
Speaker
20/6/2017
Optimisation of Wind Energy O&M Decisions Making Under Uncertainty A Heavy Lift Decision Support Tool
Speaker
11/5/2017

more professional activities

Projects

​​Wind-01: Wind Turbine Fatigue Life Assessment and Modelling: Validation and Implementation
Ferguson, David (Researcher) McMillan, David (Principal Investigator) McDonald, Alasdair (Co-investigator) Leithead, William (Co-investigator) Kazacoks, Romans (Researcher) Kazemi Amiri, Abbas (Researcher)
Aim of the project was to carry out a fatigue life assessment of a wind turbine. Dr Ferguson was involved in the instrumentation of the wind turbine. This involved the installation of strain gauges at the tower base as well as an triaxial accelerometer at the top of the tower.
Period 01-Jun-2016 - 17-Aug-2018
Enhanced Wind Turbine Parts Service-Feasibility Study
Ferguson, David (Researcher) McMillan, David (Principal Investigator)
IAA funded project working in collaboration with Renewable Parts Ltd. The aim of the project was to identify components that the company could consider for refurbishment/re-manufacture. The project involved the analysis of a large volume of wind farm component consumption data and applying metrics that would allow decisions to me made on which components were suitable for re-manufacture.
Period 06-Feb-2017 - 26-May-2017
ISUFSAA Intelligent Search for Unstructured Field Service data using novel heuristics to enable Advanced Analytics
McMillan, David (Principal Investigator) Connor, Richard (Co-investigator)
Period 15-Nov-2017 - 31-Mar-2018
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

more projects

Address

Electronic and Electrical Engineering
Royal College Building

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