Offshore wind is a relatively new industry and it is generally more expensive to generate electricity than many alternative renewable sources. Operation & Maintenance (O&M) makes up a significant part of the overall cost of running Offshore Wind Turbines (OWT). Since the O&M associated responsibility is shared among turbine manufacturers, wind farm operators and the offshore transmission owners, this has inevitably led to lack of information, duplication of effort and less efficiency. Big data analytics is one great technique that will drive future growth. In this paper, an integrated operational system of offshore wind farm is proposed deploying big data analytics. Firstly, the current state of the O&M of offshore wind farm and the big data analytics are introduced. Afterwards, a predictive maintenance model and a maintenance implementation model are proposed, and an integrated operational system is developed incorporating those two models in order to optimize maintenance planning and implementation. Finally, the possible contribution of such a system to a more effective O&M of offshore wind farm is discussed. @en

Maritime accidents and incidents, such as ship to ship collision or ship grounding, most often occur near ports due to the intensive water traffic and shallow water depth. The occurrence of those accidents place a port in a very dangerous situation, since the port could suffer from a high risk of blockage of port entry, and the consequent economic loss can be substantial. In the case of maritime accidents, it is of great significance for sea-going ships outside of the accident zone to determine a safe and smooth sailing route and efficient speeds at a busy port, thus to reduce the risk of blockage and the economic loss of the port, whilst not disturbing the current emergency logistic response system. In this regard, a decision-making method for safe and smooth sailing route and efficient speeds for sea-going ships encountering an accident can be very valuable. Because of the high nonlinearity of these decisions, PSO algorithm is used to search the safe and smooth sailing route and efficient speeds. The study results show that the proposed method can effectively achieve the safe and smooth sailing route and efficient speeds for ships encountering an accident, thus to be more economic and reduce the risky chance of blockage of the port entry.@en

In this paper, the thermal field of a large scale permanent magnet embedded salient pole wind generator (PMESPWG) is investigated by using the computational fluid dynamic (CFD) modeling. To reduce the calculation, only one quarter model of the PMESPWG is established according to its symmetry. Based on the electromagnetic analysis and the empirical equations, the copper loss, stator iron loss and rotor loss are calculated and then used as the heat source in the thermal field analysis. The temperature distributions in the generator are predicted by finite element method (FEM). The calculated results are discussed and verified by the measured ones. The analysis results show that the modelling method can provide a valuable evaluation for electromagnetic and thermal designs in the design stage. The generator temperature variation with fan speed is also discussed, which supplies a reliable reference for the cooling system optimization.

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The impedenace change that occurs when the user holds a mobile phone antenna is a well-known problem. This paper analyses the contributions to this change for a dual-band PIFA. In particular, the contribution of the slot is shown and a method of reducing it is proposed and analyzed.@en