Renewable energy (RE) sources have gained a great importance due to their inexhaustibility, sustainability, ecological awareness and supply of energy security. Among all RE sources, wind energy is currently viewed as one of the most significant fastest growing (at an average annual growth rate of more that 26% since 1990), commonly used and commercially attractive source to generate electrical energy.The vision of the wind industry in Europe is to increase wind’s fraction of electrical energy mix to more than 20% within the next 2 decades. To implement this, an average 10-15GW of additional capacity must be manufactured, delivered and implemented every year in Europe. In order to achieve this, further improvements in wind turbine technology are still needed. Wind turbines are not new concepts but still face challenges as a stable and reliable source of energy – issues with efficiency, operations, maintenance and its general costs.There is a need to reduce the rate of electrical system faults and the corresponding downtime per fault which will contribute significantly to the overall reduction of the operational and maintenance cost associated with current and future wind turbines. This project aims to develop an advanced diagnostics and predictive maintenance intelligent sensor system network for Wind Turbine (with particular focus on faults, failures and breakdowns relating to the electrical system of the wind turbine).