Geographical Information Systems (GIS) are commonly used in renewable energy resource analysis to establish optimal locations for development. Previous work focuses either on a single technology with fixed site-selection criteria, or on small, localised areas. The potential for combining or co-locating different offshore energy technologies, particularly over a large region, has been explored previously but at a relatively low level of detail. Here, bespoke resource data from high resolution co-located, co-temporal wind and wave models are presented in a GIS with a range of additional environmental and physical parameters. Dedicated decision-support tools have been developed to facilitate flexible, multi-criteria site selections specifically for combined wind-wave energy platforms, focusing on the energy resources available. Time-series tools highlight some of the more detailed factors impacting on a site-selection decision. The results show that the main potential for combined technologies in Europe is focused to the north and west due to strong resources and acceptable depth conditions, but that there are still obstacles to be overcome in terms of constructability and accessibility. The most extreme conditions generally coincide with the maximum energy output, and access to these sites is more limited.

To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001-2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500MW. Variability on scales of greater than 6 hours is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980-2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns-the North Atlantic Oscillation and the East Atlantic Pattern.

Many countries have significant interests in generating electricity using waves and tidal current technologies. In energetic areas, waves and tidal currents interact for modifying the energy resource and impacting on the design conditions. Changes to the wave climate depend on the strength of the current and the relative wave direction. SWAN simulations of the wave climate around the Orkney Islands, with and without currents, show that considerable changes in the wave climate occur near sites of interest to wave and tidal energy project developers. Using circular statistics the effect of the relative angle between the waves and the current can be investigated. Local effects can lead to 150-200% increases in wave height when the waves oppose the current. These dramatic changes lead to an increase in wave power of over 100kWm −1 . The complex nature of the tides in the channels also leads to large changes in wave power during the so-called slack water period. Wave amplification diagrams are proposed to provide a convenient summary of wave-current effects at a particular site and allow a statistical analysis to be made. When performing resource analysis and site selection work for marine energy projects, wave-current interaction must be considered.

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Abstract-Distribution networks are increasingly required to host medium to large volumes of distributed (renewable) generation capacity. To facilitate high penetration levels of these new network participants it is crucial to adopt new control strategies in which the distribution systems are operated actively. The wide deployment of schemes such as coordinated voltage control (CVC) or non-firm connections will depend on communication and control infrastructure that is likely to be part of future Smart Grid investments. This infrastructure scenario might also make viable the use of advanced real-time measurement devices required to dynamically assess overhead line ratings. Given the inherent correlation of wind power output, wind speeds and temperature, this work is aimed at demonstrating the benefits that the adoption of dynamic ratings might bring to allow the connection of more wind power capacity. A multi-period AC Optimal Power Flow (OPF)-based technique is used to evaluate the maximum capacity of new generation considering control strategies such as dynamic ratings and CVC. The method caters for the variability of demand, wind resource and temperature. Results from a simple test feeder demonstrate the significant generation capacity gains compared to the passive operation of the network.Index Terms-Distributed generation, wind power, optimal power flow, active network management, smart grids, dynamic ratings, distribution networks.