This paper presents a methodology for the forward estimation of thermal risk in offshore wind farm cables under scenarios where the farm is overplanted for economic purposes. A dynamic thermal rating assessment of the cable is proposed to estimate the thermal effects of probable load current scenarios considering actual temperatures. Calculated future temperatures are used to estimate the probability of the cable being overheated. Due to the ability of the method to estimate forward thermal risk, unnecessary power curtailment can be reduced while avoiding thermal damage to the cable. Simulated results of online thermal risk estimation and curtailment show additional power delivery of 7.26%, 9.16% and 9.67% per year for a 6% 9.9% and 13.7% wind farm overplanting respectively. The additional power is calculated compared to the annual power delivered (W h/year) with the use of the traditional continuous rating limits for the case studied.
This paper demonstrates the impact of using realistic wind power generation profiles, timevarying ocean bottom temperatures and hypothetical wind farm over-planting scenarios on export cable capacity optimisation. Given the inherent risk in over-planting, a novel hour ahead thermal risk estimation method was developed to foresee and mitigate cable temperature exceedance, employing a preventive curtailment. Two offshore wind farm locations L1(North-west European Shelf) and L2(Australian Shelf) have been chosen for testing but utilising real wind and ocean bottom temperature data. These simulated results demonstrate a 10% rating increment over the static rating in L1 resulted in a 13% increment in the amount of energy delivered over a year (MWh/year) without any risk or instances of thermal overheating. Similarly, a 9.8% rating increment in L2 resulted in a 13.6% increment in annual energy transmission (MWh/year). The financial increment for both over-planting scenarios was approximately £9 million/year for the studied cases. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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