Abstract
Building a wind farm is a long and critical process. Many operations have to be arranged in sequence to complete and put in operation a wind farm. Typically, a wind farm is located in an exposed site, with a reduced accessibility and a limited interconnections between machines. The number of crews operating in parallel on the plant is a crucial parameter. By increasing the number of teams, the time to operation decreases but the overall commissioning cost increases. The strategy adopted to schedule the building operations can have an impact on this balance. An optimized sequence may keep the time to operation low but still limiting the number of crews involved. In this study, an optimization procedure based on a genetic algorithm was used for the minimization of the construction time of a wind farm of 200 MW selected as a case study. The problem was solved by considering an approach inspired to the Multiple Travelling Salesman Problem. An increasing number of crews was also considered to find the tradeoff between time and cost. The comparison between the results of the optimization process and those of a more traditional approach showed the benefits of an optimized approach to the problem both in terms of time to operation and costs. In particular, in the case study analyzed, a saving of almost 24% of the erection and installation time (around 280k$) was achieved only by optimizing the routes followed by the construction crews.
