An addition methodology established genetic invention (GA) is presented, where the main parts of a wind farm and key technical qualifications are used as recommendation parameters and the energetic system design of the wind farm is optimised in terms of two together production cost and scheme operation. A approximate analysis of an existent wind farm design is performed including the application of genetic algorithms (GAs) for resolution optimization. A authentic wind farm in Brazil is used in the reasoning, with the within electrical network configuration delineated by the unoriginal method of energetic engineering for judge networks with underground cables directly buried in the ground. In the expression of the GA methodology, the necessary investment in construction and current energy misfortunes are defined as objective functions in the optimisation process, and the business-related calculation of the cable is secondhand. Simulations are performed for network optimisation, and the results are executed with the project resolution in the wind farm. The influence of short circuits on network judge is also analysed. The results show the economics of an within network with the exercise of the topology of the projected optimisation method of R$168,905.32. By individually evaluating the decline in the losses and investment, it maybe observed that the saving achieved is on account of operational costs, accompanying a reduction of R $ 233,504.78. In the studied case, the avoid sizing was not considerably affected apiece diameter of the within network cable.
Author(s) Details:
Paulo Roberto Duailibe Monteiro,
Electrical Engineering Department, Fluminense Federal University – UFF, Brazil.
Thiago Trezza Borges,
Electrical Engineering Department, Fluminense Federal University – UFF, Brazil.
Andre Fernando Schiochet,
Brazilian Petroleum Company- Petrobras, Brazil.
Please see the link here: https://stm.bookpi.org/RADER-V1/article/view/10086
Keywords: Wind farm, electrical system, sizing internal network, genetic algorithm, grid optimization