Camilo, F.M.; Santos, P.J.; Lobato, P.J.; Moreira, S.B. Optimization of Offshore Wind Power Generation in Response to the 2022 Extreme Drought in Portugal. Energies2023, 16, 7542.
Camilo, F.M.; Santos, P.J.; Lobato, P.J.; Moreira, S.B. Optimization of Offshore Wind Power Generation in Response to the 2022 Extreme Drought in Portugal. Energies 2023, 16, 7542.
Camilo, F.M.; Santos, P.J.; Lobato, P.J.; Moreira, S.B. Optimization of Offshore Wind Power Generation in Response to the 2022 Extreme Drought in Portugal. Energies2023, 16, 7542.
Camilo, F.M.; Santos, P.J.; Lobato, P.J.; Moreira, S.B. Optimization of Offshore Wind Power Generation in Response to the 2022 Extreme Drought in Portugal. Energies 2023, 16, 7542.
Abstract
Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net 1 Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, extreme weather periods are occurring in a cyclical manner, with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports.
Engineering, Electrical and Electronic Engineering
Copyright:
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