Optimization of Offshore Wind Farms Configuration Minimizing the  Wake Effect

Jesus, Beatriz; Cerveira, Adelaide; Baptista, José

doi:10.24084/repqj20.211

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…[13] PSO Does not guarantee finding the optimal solution. [23,24] MILP Gives the optimal solution to the problem. [25] ML/DNN Does not guarantee finding the optimal solution within an absolute error of 1.5%.…”

Section: Aocspmentioning

confidence: 99%

“…Constraint (23) guarantees that the network connects all the selected WTs. Constraints (24) guarantee that each WT has one incoming connection. Constraints (25) are the flow conservation constraints and guarantee that, for each WT j ∈ N, if an incoming connection supporting t downstream WTs exists, then the outgoing connections from WT j must support t − 1 downstream WTs.…”

Section: Cable Connection Layout Modelmentioning

confidence: 99%

“…In Lima et al [23], Jensen's model was used to calculate the wake effect only considering the predominant wind speed. From another perspective, the Jensen model was used to calculate the wake effect considering all wind speeds obtaining the maximum energy production and the minimum levelised cost of energy (LCOE) [24]. This model enables the optimal positioning of WTs to achieve maximum energy efficiency while considering losses due to the wake effect.…”

Section: Introductionmentioning

confidence: 99%

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Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses

et al. 2023

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The last two decades have witnessed a new paradigm in terms of electrical energy production. The production of electricity from renewable sources has come to play a leading role, thus allowing us not only to face the global increase in energy consumption, but also to achieve the objectives of decarbonising the economies of several countries. In this scenario, where onshore wind energy is practically exhausted, several countries are betting on constructing offshore wind farms. Since all the costs involved are higher when compared to onshore, optimising the efficiency of this type of infrastructure as much as possible is essential. The main aim of this paper was to develop an optimisation model to find the best wind turbine locations for offshore wind farms and to obtain the wind farm layout to maximise the profit, avoiding cable crossings, taking into account the wake effect and power losses. The ideal positioning of wind turbines is important for maximising the production of electrical energy. Furthermore, a techno-economic analysis was performed to calculate the main economic indicators, namely the net present value, the internal rate of return, and the payback period, to support the decision-making. The results showed that the developed model found the best solution that maximised the profits of the wind farm during its lifetime. It also showed that the location of the offshore substation played a key role in achieving these goals.

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Section: Aocspmentioning

confidence: 99%

Section: Cable Connection Layout Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses

et al. 2023

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The Impact of Optimizing Hybrid Renewable Energy System on Wine Industry Sustainability

Jesus,

Cerveira,

Santos

et al. 2024

2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

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Self-Sustainability Assessment for a High Building Based on Linear Programming and Computational Fluid Dynamics

2023

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With excess energy use from non-renewable sources, new energy generation solutions must be adopted to make up for this excess. In this sense, the integration of renewable energy sources in high-rise buildings reduces the need for energy from the national power grid to maximize the self-sustainability of common services. Moreover, self-consumption in low-voltage and medium-voltage networks strongly facilitates a reduction in external energy dependence. For consumers, the benefits of installing small wind turbines and energy storage systems include tax benefits and reduced electricity bills as well as a profitable system after the payback period. This paper focuses on assessing the wind potential in a high-rise building through computational fluid dynamics (CFD) simulations, quantifying the potential for wind energy production by small wind turbines (WT) at the installation site. Furthermore, a mathematical model is proposed to optimize wind energy production for a self-consumption system to minimize the total cost of energy purchased from the grid, maximizing the return on investment. The potential of a CFD-based project practice that has wide application in developing the most varied processes and equipment results in a huge reduction in the time and costs spent compared to conventional practices. Furthermore, the optimization model guarantees a significant decrease in the energy purchased at peak hours through the energy stored in energy storage systems (ESS). The results show that the efficiency of the proposed model leads to an investment amortization period of 7 years for a lifetime of 20 years.

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Optimization of Offshore Wind Farms Configuration Minimizing the Wake Effect

Cited by 3 publications

References 13 publications

Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses

Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses

The Impact of Optimizing Hybrid Renewable Energy System on Wine Industry Sustainability

Self-Sustainability Assessment for a High Building Based on Linear Programming and Computational Fluid Dynamics

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