Bio-objective long-term maintenance scheduling for wind turbines in multiple wind farms

2020 ◽  
Vol 160 ◽  
pp. 1136-1147
Author(s):  
Yifan Zhou ◽  
Jindan Miao ◽  
Bin Yan ◽  
Zhisheng Zhang
SIMULATION ◽  
2021 ◽  
pp. 003754972110286
Author(s):  
Eduardo Pérez

Wind turbines experience stochastic loading due to seasonal variations in wind speed and direction. These harsh operational conditions lead to failures of wind turbines, which are difficult to predict. Consequently, it is challenging to schedule maintenance actions that will avoid failures. In this article, a simulation-driven online maintenance scheduling algorithm for wind farm operational planning is derived. Online scheduling is a suitable framework for this problem since it integrates data that evolve over time into the maintenance scheduling decisions. The computational study presented in this article compares the performance of the simulation-driven online scheduling algorithm against two benchmark algorithms commonly used in practice: scheduled maintenance and condition-based monitoring maintenance. An existing discrete event system specification simulation model was used to test and study the benefits of the proposed algorithm. The computational study demonstrates the importance of avoiding over-simplistic assumptions when making maintenance decisions for wind farms. For instance, most literature assumes maintenance lead times are constant. The computational results show that allowing lead times to be adjusted in an online fashion improves the performance of wind farm operations in terms of the number of turbine failures, availability capacity, and power generation.


2014 ◽  
Vol 51 (4) ◽  
pp. 15-24
Author(s):  
A. Mutule ◽  
O. Kochukov

Abstract An approach is proposed to the modelling of wind farms in the electric power system long-term planning. It allows a specialist to perform calculations based on scanty information and offers a set of ready-to-use data for easy, fast, and precise modelling. The authors exemplify the calculations of wind speed probability density and power curves and give an idea for relevant corrections. They also show how to pass from a single wind turbine model to the unified model of multiple wind turbines which would meet the requirements of long-term planning tasks. The paper presents the data on wind farms that are operating in UK and Oceania


2020 ◽  
Vol 216 ◽  
pp. 01020
Author(s):  
Vladislav Shakirov ◽  
Victor Kurbatsky ◽  
Nikita Tomin ◽  
Huseyngulu Guliyev

The article deals with the problem of the negative impact of wind farms stochastic generation on power grid. One of the ways to reduce the stochasticity of the wind farms generation is their geographically distributed siting. A technique for sizing and distributed siting of wind farms from the standpoint of the influence on the variability of the total generated power is proposed. Modeling of wind power generation with hourly detailing is carried out using the developed Wind-MCA software based on data from archives of long-term observations of ground-based weather stations. The optimal distribution of wind turbines in potential locations is based on a genetic algorithm. The objective function is the coefficient of variation of the power generated by all wind farms in the sites under consideration, depending on the number of wind turbines in their composition. The genetic algorithm is implemented using the built-in MATLAB function. The proposed technique is applied to assess the capacity options and sites for wind farms in the Zabaykalsky Krai. The solution providing the minimum value of the coefficient of variation of the wind farms generated power and high value of the wind farms capacity utilization factor has been obtained.


2021 ◽  
Author(s):  
Kai-tung Ma ◽  
Yongyan Wu ◽  
Simen Fodstad Stolen ◽  
Leopoldo Bello ◽  
Menno ver der Horst ◽  
...  

Abstract As renewable energy developers start venturing into deeper waters, the floating offshore wind turbines (FOWTs) are becoming the preferred solutions over fixed supporting structures. Many similarities can be identified between a FOWT and a floating oil & gas facility, such as floater concepts (spar, semi-submersible, tension leg platform, etc) and their mooring system designs. This paper focuses on the mooring designs for FOWTs by leveraging the extensive experience gained from the offshore oil & gas industry. Similarities and differences are highlighted in design criteria, mooring analysis, long-term integrity management, installation method and project execution. The established practices regarding mooring design and analysis are reviewed. Anchor radius is recommended based on water depth by referencing sample mooring designs from the oil & gas industry. Long-term mooring integrity and failure rates are summarized. Meanwhile, a few well-known issues are discussed, such as line break due to fatigue, corrosion on chain, and known issues with components such as clump weights. Regarding mooring installation, the established method for prelay and hook-up is reviewed. Finally, opportunities for cost reduction of mooring systems of FOWTs are presented related to project execution of large scale wind farms as well as potential areas of innovation, such as installation methods, use of synthetic fiber rope, and digitalization. In summary, the state-of-the-art practices from the oil & gas industry are reviewed and documented to benefit the developments of upcoming FOWT projects.


2018 ◽  
Vol 14 (5) ◽  
pp. 1909-1919 ◽  
Author(s):  
Hamed Mirsaeedi ◽  
Alireza Fereidunian ◽  
Seyed Mohsen Mohammadi-Hosseininejad ◽  
Payman Dehghanian ◽  
Hamid Lesani

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianxue Wang ◽  
Jianming Lu ◽  
Zhaohong Bie ◽  
Shutang You ◽  
Xiaoyu Cao

Asset management of distribution systems is an important issue for smart grid. Maintenance scheduling, as an important part of asset management, affects the reliability of distribution equipment and power supply. This research focuses on long-term distribution system maintenance scheduling aided by available operation information, which is a prominent advantage of smart grid over conventional distribution systems. In this paper, the historical and future operation information in smart grid is taken into account through a decoupled time-varying reliability model of equipment. Based on distribution system reliability assessment, a maintenance scheduling model is proposed to determine the optimal implementation time of maintenance activities to minimize distribution systems’ total cost, while satisfying reliability requirements. A combined algorithm that consists of particle swarm optimization and tabu search is designed and applied to the optimization problem. Numerical result verifies that the proposed method can schedule long-term maintenance of distribution systems in smart grid economically and effectively.


2001 ◽  
Vol 120 (5) ◽  
pp. A613-A613
Author(s):  
P BORNMAN ◽  
K RADEBOLD ◽  
H DEBAERE ◽  
L VENTER ◽  
H HEINZE ◽  
...  

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