Simulation of Wind Farm Operations and Maintenance

2013 ◽  
Author(s):  
Eduardo Pérez ◽  
Lewis Ntaimo ◽  
Yu Ding
Keyword(s):  
Wind Farm ◽  
Discrete Event ◽  
Maintenance Scheduling ◽  
Simulation Framework ◽  
Structural Element ◽  
Maintenance Strategies ◽  
Random Events ◽  
Operations And Maintenance ◽  
Event Based ◽  
Commercial Size

We develop a discrete event-based simulation framework that mimics the operations of a commercial size wind farm. Each turbine is treated as separate module, so that the simulation can be easily scaled up to more than one hundred turbines for a farm. Each turbine module includes a structural element sub-module, degradation sub-module, power generation sub-module, sensing and maintenance scheduling sub-module. The simulator is specially designed to handle a large number of unorganized random events (turbine failures, waiting for parts, weather disruptions) and reflect in the simulator’s outputs the variation from parameters and operations. We report on implementation results and provide insights into wind farm operations under different maintenance strategies.

A simulation-driven online scheduling algorithm for the maintenance and operation of wind farm systems

SIMULATION ◽  
2021 ◽  
pp. 003754972110286
Author(s):  
Eduardo Pérez
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Computational Study ◽  
Scheduling Algorithm ◽  
Discrete Event ◽  
Wind Farms ◽  
Online Scheduling ◽  
Maintenance Scheduling ◽  
Lead Times ◽  
System Specification

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.

scholarly journals Using a New Event-Based Simulation Framework for Investigating Resource Provisioning in Clouds

2011 ◽  
Vol 19 (2-3) ◽  
pp. 161-178 ◽  
Author(s):  
Simon Ostermann ◽  
Kassian Plankensteiner ◽  
Radu Prodan
Keyword(s):  
Large Scale ◽  
Discrete Event ◽  
Resource Provisioning ◽  
Attractive Alternative ◽  
Simulation Framework ◽  
File Transfers ◽  
Complex Simulation ◽  
Event Based ◽  
The Impact ◽  
Cloud Resources

Today, Cloud computing proposes an attractive alternative to building large-scale distributed computing environments by which resources are no longer hosted by the scientists' computational facilities, but leased from specialised data centres only when and for how long they are needed. This new class of Cloud resources raises new interesting research questions in the fields of resource management, scheduling, fault tolerance, or quality of service, requiring hundreds to thousands of experiments for finding valid solutions. To enable such research, a scalable simulation framework is typically required for early prototyping, extensive testing and validation of results before the real deployment is performed. The scope of this paper is twofold. In the first part we present GroudSim, a Grid and Cloud simulation toolkit for scientific computing based on a scalable simulation-independent discrete-event engine. GroudSim provides a comprehensive set of features for complex simulation scenarios from simple job executions on leased computing resources to file transfers, calculation of costs and background load on resources. Simulations can be parameterised and are easily extendable by probability distribution packages for failures which normally occur in complex distributed environments. Experimental results demonstrate the improved scalability of GroudSim compared to a related process-based simulation approach. In the second part, we show the use of the GroudSim simulator to analyse the problem of dynamic provisioning of Cloud resources to scientific workflows that do not benefit from sufficient Grid resources as required by their computational demands. We propose and study four strategies for provisioning and releasing Cloud resources that take into account the general leasing model encountered in today's commercial Cloud environments based on resource bulks, fuzzy descriptions and hourly payment intervals. We study the impact of our techniques to the overall execution time, overall cost and cost per unit of saved time with respect to various instance types offered by the Amazon EC2.

A new multi-fidelity flow-acoustics simulation framework for wind farm application

2022 ◽  
Vol 156 ◽  
pp. 111939
Author(s):  
Jiufa Cao ◽  
Camilla Marie Nyborg ◽  
Ju Feng ◽  
Kurt S. Hansen ◽  
Franck Bertagnolio ◽  
...  
Keyword(s):  
Wind Farm ◽  
Simulation Framework

scholarly journals Value-Centric Approaches to Design, Operations, and Maintenance of Wind Turbines

2013 ◽  
Author(s):  
Madhur A. Khadabadi ◽  
Karen B. Marais
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Farm ◽  
Net Present Value ◽  
Operating Cost ◽  
Optimal Level ◽  
Two Dimensions ◽  
Alternative View ◽  
Operations And Maintenance ◽  
Farm Operators

Wind turbine maintenance is emerging as an unexpectedly high component of turbine operating cost and there is an increasing interest in managing this cost. Here, we present an alternative view of maintenance as a value-driver, and develop an optimization algorithm to maximize the value delivered by maintenance. We model the stochastic deterioration of the turbine in two dimensions: the deterioration rate, and the extent of deterioration, and view maintenance as an operator that moves the turbine to an improved state in which it can generate more power and so earn more revenue. We then use a standard net present value (NPV) approach to calculate the value of the turbine by deducting the costs incurred in the installation, operations and maintenance from the revenue due to the power generation. The application of our model is demonstrated using several scenarios with a focus on blade deterioration. We evaluate the value delivered by implementing blade condition monitoring systems (CMS). A higher fidelity CMS allows the blade state to be determined with higher precision. With this improved state information, an optimal maintenance strategy can be derived. The difference between the value of the turbine with and without CMS can be interpreted as the value of the CMS. The results indicate that a higher fidelity (and more expensive) condition monitoring system (CMS) does not necessarily yield the highest value, and, that there is an optimal level of fidelity that results in maximum value. The contributions of this work are twofold. First, it is a practical approach to wind turbine valuation and operation that takes operating and market conditions into account. This work should therefore be useful to wind farm operators and investors. Second, it shows how the value of a CMS can be explicitly assessed. This work should therefore be useful to CMS manufacturers and wind farm operators.

Arena-Based Modeling of the Maintenance Operation for a Wind Farm

2013 ◽  
Vol 401-403 ◽  
pp. 2205-2208 ◽  
Author(s):  
Huai Zhong Li ◽  
Tong Jing ◽  
Hong Zhang
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Discrete Event ◽  
Onshore Wind ◽  
Electric System ◽  
System A ◽  
Factors Influencing ◽  
Event Model ◽  
Main Factors ◽  
Discrete Event Model

Wind energy has become a leading developing direction in electric power. The high cost associated with turbine maintenance is a key challenging issue in wind farm operation as wind turbines are hard-to access for inspection and repair. Analysis of an onshore wind farm is carried out in this paper in terms of the operation, failure, and maintenance. Failures are categorized into three classes according to the downtime. It is found that the pitch, gearbox and generator have the most amount of downtime, while the most number of failures is from the pitch and electric system. A discrete-event model is developed by using Arena to simulate the operation, failure occurrence, and maintenance of the wind turbines, with an aim to determine the main factors influencing maintenance costs and the availability of the turbines in the wind farm.

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