scholarly journals An overall performance index for wind farms: a case study in Norway Arctic region

Author(s):  
Albara M. Mustafa ◽  
Abbas Barabadi ◽  
Tore Markeset ◽  
Masoud Naseri

AbstractWind farms (WFs) experience various challenges that affect their performance. Mostly, designers focus on the technical side of WFs performance, mainly increasing the power production of WFs, through improving their manufacturing and design quality, wind turbines capacity, their availability, reliability, maintainability, and supportability. On the other hand, WFs induce impacts on their surroundings, these impacts can be classified as environmental, social, and economic, and can be described as the sustainability performance of WFs. A comprehensive tool that combines both sides of performance, i.e. the technical and the sustainability performance, is useful to indicate the overall performance of WFs. An overall performance index (OPI) can help operators and stakeholders rate the performance of WFs, more comprehensively and locate the weaknesses in their performance. The performance model for WFs, proposed in this study, arranges a set of technical and sustainability performance indicators in a hierarchical structure. Due to lack of historical data in certain regions where WFs are located, such as the Arctic, expert judgement technique is used to determine the relative weight of each performance indicator. In addition, scoring criteria are predefined qualitatively for each performance indicator. The weighted sum method makes use of the relative weights and the predefined scoring criteria to calculate the OPI of a specific WF. The application of the tool is illustrated by a case study of a WF located in the Norwegian Arctic. Moreover, the Arctic WF is compared to another WF located outside the Arctic to illustrate the effects of Arctic operating conditions on the OPI.

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4439
Author(s):  
Albara M. Mustafa ◽  
Abbas Barabadi

Infrastructure systems, such as wind farms, are prone to various human-induced and natural disruptions such as extreme weather conditions. There is growing concern among decision makers about the ability of wind farms to withstand and regain their performance when facing disruptions, in terms of resilience-enhanced strategies. This paper proposes a probabilistic model to calculate the resilience of wind farms facing disruptive weather conditions. In this study, the resilience of wind farms is considered to be a function of their reliability, maintainability, supportability, and organizational resilience. The relationships between these resilience variables can be structured using Bayesian network models. The use of Bayesian networks allows for analyzing different resilience scenarios. Moreover, Bayesian networks can be used to quantify resilience, which is demonstrated in this paper with a case study of a wind farm in Arctic Norway. The results of the case study show that the wind farm is highly resilient under normal operating conditions, and slightly degraded under Arctic operating conditions. Moreover, the case study introduced the calculation of wind farm resilience under Arctic black swan conditions. A black swan scenario is an unknowable unknown scenario that can affect a system with low probability and very high extreme consequences. The results of the analysis show that the resilience of the wind farm is significantly degraded when operating under Arctic black swan conditions. In addition, a backward propagation of the Bayesian network illustrates the percentage of improvement required in each resilience factor in order to attain a certain level of resilience of the wind farm under Arctic black swan conditions.


2014 ◽  
Vol 8 (1) ◽  
pp. 52-62 ◽  
Author(s):  
Yousong Wang ◽  
Honglei Yi ◽  
Mian Fang

Sustainable principles have been applied in many sectors including the construction industry. In light of this requirement, delivery and operation of public funded projects have been given particular attention since they are seen as benchmarks in this industry and possess more significant impact on economy, environment, society, resource utilization, health and safety, as well as project governance. Current studies on assessing sustainability performance of these projects are found to have some gaps. By calculating the sustainability performance indicator, the research reported in this paper introduced an improved System Dynamic model addressing the impact of policies and stakeholders’ perceptions based on the previous studies. In addition, the improved model alters the way in which sustainability performance indicator evolves to make it more precise. A real stadium project in Shenzhen, China is presented to illustrate the application of the improved model in appraising the sustainability performance of public funded projects. The case study also reveals the aspects to be enhanced to make the sustainability performance better in this project.


2017 ◽  
Vol 1 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Nina Lansbury Hall ◽  
Jarra Hicks ◽  
Taryn Lane ◽  
Emily Wood

The wind industry is positioned to contribute significantly to a clean energy future, yet the level of community opposition has at times led to unviable projects. Social acceptance is crucial and can be improved in part through better practice community engagement and benefit-sharing. This case study provides a “snapshot” of current community engagement and benefit-sharing practices for Australian wind farms, with a particular emphasis on practices found to be enhancing positive social outcomes in communities. Five methods were used to gather views on effective engagement and benefit-sharing: a literature review, interviews and a survey of the wind industry, a Delphi panel, and a review of community engagement plans. The overarching finding was that each community engagement and benefit-sharing initiative should be tailored to a community’s context, needs and expectations as informed by community involvement. This requires moving away from a “one size fits all” approach. This case study is relevant to wind developers, energy regulators, local communities and renewable energy-focused non-government organizations. It is applicable beyond Australia to all contexts where wind farm development has encountered conflicted societal acceptance responses.


2020 ◽  
Vol 9 (10) ◽  
pp. 563
Author(s):  
Alejandro Zunino ◽  
Guillermo Velázquez ◽  
Juan Pablo Celemín ◽  
Cristian Mateos ◽  
Matías Hirsch ◽  
...  

Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saeed Peyghami ◽  
Tomislav Dragicevic ◽  
Frede Blaabjerg

AbstractThis paper proposes a long-term performance indicator for power electronic converters based on their reliability. The converter reliability is represented by the proposed constant lifetime curves, which have been developed using Artificial Neural Network (ANN) under different operating conditions. Unlike the state-of-the-art theoretical reliability modeling approaches, which employ detailed electro-thermal characteristics and lifetime models of converter components, the proposed method provides a nonparametric surrogate model of the converter based on limited non-linear data from theoretical reliability analysis. The proposed approach can quickly predict the converter lifetime under given operating conditions without a further need for extended, time-consuming electro-thermal analysis. Moreover, the proposed lifetime curves can present the long-term performance of converters facilitating optimal system-level design for reliability, reliable operation and maintenance planning in power electronic systems. Numerical case studies evaluate the effectiveness of the proposed reliability modeling approach.


Energy ◽  
2021 ◽  
Vol 221 ◽  
pp. 119902
Author(s):  
Amir Reza Razmi ◽  
M. Soltani ◽  
Armin Ardehali ◽  
Kobra Gharali ◽  
M.B. Dusseault ◽  
...  

2019 ◽  
Vol 9 (20) ◽  
pp. 4406
Author(s):  
Seongkwan Lee ◽  
Amr Shokri ◽  
Abdullah Al-Mansour

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.


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