Reliability of Collection Grids for Large Offshore Wind Parks

Sannino, A.; Breder, Henrik; Nielsen, Erik Koldby

doi:10.1109/pmaps.2006.360415

Cited by 47 publications

(46 citation statements)

References 4 publications

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“…It can be seen that when considering medium voltage AC (MVAC) cables the estimation made in the paper by Sannino et al [7] appears to overestimate the failure rate compared to that which has been observed by wind farms with similar ratings such as Scroby Sands. However the estimations made in the analysis carried out by Underbrink et al [6] appears to underestimate the failure rate across both MVAC and High Voltage AC (HVAC), which may be as a result of basing their estimations on onshore cable reliability statistics.…”

Section: Resultsmentioning

confidence: 93%

“…In order to populate the database shown in Table 2 a number of papers and reports which focussed on reliability analysis and offshore cables were reviewed [3][4][5][6][7][8][9][10]. The reliability figures used were then converted from a number of different formats to be represented as failures / year in order to allow for comparison between different cable lengths and ratings.…”

Section: Discussionmentioning

confidence: 99%

“…As a result of this a number of authors have had to estimate failure rates such as the figures found in [3] which creates an estimate based on other literature, [4][5][6] which estimate failure rates through observation of onshore transmission reliability data and [7] which estimates a failure rate through discussion with cable manufacturers.…”

Section: Introductionmentioning

confidence: 99%

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Review of offshore cable reliability metrics

Warnock¹,

McMillan²,

Pilgrim³

et al. 2017

13th IET International Conference on AC and DC Power Transmission (ACDC 2017)

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Reliable cable systems are essential for offshore wind operation. Industry trends have led to a large number of offshore cable connections being installed recently, with 11027 MW of offshore wind connected at the end of 2015 compared to just 2955 MW in 2010 [1]. Despite the increase in connections, the publically available reliability data in this area is almost non-existent. With several connections in planning of both similar and increasing lengths it is essential to better understand these metrics.A review of published reliability data was undertaken in order to populate a database which is presented in this paper. This data focusses on a number of connection types including both AC and DC connections across a number of cable ratings and configurations. From this database it is confirmed that reliability figures currently being used across the literature generally conform to those currently being experienced in the offshore wind industry. However it is established that failure rates taken from some reports are not accurate as the technology and environments these are calculated from are typically different from those used in offshore wind farm connections. This information is collated and converted into reliability metrics in order for comparisons to be made.Analysis of the cost of an outage experienced by a windfarm is also carried out in this paper. The results of which establish that the revenue lost from a cable failure could potentially be substantial. The findings in this paper would also suggest a greater risk of failure in the early life of a windfarm and as such a greater potential cost associated with this risk.It is important to have a better understanding of offshore renewable energy cable connections as the reliability of a cable has a significant impact on the Levelised Cost of Energy. With a greater understanding of the metrics investors can make more informed decisions with respect to the technology that is installed as well as the importance of the installation process itself, due diligence on subsequent OFTO asset purchases and the maintenance plans that have been outlined for the connection.

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Section: Resultsmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Review of offshore cable reliability metrics

Warnock¹,

McMillan²,

Pilgrim³

et al. 2017

13th IET International Conference on AC and DC Power Transmission (ACDC 2017)

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show abstract

“…7,12 Assumed that the busbar of wind farm has 10 feeders, and each feeder has 7 WTGs. Each WTG unit has a rated power output of 2 MW.…”

Section: Case Studiesmentioning

confidence: 99%

Reliability evaluation for electrical collector systems of wind farm using the section enumeration technique

Xie

Yang

et al. 2013

Journal of Renewable and Sustainable Energy

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Topology has a significant effect on the reliability performance of an electrical collector system (ECS) of wind farms. Novel indices for the reliability of wind farm ECS are presented based on topological features of wind farm ECS in this paper. The concept of the section for a wind farm ECS is defined. The probability table of multistate capacity (PTMC) for a wind turbine generator (WTG) and the Probability Table of the Number of WTG in Up-state (PTNU) for a section can be created. Based on the PTMC and PTNU, PTMC of a wind farm can be established using the state enumeration algorithm and the matrix operations. Therefore, the reliability evaluation model considering effects of wind speed and component failures can be built. The proposed model not only considers the multi-failures of ECS components including failures of cable feeder, WTG, and wind turbine transformer (WTT) but also states of switching devices in failure, disconnection, and switching processes. Four wind farm ECS topologies, i.e., radial topology, single-sided ring topology, double-sided ring topology, and star topology, are implemented. Case studies on the reliability evaluation of wind farm ECS are used to verify the feasibility and validity of the proposed technique. V C 2013 AIP Publishing LLC. [http://dx.NOMENCLATURE U i unavailability of the ith component A j availability of the jth component v t wind speed at the tth hour P(v t )power output of a WTG at the tth hour P r rated power output of a WTG v ci , v r , v co cut-in, rated, and cut-out wind speeds of a WTG, respectively N s-wf number of sections in a wind farm ECS N w-s number of total WTGs in a section N w-wf number of total WTGs in a wind farm N ts-w number of total states for PTMC of a WTG N ts-wf number of total states for PTMC of a wind farm t re repair time of a failed component, which equals the time interval from the moment of the occurrence of component failure to the moment of the failed component being repaired t ds disconnection time, which equals the time interval from the moment of the occurrence of component failure to the moment of the failed component being isolated a) Electronic

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“…Though computational complexity could be ascertained to each of these methods each work strikes effectively in terms of the algorithm proposed. Reference [8] provides quantified values for offshore WF reliability with main focus on the foremost electrical installations. Influential factors in determining the outage data of such farms are also taken into account.…”

Section: Introductionmentioning

confidence: 99%

Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit

Subramanian

Attya

Hartkopf

2014

2014 16th International Conference on Harmonics and Quality of Power (ICHQP)

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The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.

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Reliability of Collection Grids for Large Offshore Wind Parks

Cited by 47 publications

References 4 publications

Review of offshore cable reliability metrics

Review of offshore cable reliability metrics

Reliability evaluation for electrical collector systems of wind farm using the section enumeration technique

Novel Wind Turbine reliability model-implementation to estimate Wind Farms capacity credit

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