Estimation of Weibull parameters for wind energy analysis across the UK

Abstract This study aimed to compare the graphical method (GM) and standard deviation method (SDM), based on analyses and efficient Weibull parameters by estimating future wind energy potential in the coastline region of Dar es Salaam, Tanzania. Hence, the conclusion from the numerical method comparisons will also determine suitable wind turbines that are cost-effective for the study location. The wind speed data for this study were collected by the Tanzania Meteorological Authority Dar es Salaam station over the period of 2017 to 2019. The two numerical methods introduced in this study were both found to be appropriate for Weibull distribution parameter estimation in the study area. However, the SDM gave a higher value of the Weibull parameter estimation than the GM. Furthermore, the five selected commercial wind turbine models that were simulated in terms of performance were based on a capacity factor using the SDM and were both over 25% the recommended capacity factor value. The Polaris P50-500 commercial wind turbine is recommend as a suitable wind turbine to be installed in the study area due to its maximum annual capacity factor value over 3 years.

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A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment

Energies ◽

10.3390/en11071855 ◽

2018 ◽

Vol 11 (7) ◽

pp. 1855 ◽

Cited By ~ 7

Author(s):

Varvara Mytilinou ◽

Estivaliz Lozano-Minguez ◽

Athanasios Kolios

Keyword(s):

Decision Making ◽

Wind Energy ◽

Wind Farm ◽

Cost Effective ◽

Optimization Techniques ◽

Offshore Wind ◽

Moray Firth ◽

The Uk ◽

The Given ◽

Nondominated Sorting

This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK.

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The challenges of high wind energy penetration in the UK power system

2014 International Conference on Power System Technology ◽

10.1109/powercon.2014.6994004 ◽

2014 ◽

Cited By ~ 4

Author(s):

David Infield ◽

Lei Wu

Keyword(s):

Power System ◽

Wind Energy ◽

High Wind ◽

The Uk

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Wind energy

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2006.1955 ◽

2007 ◽

Vol 365 (1853) ◽

pp. 957-970 ◽

Cited By ~ 12

Author(s):

W.E Leithead

Keyword(s):

Wind Energy ◽

Current Drive ◽

Department Of Energy ◽

The Us ◽

Technical Issues ◽

The Uk ◽

Renewable Energy Generation ◽

Expected Increase ◽

Eu Commission ◽

The Eu

From its rebirth in the early 1980s, the rate of development of wind energy has been dramatic. Today, other than hydropower, it is the most important of the renewable sources of power. The UK Government and the EU Commission have adopted targets for renewable energy generation of 10 and 12% of consumption, respectively. Much of this, by necessity, must be met by wind energy. The US Department of Energy has set a goal of 6% of electricity supply from wind energy by 2020. For this potential to be fully realized, several aspects, related to public acceptance, and technical issues, related to the expected increase in penetration on the electricity network and the current drive towards larger wind turbines, need to be resolved. Nevertheless, these challenges will be met and wind energy will, very likely, become increasingly important over the next two decades. An overview of the technology is presented.

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