Online ISSN
1752-1424
Print ISSN
1752-1416
IET Renewable Power Generation
Volume 5, Issue 6, November 2011
Volumes & issues:
Volume 5, Issue 6
November 2011
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- Author(s): N. Gyawali ; Y. Ohsawa ; O. Yamamoto
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 407 –421
- DOI: 10.1049/iet-rpg.2010.0058
- Type: Article
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p.
407
–421
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Energy storage devices are necessary to address the issues associated with stochastic variation of generated power in a wind energy conversion system. This study explores the control and operational aspects of integrating a smart energy storage system (SESS) into a double-fed induction generator-based wind power system. The fuel-cell/electrolyser subsystem of SESS is employed to provide long-term energy balance by utilising H2 as storage medium, whereas the superconducting magnetic energy storage is employed as buffer storage for transient compensation. The control schemes enable the integrated system to operate seamlessly in different modes fulfilling the operational requirements. Here, system configuration is proposed, control scheme is designed and the detailed dynamic modelling is developed for each component of the system. Simulation is carried out to study the control behaviour of wind turbines during the sudden load change and wind speed variations. The results demonstrate the applicability of the overall operational and control architecture for hybrid wind/storage operation. The control scheme of SESS and power management technique employed into the grid-side converter system, in particular, highlight the capability of the proposed system in managing intermittency and making it a dispatchable entity. - Author(s): M. Azzouz ; A.-l. Elshafei ; H. Emara
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 422 –430
- DOI: 10.1049/iet-rpg.2010.0102
- Type: Article
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p.
422
–430
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Fuzzy logic is a convenient approach to construct maximum power-point-tracking algorithms. A new scheme composed of two fuzzy systems is proposed here. The first fuzzy system is based on a modified hill climb search algorithm to conclude the power set-point. The second fuzzy system is an adaptive proportional integral-like controller that uses a variable structure tuning algorithm to track the power set-point. Simulations show that the proposed scheme can improve the system efficiency. - Author(s): S.R. Samantaray ; A. Samui ; B. Chitti Babu
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 431 –438
- DOI: 10.1049/iet-rpg.2010.0166
- Type: Article
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431
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This study presents a new technique for islanding detection in distributed generation (DG) using time-frequency transform such as S-transform. S-transform is an invertible time-frequency spectral localisation technique that provides the time-frequency contours of the voltage and current signals retrieved at the target DG location. The energy index (ratio of the spectral energy content of the voltage to current signals) is computed to track the islanding situation from non-islanding conditions such as sudden load change, tripping of other DG, etc. Further, to aid the islanding detection scheme, a cumulative sum detector is also computed based on the spectral energy content of the negative sequence components of the current and voltage signals. The results, based on extensive study, indicate that the proposed technique can reliably detect islanding in DGs connected to power distribution network. - Author(s): J. Mohammadi ; A. Rahimi-Kian ; M.-S. Ghazizadeh
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 439 –447
- DOI: 10.1049/iet-rpg.2011.0066
- Type: Article
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439
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Intermittence is one the main obstacles in wind power penetration, due to imbalance charges set by market prices. To cope with this drawback, demand-side participation has been proposed as a good complement that can handle positive and negative imbalances. This study suggests an offering optimisation model for aggregated wind power and flexible loads in day-ahead electricity markets. Flexible load as a storage unit can either cover wind power imbalances or recover itself according to electricity price and load curve during various hours. The proposed offering model is compared with the disaggregated operations of wind and demand response with satisfactory results. - Author(s): Y. Yuan ; J. Zhou ; P. Ju ; J. Feuchtwang
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 448 –454
- DOI: 10.1049/iet-rpg.2010.0218
- Type: Article
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448
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Load flow is highly uncertain with the large-scale integration of wind power. It is unrealistic to adopt traditional deterministic load flow calculation for system planning and operation. A method is proposed in this study combining cumulants and Gram–Charlier expansion to calculate probabilistic load flow (PLF) of power system containing large-scale wind power. It has significantly reduced the computational time compared to Monte Carlo methods while maintaining a high degree of accuracy. The method was found quite suitable for the PLF calculation of power system with large-scale wind power injected. - Author(s): S. Zhao and N.-K.C. Nair
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 455 –464
- DOI: 10.1049/iet-rpg.2010.0156
- Type: Article
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p.
455
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To understand the impact of increasing penetration of wind energy on power system, dynamic models of wind turbine generator are being incorporated into power system simulation software by transmission system operators. This enables them to carry out security assessment during planning and operations. Unlike synchronous machine-based generators, majority of wind generator models have not been universally standardised and validated. The performance of different wind turbine models (i.e. generic and manufacturer-specific models) under grid disturbance and their cumulative impact as seen by the transmission will need to be completely understood to enable realistic system security assessment. Comparison of these models with actual field measurements is also an attractive option for opportunistic testing. This study will examine model development and its use from the transmission system operator perspective. The generic model will then be compared with detailed individual model for actual wind farm connection studies. The measurement data based on naturally occurring power system disturbance will be used for model validation. - Author(s): R. Waters ; M. Rahm ; M. Eriksson ; O. Svensson ; E. Strömstedt ; C. Boström ; J. Sundberg ; M. Leijon
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 465 –469
- DOI: 10.1049/iet-rpg.2010.0124
- Type: Article
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(5)
The ability of a wave energy converter to capture the energy of ocean waves has been studied in offshore experiments. This study covers 50 days during which the converter was subjected to ocean waves over a wide range of frequencies and amplitudes as well as three different electrical loads. The results present the wave energy converter's energy absorption as a function of significant wave height, energy period and electrical load. It is shown that the power generated overall continues to increase with wave amplitude, whereas the relative absorption decreases towards the highest periods and amplitudes. The absorption reached a maximum of approximately 24% with the used combination of buoy, generator and electrical load. Absorption to cover for iron and mechanical losses has not been included. A brief study of the nature of the electromagnetic damping force has also been included in the study. The wave energy converter is of the technology that is being researched at Uppsala University and experimented on off the Swedish west coast at the Lysekil wave energy research site. - Author(s): A. Anvari Moghaddam and A.R. Seifi
- Source: IET Renewable Power Generation, Volume 5, Issue 6, p. 470 –480
- DOI: 10.1049/iet-rpg.2010.0104
- Type: Article
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p.
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Accurate forecasting of renewable energies such as wind and solar has become one of the most important issues in developing smart grids. Therefore introducing suitable means of weather forecasting with acceptable precision becomes a necessary task in today's changing power world. In this work, an intelligent way for hourly estimation of both wind speed and solar radiation in a typical smart grid has been proposed and its superior performance is compared to those of conventional methods and neural networks (NNs). The methodology is based on linear predictive coding and digital image processing principles using two dimensional (2-D) finite impulse response filters. Meteorological data have been collected during the period 1 January 2009 to 31 December 2009 from Casella automatic weather station (AWS) at Plymouth, UK. Numerical results indicate that a considerable improvement in forecasting process is achieved with 2-D predictive filtering compared to the conventional approaches.
Power management of double-fed induction generator-based wind power system with integrated smart energy storage having superconducting magnetic energy storage/fuel-cell/electrolyser
Evaluation of fuzzy-based maximum power-tracking in wind energy conversion systems
Time-frequency transform-based islanding detection in distributed generation
Aggregated wind power and flexible load offering strategy
Probabilistic load flow computation of a power system containing wind farms using the method of combined cumulants and Gram–Charlier expansion
Assessment of wind farm models from a transmission system operator perspective using field measurements
Ocean wave energy absorption in response to wave period and amplitude – offshore experiments on a wave energy converter
Study of forecasting renewable energies in smart grids using linear predictive filters and neural networks
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