A Wavelet-Prony Method for Modeling of Fixed-Speed Wind Farm Low-Frequency Power Pulsations

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency pulsations contained within active power flow. A primary concern is excitation of low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of interconnection between the Northern and Southern power system networks. In order to determine whether the prevalence of wind generation has a negative effect (excites modes) or positive impact (damping of modes) on the power system, oscillations must be measured and characterised. Using time – frequency methods, this paper presents work that has been conducted to extract features from low-frequency active power pulsations to determine the composition of oscillatory modes which may impact on dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Determination of battery storage capacity in energy buffer for wind farm

Design of a battery energy storage system (BESS) in a buffer scheme is examined for the purpose of attenuating the effects of unsteady input power from wind farms. The design problem is formulated as maximization of an objective function that measures the economic benefit obtainable from the dispatched power from the wind farm against the cost of the BESS. Solution to the problem results in the determination of the capacity of the BESS to ensure constant dispatched power to the connected grid, while the voltage level across the dc-link of the buffer is kept within preset limits. A computational procedure to determine the BESS capacity and the evaluation of the dc voltage is shown. Illustrative examples using the proposed design method are included.

A new constraint handling method for wind farm layout optimization with lands owned by different owners

For wind farm optimizations with lands belonging to different owners, the traditional penalty method is highly dependent on the type of wind farm land division. The application of the traditional method can be cumbersome if the divisions are complex. To overcome this disadvantage, a new method is proposed in this paper for the first time. Unlike the penalty method which requires the addition of penalizing term when evaluating the fitness function, it is achieved through repairing the infeasible solutions before fitness evaluation. To assess the effectiveness of the proposed method on the optimization of wind farm, the optimizing results of different methods are compared for three different types of wind farm division. Different wind scenarios are also incorporated during optimization which includes (i) constant wind speed and wind direction; (ii) various wind speed and wind direction, and; (iii) the more realisticWeibull distribution. Results show that the performance of the new method varies for different land plots in the tested cases. Nevertheless, it is found that optimum or at least close to optimum results can be obtained with sequential land plot study using the new method for all cases. It is concluded that satisfactory results can be achieved using the proposed method. In addition, it has the advantage of flexibility in managing the wind farm design, which not only frees users to define the penalty parameter but without limitations on the wind farm division.

Different approaches of applying single-objective binary genetic algorithm on the wind farm design

This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.

Minimize frequency fluctuations of isolated power system with wind farm by using superconducting magnetic energy storage

Wind power generation as one of the most popular renewable energy applications is absorbing more and more attention all over the world. However, output power fluctuations of wind farm due to random variations of wind speed can cause network frequency and voltage flicker in power systems. The power quality consequently declines, particularly in an isolated power system such as the power system in a remote community or a small island. This paper proposes an application of superconducting magnetic energy storage (SMES) to minimize output fluctuations of an isolated power system with wind farm. The isolated power system is fed by a diesel generator and a wind generator consisting of a wind turbine and squirrel cage induction machine. The control strategy is detailed and the proposed system is evaluated by simulation in Matlab/Simulink.

Repeated mapping of reefs constructed by Sabellaria spinulosa Leuckart 1849 at an offshore wind farm site

Sabellaria spinulosa reefs are considered to be sensitive and of high conservation status. This article evaluates the feasibility of using remote sensing technology to delineate S. spinulosa reefs. S. spinulosa reef habitats associated with the Thanet Offshore Windfarm site were mapped using high resolution sidescan sonar (410 kHz) and multibeam echo sounder (<1 m2) data in 2005 (baseline), 2007 (pre-construction baseline) and 2012 (post-construction). The S. spinulosa reefs were identified in the acoustic data as areas of distinct irregular texturing. Maps created using acoustic data were validated using quantitative measures of reef quality, namely tube density (as a proxy for the density of live S. spinulosa), percentage cover of S. spinulosa structures (both living and dead) and associated macrofauna derived from seabed images taken across the development site. Statistically significant differences were observed in all physical measures of S. spinulosa as well the number (S) and diversity (H׳) of associated species, derived from seabed images classified according to the presence or absence of reef, validating the use of high resolution sidescan sonar to map these important biogenic habitats. High precision mapping in the early stages allowed for the micro-siting of wind turbines in a way that caused minimal damage to S. spinulosa reefs during construction. These habitats have since recovered and expanded in extent. The surveys undertaken at the Thanet Offshore Windfarm site demonstrate the importance of repeat mapping for this emerging industry, allowing habitat enhancement to be attributed to the development whilst preventing background habitat degradation from being wrongly attributed to the development.

High Level Environmental Screening Study for Offshore Wind Farm Developments – Marine Habitats and Species Project

High level environmental screening study for offshore wind farm developments – marine habitats and species This report provides an awareness of the environmental issues related to marine habitats and species for developers and regulators of offshore wind farms. The information is also relevant to other offshore renewable energy developments. The marine habitats and species considered are those associated with the seabed, seabirds, and sea mammals. The report concludes that the following key ecological issues should be considered in the environmental assessment of offshore wind farms developments: • likely changes in benthic communities within the affected area and resultant indirect impacts on fish, populations and their predators such as seabirds and sea mammals; • potential changes to the hydrography and wave climate over a wide area, and potential changes to coastal processes and the ecology of the region; • likely effects on spawning or nursery areas of commercially important fish and shellfish species; • likely effects on mating and social behaviour in sea mammals, including migration routes; • likely effects on feeding water birds, seal pupping sites and damage of sensitive or important intertidal sites where cables come onshore; • potential displacement of fish, seabird and sea mammals from preferred habitats; • potential effects on species and habitats of marine natural heritage importance; • potential cumulative effects on seabirds, due to displacement of flight paths, and any mortality from bird strike, especially in sensitive rare or scarce species; • possible effects of electromagnetic fields on feeding behaviour and migration, especially in sharks and rays, and • potential marine conservation and biodiversity benefits of offshore wind farm developments as artificial reefs and 'no-take' zones. The report provides an especially detailed assessment of likely sensitivity of seabed species and habitats in the proposed development areas. Although sensitive to some of the factors created by wind farm developments, they mainly have a high recovery potential. The way in which survey data can be linked to Marine Life Information Network (MarLIN) sensitivity assessments to produce maps of sensitivity to factors is demonstrated. Assessing change to marine habitats and species as a result of wind farm developments has to take account of the natural variability of marine habitats, which might be high especially in shallow sediment biotopes. There are several reasons for such changes but physical disturbance of habitats and short-term climatic variability are likely to be especially important. Wind farm structures themselves will attract marine species including those that are attached to the towers and scour protection, fish that associate with offshore structures, and sea birds (especially sea duck) that may find food and shelter there. Nature conservation designations especially relevant to areas where wind farm might be developed are described and the larger areas are mapped. There are few designated sites that extend offshore to where wind farms are likely to be developed. However, cable routes and landfalls may especially impinge on designated sites. The criteria that have been developed to assess the likely marine natural heritage importance of a location or of the habitats and species that occur there can be applied to survey information to assess whether or not there is anything of particular marine natural heritage importance in a development area. A decision tree is presented that can be used to apply ‘duty of care’ principles to any proposed development. The potential ‘gains’ for the local environment are explored. Wind farms will enhance the biodiversity of areas, could act as refugia for fish, and could be developed in a way that encourages enhancement of fish stocks including shellfish.

Many ways to say 'no', different ways to say 'yes': Applying Q-Methodology to understand public acceptance of wind farm proposals

This paper explores the nature of public acceptance of wind farms by investigating the discourses of support and objection to a proposed offshore scheme. It reviews research into opposition to wind farms, noting previous criticisms that this has tended to provide descriptive rather than explanatory insights and as a result, has not effectively informed the policy debate. One explanation is that much of this research has been conceived within an unreflective positivist research frame, which is inadequate in dealing with the subjectivity and value-basis of public acceptance of wind farm development. The paper then takes a case study of an offshore wind farm proposal in Northern Ireland and applies Q-Methodology to identify the dominant discourse of support and objection. It is argued that this provides new insights into the nature of wind farm conflicts, points to a number or recommendations for policy functions of an example of how this methodology can act as a potential bridge between positivist and post-positivist approaches to policy analysis.

Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

Validation of fixed speed induction generator models for inertial response using wind farm measurements

This paper outlines the use of phasor measurement unit (PMU) records to validate models of fixed speed induction generator (FSIG)-based wind farms during frequency transients. Wind turbine manufacturers usually create their own proprietary models which they can supply to power system utilities for stability studies, subject to confidentiality agreements. However, it is desirable to confirm the accuracy of supplied models with measurements from the particular installation, in order to assess their validity under real field conditions. This is prudent due to possible changes in control algorithms and design retrofits, not accurately reflected or omitted in the supplied model. One important aspect of such models, especially for smaller power systems with limited inertia, is their accuracy during system frequency transients. This paper, therefore, assesses the accuracy of FSIG models with regard to frequency stability, and hence validates a subset of the model dynamics. Such models can then be used with confidence to assess wider system stability implications. The measured and simulated response of a wind farm using doubly fed induction generator (DFIG) technology is also assessed.