Employing Wind Farm Performance Data for Model Validation and Turbine Layout/Geometry Optimization

A multiscale numerical framework coupled with control strategies for simulating a wind farm in complex terrain

The renewable energy is regarded as one of the basic necessities in which many countries have relied to move the wheel of development forward, The rate of energy consumption was considered as an indicator of nations and peoples progress as electric energy represents the infrastructure of various contemporary activities that many countries adopt in their economic growth. The programs of energy development is not taken into account unless there are developing plans not concerned with change, progress and not to deplete fossil fuel resources, which has been depleting in recent times because of the increase in demand for electricity and for the high in oil prices, research concerned the possibility of finding a new resource of electric energy, The solar and wind energy in an important step to solve the problem of electric power crisis in Mosul city and the beginning of energy self-sufficiency. The research aims to identify the concept of developing the renewable energy industry and its types, in addition to know the impact of the natural geographical features in Mosul city to clarify its role in developing the renewable energy industry to know the appropriate sites to establish sites for solar cells and wind farms and their establishment in the study area, for the problem of power outages was regarded as one of the basic problems facing the Iraqi state, including Mosul city , this asked us to study this problem through renewable energy to reach methods to solve it. The study showed that there are three levels of spatial suitability to choose solar cell sites which are inappropriate areas and occupies 2.8 km2 by 4. 1% of the area of Mosul city. It included the areas that are in the shadows of the hills facing the solar radiation, whose slopes are towards the north, and suitable areas of medium degree which occupies 115.9 km2, 2.58% which includes most of the city’s area that's increased in the east and west of the city for relatively high which occupies 80.3km2 by3.40%. It includes most of the city’s area and increases in the east and west of the city, being high areas and their slope towards the south that receive large amounts of solar radiation.

Hourly modeled wind turbine power output time series – modeled from outputs from the mesoscale numerical weather prediction system WRF – are used to examine the spatial smoothing of various wind farm portfolios located on a complex isolated island group with a surface area of 1400 km2. Power spectral densities (PSD), hourly step change functions, and duration curves are generated, and the 5th and 95th percentiles of the step change functions are calculated. The spatial smoothing is identified from smaller high frequency PSD values, less hourly fluctuations, and more flat duration curves per installed wind power capacity, compared to single wind turbine outputs. A discussion on the limitation of the spatial smoothing for the region is included, where a smoothing effect is clear for periods up to 1–2 days, although most evident at the higher frequencies. By maximizing the smoothing effect, optimal wind farm portfolios are presented with the intention to minimize the overall wind power fluctuations. The focus is mainly on the smoothing effect in highest resolvable frequencies. Optimizing wind farm capacities at fourteen pre-defined good wind farm site locations has a minimal improvement on the hourly fluctuations. However, choosing good combinations of the individual wind farm site locations decrease the 1–3 hourly fluctuations considerably; the optimized wind farm portfolios consist of distant wind farms, while poor portfolios consist of clustered wind farms. The 5th and 95th percentiles are 15 % less for an optimized portfolio with four wind farms compared to a poor combination of four wind farms.

With large wind energy integration into power systems, wind farms begin to influence power systems in a much more significant manner. As wind energy systems utilize different generator technologies from the one utilized in the conventional power plants, the steady-state, transient and small-signal dynamics, as well as, power system stability will thus be significantly affected. The impact of wind energy systems on the power system dynamics and stability is thus of practical importance. As there is a significant increase in installation of wind turbines equipped with doubly-fed induction generator (DFIG) in recent years, a dynamic model of the DFIG wind turbine is firstly developed in this thesis. The model is validated against field measurement data, and the validation gives confidence about the accuracy and applicability of the developed model. DFIG wind farms consist of tens to hundreds of identical DFIG wind turbines increasing the complexity of the wind farm model and simulation time. A novel aggregation technique is developed in this thesis that incorporates a multiplication factor, namely mechanical torque compensation factor (MTCF), to the mechanical torque of the full aggregated wind farm model. The MTCF is initially constructed to approximate a Gaussian function by using fuzzy logic method. By optimizing the MTCF on a trial and error basis, less than 10 percent discrepancy is then achieved between the proposed aggregated model and the complete model. The proposed aggregation technique is then applied to a 120 MVA offshore wind farm comprising of 72 DFIG wind turbines and shows higher accuracy in approximating the wind farm dynamics as it appears at the point of common coupling (PCC) as compared to the full aggregated model. The proposed aggregated model computes faster than the complete wind farm model by 90.3 percent during normal operations and 87 percent during grid disturbances. To overcome the adverse effects due to the fluctuating nature of wind, two wind power smoothing methods are proposed using a fuzzy logic pitch angle controller for a smooth performance with a minimum drop in output power. One method performs partial smoothing with only 4.74 percent drop in the output power while the other method offers complete smoothing with a 8.28 percent drop in output power. The impact of wind energy integration on power system transient stability (PSTS) is studied quantitatively with the transient energy margin (TEM), which is calculated through the evaluation of the transient energy function (TEF). This study is carried out in two ways in the thesis. One is to analyse the impact of transient fault on the DFIG wind turbine as compared to SGs for different factors, like the fault clearing time, the grid coupling, the inertia constant and the voltage sag. The study reveals that transient stability of the DFIG wind turbine is hardly affected by the grid coupling, the inertia constant and the generator terminal voltage sag variations indicating its consistent transient performance within a wide range of these factors. The fault clearing time should be almost 11 percent faster for the system with the DFIG than the synchronous generator (SG). The other is to investigate the impact of the DFIG wind farm on the PSTS with the variation of different factors, which are the voltage sag, the fault clearing time, the load and the wind power penetration level. The study reveals that power systems integrated with DFIG wind farms are sensitive to transient events with high voltage sag, high fault clearing time, low load operation and high wind power penetration level. Machines at different locations individually possess distinct fault response and suffer from a large-scale power imbalance. As a result, reliable operation of DFIG wind farm integrated power systems demands upgraded equipment, such as advanced switchgear, fast breakers/isolators, efficient power reserve systems and advanced reactive power compensating device, etc.

The contribution of wind power in conventional generation is increasing rapidly now-a-days. Hence a better understanding of wind power plants is required. But the wind power plants generally containing induction generators exhibit a rather different behavior than the conventional power plants which use synchronous generators. The purpose of this paper is to analyze and study transient stability of a wind farm based on conventional fixed speed Induction generator when it has been integrated with a weak grid. A comparative analysis of the transient stability improvement of a FSIG wind plant has been done, when it is supported with FACTS like S.V.C and STATCOM of equal ratings. Single case of transient condition i.e. a three phase fault has been studied by simulation. With the increase in demand of power and decrease of fossil fuels, mankind has been forced to search alternative sources for the generation of electricity. Wind power in spite of being stochastic in nature has proved itself as a viable solution to this problem. As the wind turbine technology is developing at a good pace, more and more wind power plants are being integrated with the conventional form of generation. With the increase in the ratio of wind generation to conventional generation, several problems related with integration of wind farms have emerged. These problems are due to distinct properties of the generators used with the conventional form (Thermal & Hydro) of generation and wind based generation (1)-(4). In thermal and hydro power based generation synchronous generators are used while in wind based generation mostly induction generators are used. Induction and synchronous generators do not exhibit similar behavior during power system stresses (transients). Moreover, increase in wind power based generation requires a reliable transmission system for power evacuation to the load centers. As the wind farms are mainly concentrated in far flung and rural areas their interconnection with the grid becomes a problem. This problem is mainly due to the existence weak transmission grids in the rural areas (1)-(4). Earlier when the share of wind power generation as compared with the conventional generation was low, during transient conditions; whenever the power system reached on the verge of instability the wind farm was disconnected from the grid and was reconnected when transients passed away. But as the share of wind power in the conventional generation increased, the practice of disconnecting the wind farms from the rest of the grid led to the drop in frequency of the power system. So now-a- days even if a fault occurs in the power system somewhere near the wind farms, they still remain connected with the grid for a critical time period. This phenomenon is called fault ride through (FRT) in wind farms (5). This paper has studied a transient condition (fault) in a grid connected fixed speed induction generator based wind farm and its fault ride through performance. A comparison of the performance of fact devices like static var compensators (svc) and static synchronous compensators (statcom) in improving the transient stability of wind farms during fault is also done.

Multi-objective optimization of clustered wind farms based on potential game approach

The demand on energy supply increases continuously as economies develop and world population grows. Most of the energy in the world comes from the fossil fuels and the increase in energy demand accelerates the rate of depleting the fossil fuel resources. As fossil fuel is finite and also due to the environmental considerations, renewable energy (RE) resources have been actively developed as the alternative sources for electricity generation. Renewable sources used for large-scale electricity production can include wind, photovoltaic (PV), waves and so on. Among all the RE resources, wind power generation is witnessing rapid developments in recent years. Unfortunately, wind tends to be unsteady. The fluctuating and uncertain output powers from wind farms can be problematic, especially if there is a high penetration level of the renewable source in a grid system. The fluctuations may lead to excessive voltage variations and unacceptable degree of frequency deviations. Moreover, the unsteady and uncertain input wind power can cause firm power dispatch commitment from wind farms a difficult task. Expensive generation reserves have to be provided for grid system to ensure adequate level of system security and reliability is guaranteed. In fact, power generation from wind farms has often been excluded in the dispatch planning of the grids. Unless other viable techniques can be found, the above issues can constitute major impediment to the successful large-scale integration of wind power generation into grid systems. In this connection, the use of energy storage system (ESS) is one possible solution to mitigate the negative impacts of the unsteady wind power on electricity supply systems and to improve on the dispatchability of the wind power. In this investigation, in order to smoothen the fluctuations in the wind and to realize the dispatch planning of the wind power in a way similar to that of conventional generators, it is proposed that a three-level ESS is incorporated in a large-scale wind power generation scheme. In essence, at cluster-level of wind turbine generators (WTG), the solution involves having the high- and mid-frequency components of the aggregated wind power routed to supercapacitors (SC) and battery banks respectively of a battery-supercapacitor hybrid energy storage system (BSHESS) by a high-pass filter (HPF) and a band-pass filter (BPF). It then results in the smoothening of the wind power harnessed by the cluster. In this thesis, the BSHESS control scheme to reduce the wind power perturbations has been shown. A statistical method is also developed to determine the capacities of the minimum-cost BSHESS to meet the power smoothing objective at pre-specified probability level. Application of the proposed design approach is demonstrated using data obtained from an existing wind farm. As for dispatch planning, attention is to use a low-pass filter (LPF) to extract the low-frequency intrinsic mode and residue functions of wind power. The relatively slow-changing characteristics of the low-frequency wind power components, which contain most of the energy in the wind power, allow accurate forecasts of the power components to be obtained using artificial neural network (ANN). Dispatch planning of the wind power is then realized through buffering the low-frequency power fluctuations by a proposed power flows control strategy applied to a pumped hydroelectric storage (PHS) system. Focusing on low-frequency wind power for dispatch planning is a distinct advantage over the dispatch planning methods proposed by other researchers. Furthermore, a statistical method to determine the power and energy capacities of the PHS is included. The efficacy of the developed approach to dispatch planning is again illustrated based on data obtained from an existing wind farm. In all the above works, suitable cut-off frequencies for the HPF, BPF and LPF are derived based on the developed concept of minimum overlap energy and the outcome of empirical mode decomposition (EMD) analysis. EMD method is used to gain insights into the frequency-time characteristics of wind power. In this manner, the wind power can then be grouped into high-, mid- and low-frequency bands.

Large-eddy simulation of a utility-scale wind farm in complex terrain

Wind energy is a rapidly expanding source of renewable energy, but is highly intermittent. The performance of a wind farm, composed of a collection of wind turbines, depends not only on the placement of wind turbines in a farm, but also control actions taken by individual turbines. The wind turbine placement (layout) design problem involves adjusting turbine locations within a given area to improve a performance objective (such as maximizing annualized energy production). This layout problem has been addressed previously considering the effect of constraints such land configuration, installed capacity, and wake model choice on the performance of wind farms. All the studies, however, ignore the effects of the control system, which can have significant impact on performance. A well designed wind farm — without an optimal controller — will not achieve the full system level optimal performance, and vice-versa. In this article, we propose a novel layout co-design approach that includes optimal control considerations to exploit this synergy between farm layout and control. Layout case studies involving 8 and 12 turbines are presented. An annual energy production improvement of up to 17% is observed when accounting for coupling between control and layout design, when compared to layout-only optimization.

Wind Turbine Operation and Maintenance Video Supportive System Based on the Mobile Internet of Things

Wind power forecast plays an important role in wind farm operation and grid scheduling decisions. Prediction of power output from wind vector based on wind farm equivalent power curve is the final step of forecast, which has a lot of interaction with the grid dispatching, and it has a particularly prominent influence on the wind farm power output so as to cut down prediction accuracy. Focusing on the step of "wind-power transformation", a correction method of day-ahead wind power forecast including multiple factors such as wind-abandon coefficient is proposed in this paper. Firstly, it is proved that the wind power prediction error is affected by a variety of factors, such as the amplitude of predicted power, the volatility of forecast as well as the stability of recent wind power output. And a model is built to quantify them respectively. Then the wind-abandon coefficient is introduced to modeling the effect of wind power curtailment activities of grid dispatching to forecast accuracy. Finally, the evaluation model of wind power forecasting error is built by using the multiple linear regression method and corrects the predictive value. Case study basing on the actual operation data of a wind farm in northern China has shown that the proposed method is effective to improve the accuracy level of wind power forecast.

This study investigates the effects of the construction and operation of a large Danish offshore wind farm on harbor and gray seal haul-out behavior within a nearby (4 km) seal sanctuary. Time-lapse photography, visual monitoring, and aerial surveys were used to monitor the number of seals on land in daylight hours. Seals were monitored during two preconstruction periods (19 June–31 August 2001 and April–August 2002), a construction period of the wind farm (August 2002–December 2003), and a period of operation of the wind farm (December 2003–December 2004). Monthly aerial surveys were conducted to estimate the proportion of seals in the sanctuary relative to neighboring haul-out sites. From preconstruction to construction and through the first year of operation the number of harbor seals in the sanctuary increased at the same rate as the number of seals at the neighboring haul-out sites. No long-term effects on haul-out behavior were found due to construction and operation of the wind farm. However, a significant short-term decrease was seen in the number of seals present on land during sheet pile driving in or near the wind farm. Acoustic deterrents were utilized simultaneously to avoid hearing damage.

The construction of offshore wind farms in Northern Europe commenced in the early nineties. In the beginning, only minor test offshore wind farms were built, but from 2002 and onwards, large-scale offshore wind farms have been erected. Construction and operation experiences from these wind farms are now being collected, and this paper discusses construction and operation experiences obtained from selected offshore wind farms. Differences and similarities between the wind industry and the oil and gas industry are discussed with a view to raising the awareness of this new and growing industry among market players in the oil and gas industry. Current status and plans in Europe [1] In the European Union (EU) the development of wind power is very impressive. Over the past five years, 30% of all newly installed electricity generating capacity has been wind power. The installed capacity is now 40.5 GW, and the generated power is enough to supply 21 million households. However, wind power still only covers 2.8% of the total European electricity demand. Only 680 MW of the above-mentioned 40.5 GW capacity are installed off shore. Recent projections of the future development suggest that by 2030 the installed capacity may reach 300 GW of which 150 GW are expected to be installed off shore. Whether the targets for offshore wind power will be met depends crucially on technology development, grid infrastructure and the existence of political incentives to encourage investments. A renewables target of at least 20% of EU energy by 2020 will be a significant driving force behind this development. It will only be possible to meet this target with a strong contribution from wind power. Another driving force behind the wind power development is the increase in fossil fuel prices. Current status and plans in Denmark [2] Denmark has been and is still a frontrunner in the development of on- and offshore wind energy. Only in Denmark, Spain, Germany and Ireland does wind power cover more than 5% of the electricity demand. In Denmark, the actual figure is close to 20%. The installed capacity is 3100 MW of which 420 MW are located off shore (two large-scale wind farms contribute 325 MW). Recent wind farm developments have been located off shore, and future plans aim to expand offshore wind power event further. Currently, investment decisions to erect two offshore wind farms of 200 MW each are in the pipeline. Challenges going off shore The main reasons for going off shore are access to large energy resources and potentially less complicated planning processes. Although the wind resources are vast, the investment in foundations and electrical infrastructure (cables and substations) are dramatically higher than for onshore wind farms, and operation costs increase as well. At first glance, the planning process, including the environmental statements, seems to be easier off shore, but experience shows that there are many stakeholders in the offshore areas, who make the offshore process as difficult as the onshore process.

This paper proposes a coordinated operational strategy of energy storage system (ESS) and wind farm to reduce wind power spillage and alleviate wind power fluctuation. Firstly, power curve of a wind farm, in the form of an equivalent wind turbine, is determined by least square fitting. Based on the power output characteristic of the wind farm and historic operating data, the statistical properties of wind power spillage and fluctuation can be obtained. Secondly, the target for wind farm and ESS power output is calculated. Power generation/absorption capabilities of ESS and available power output reducing range of the wind farm are quantified as well, considering the operational constraints of ESS and dispatched wind power output. Finally, a coordinated operational strategy is developed not only to adjust the combined ESS and wind farm to meet the dispatch requirement, but also to ensure ESS and the wind farm to satisfy operational constraints. Case studies are conducted on a practical wind farm with battery energy storage system installed, which demonstrate that the coordination of ESS can greatly boost the revenue and improve power quality of wind farm.

Summary1. There has been a rapid increase in the development of renewable energy because of the need to combat climate change. One of the most widely used technologies has been onshore wind farms. These have the potential to affect birds through disturbance or collision, but the extent to which such developments cause general population declines, and therefore are of wider conservation concern, remains largely untested.2. Monitoring data from wind farms located on unenclosed upland habitats in the UK were collated to test whether breeding densities of upland birds were reduced as a result of wind farm construction or during wind farm operation.3. Data were available for ten species although none were raptors. Red grouse Lagopus lagopus scoticus, snipe Gallinago gallinago and curlew Numenius arquata densities all declined on wind farms during construction. Red grouse densities recovered after construction, but snipe and curlew densities did not. Post‐construction curlew densities on wind farms were also significantly lower than reference sites. Conversely, densities of skylark Alauda arvensis and stonechat Saxicola torquata increased on wind farms during construction.4. There was little evidence for consistent post‐construction population declines in any species, suggesting for the first time that wind farm construction can have greater impacts upon birds than wind farm operation.5. The impacts of wind farms were largely unaffected by technical specifications (turbine height, number or total generating power) and therefore are widely applicable.6. Synthesis and applications. This study confirms that regulatory authorities and developers should particularly consider the likely impacts of wind farms on large waders. Greater weight should be given to the effects of construction on wildlife in impact assessments than at present. Mitigation measures during construction, including restricting construction activity to non‐breeding periods, should be considered and tested as a means to reduce these negative effects.