Simulation and study of power quality issues in a fixed speed wind farm substation.
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ABSTRACT:
SUBMITTER: Magesh T
PROVIDER: S-EPMC4407622 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:Global power production increasingly relies on wind farms to supply low-carbon energy. The recent Intergovernmental Panel on Climate Change (IPCC) Special Report predicted that renewable energy production must leap from [Formula: see text] of the global energy mix in 2018 to [Formula: see text] by 2050 to keep global temperatures from rising 1.5°C above preindustrial levels. This increase requires reliable, low-cost energy production. However, wind turbines are often placed in close proximity within wind farms due to land and transmission line constraints, which results in wind farm efficiency degradation of up to [Formula: see text] for wind directions aligned with columns of turbines. To increase wind farm power production, we developed a wake steering control scheme. This approach maximizes the power of a wind farm through yaw misalignment that deflects wakes away from downstream turbines. Optimization was performed with site-specific analytic gradient ascent relying on historical operational data. The protocol was tested in an operational wind farm in Alberta, Canada, resulting in statistically significant ([Formula: see text]) power increases of 7-[Formula: see text] for wind speeds near the site average and wind directions which occur during less than [Formula: see text] of nocturnal operation and 28-[Formula: see text] for low wind speeds in the same wind directions. Wake steering also decreased the variability in the power production of the wind farm by up to [Formula: see text] Although the resulting gains in annual energy production were insignificant at this farm, these statistically significant wake steering results demonstrate the potential to increase the efficiency and predictability of power production through the reduction of wake losses.
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Project description:Based on wind speed, direction and power data, an assessment method of wind energy potential using finite mixture statistical distributions is proposed. Considering the correlation existing and the effect between wind speed and direction, the angular-linear modeling approach is adopted to construct the joint probability density function of wind speed and direction. For modeling the distribution of wind power density and estimating model parameters of null or low wind speed and multimodal wind speed data, based on expectation-maximization algorithm, a two-component three-parameter Weibull mixture distribution is chosen as wind speed model, and a von Mises mixture distribution with nine components and six components are selected as the models of wind direction and the correlation circular variable between wind speed and direction, respectively. A comprehensive technique of model selection, which includes Akaike information criterion, Bayesian information criterion, the coefficient of determination R2 and root mean squared error, is used to select the optimal model in all candidate models. The proposed method is applied to averaged 10-min field monitoring wind data and compared with the other estimation methods and judged by the values of R2 and root mean squared error, histogram plot and wind rose diagram. The results show that the proposed method is effective and the area under study is not suitable for wide wind turbine applications, and the estimated wind energy potential would be inaccuracy without considering the influence of wind direction.
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Project description:The purpose of this paper is to provide a high level, holistic overview of the work being undertaken in the wind energy industry. It summarises the main techniques used to simulate both aerodynamic and structural issues associated with wind turbines and farms. The motivation behind this paper is to provide new researchers with an outlook of the modelling and simulation landscape, whilst highlighting the trends and direction research is taking. Each section summarises an individual area of simulation and modelling, covering the important historical research findings and a comprehensive analysis of recent work. This segregated approach emphasises the key components of wind energy. Topics range in geometric scales and detail, ranging from atmospheric boundary layer modelling, to fatigue and fracture in the turbine blades. More recent studies have begun to combine a range of scales and physics to better approximate real systems and provide higher fidelity and accurate analyses to manufacturers and companies. This paper shows a clear trend towards coupling both scales and physics into singular models utilising high performance computing system.
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Project description:ObjectivesTo assess the quality of sleep of employees in the German offshore wind industry and to explore factors associated with poor sleep quality.DesignWeb-based cross-sectional survey.SettingOffshore companies operating in wind farms within the German exclusive economic zone.ParticipantsWorkers with regular offshore commitments and at least 28 days spent offshore in the past year (n=268).Outcome measuresSleep quality in the past 4 weeks, troubles falling asleep or sleeping through in the past 4 weeks, differences in sleep quality between offshore deployments and onshore leaves.ResultsHaving problems with sleep onset was reported by 9.5% of the respondents. 16.5% reported troubles with maintaining sleep three or more times per week. The overall quality of sleep was rated as very bad by only 1.7% of the participants. 47.9% of the workers reported their quality of sleep to be worse during offshore commitments than when being onshore. Higher levels of exposition to noise, vibrations and poor air quality were associated with sleeping troubles and poorer sleep quality. Sharing the sleep cabin with colleagues was associated with troubles sleeping through. No association was found for working in rotating shifts and for regularity of the offshore commitments.ConclusionsWorkers in our study showed frequent sleep problems and poorer sleep quality offshore than onshore. Our results indicate that higher degrees of exposure to noise, vibrations and artificial ventilation are associated with poor sleep quality rather than organisational factors such as shift-work and type of working schedule. In view of the high demands of the offshore workplace and the workers' particular recovery needs, addressing sleep disorders should be part of any health and safety management strategy for this workplace.
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Project description:Near-surface (10 m) wind speed (NWS) plays a crucial role in many areas, including the hydrological cycle, wind energy production, and the dispersion of air pollution. Based on wind speed data from Tazhong and the northern margins of the Taklimakan Desert in Xiaotang in spring, summer, autumn, and winter of 2014 and 2015, statistical methods were applied to determine the characteristics of the diurnal changes in wind speed near the ground and the differences in the wind speed profiles between the two sites. The average wind speed on a sunny day increased slowly with height during the day and rapidly at night. At heights below 4 m the wind speed during the day was higher than at night, whereas at 10 m the wind speed was lower during the day than at night. The semi-empirical theory and Monin-Obukhov (M-O) similarity theory were used to fit the NWS profile in the hinterland of the Tazhong Desert. A logarithmic law was applied to the neutral stratification wind speed profile, and an exponential fitting correlation was used for non-neutral stratification. The more unstable the stratification, the smaller the n. Using M-O similarity theory, the "linear to tens of" law was applied to the near-neutral stratification. According to the measured data, the distribution of φ M with stability was obtained. The γm was obtained when the near-surface stratum was stable in the hinterland of Tazhong Desert and the βm was obtained when it was unstable. In summer, γ m and βm were 5.84 and 15.1, respectively, while in winter, γm and βm were 1.9 and 27.1, respectively.
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Project description:To promote the coordinated development between renewable energy and the distribution network, a capacity allocation model of battery energy storage systems (BESS) is proposed to achieve the coordinated optimization for active and reactive power flow, which can reduce the voltage deviation and improve the absorptive capacity for renewable energy. In addition, BESS with four-quadrant operation characteristics, on-load tap changer, and capacitor banks are treated as flexible devices to improve the adaptability for renewable energy fluctuations. In view of the uncertainties of renewable energy caused by the inaccuracy of historical sample data, a set of extreme scenarios with the characteristics of temporal and spatial correlation are considered to obtain a robust BESS configuration decision. The big-M approach and the second-order conic relaxation technique are utilized to convert the BESS capacity allocation model into a mixed-integer linear programming problem. Finally, the IEEE 33-node distribution system is taken as an example to verify the effectiveness of the proposed method.
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Project description:This paper proposes an optimal reactive power control method to maximize wind farm revenue and minimize the total electrical losses of a doubly-fed induction generator (DFIG)-based wind farm. Specifically, the split Bregman method is used to solve the optimal control problem in a distributed manner. That is, the optimization problem is decomposed into sub-problems by the optimal distributed control strategy, and each sub-problem is solved independently in each local controller through the parallel method, which reduces the calculating burden and improves the information privacy. Thus, when a fault occurs, the proposed distributed control strategy can overcome the system fault and improve the reliability and security of the system. Furthermore, an economic financial model of annual revenue is contributed to examine the income impact with or without certified emission reduction (CER) by the clean development mechanism (CDM). Compared with the dual ascent (DA) method, sequential quadratic programming (SQP) method and the proportional dispatch method (PDM), the annual revenue (AR) of the wind farm using the proposed split Bregman method is the highest. Simulation results demonstrate that this method has promising performance in both optimization quality and computational efficiency.
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Project description:In hydroelectric dominated systems, the value and benefits of energy are higher during extended dry periods and lower during extended or extreme wet periods. By accounting for regional and temporal differences in the relationship between wind speed and reservoir inflow behavior during wind farm site selection, the benefits of energy diversification can be maximized. The goal of this work was to help maximize the value of wind power by quantifying the long-term (30-year) relationships between wind speed and streamflow behavior, using British Columbia (BC) and the Pacific Northwest (PNW) as a case study. Clean energy and self-sufficiency policies in British BC make the benefits of increased generation during low streamflow periods particularly large. Wind density (WD) estimates from a height of 10m (North American Regional Reanalysis, NARR) were correlated with cumulative usable inflows (CUI) for BC (collected from BC Hydro) for 1979-2010. The strongest WD-CUI correlations were found along the US coast (r ~0.55), whereas generally weaker correlations were found in northern regions, with negative correlations (r ~ -0.25) along BC's North Coast. Furthermore, during the lowest inflow years, WD anomalies increased by up to 40% above average values for the North Coast. Seasonally, high flows during the spring freshet were coincident with widespread negative WD anomalies, with a similar but opposite pattern for low inflow winter months. These poorly or negatively correlated sites could have a moderating influence on climate related variability in provincial electricity supply, by producing greater than average generation in low inflow years and reduced generation in wet years. Wind speed and WD trends were also analyzed for all NARR grid locations, which showed statistically significant positive trends for most of the PNW and the largest increases along the Pacific Coast.
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Project description:BackgroundHow accurately do people perceive extreme wind speeds and how does that perception affect the perceived risk? Prior research on human-wind interaction has focused on comfort levels in urban settings or knock-down thresholds. No systematic experimental research has attempted to assess people's ability to estimate extreme wind speeds and perceptions of their associated risks.MethodWe exposed 76 people to 10, 20, 30, 40, 50, and 60 mph (4.5, 8.9, 13.4, 17.9, 22.3, and 26.8 m/s) winds in randomized orders and asked them to estimate wind speed and the corresponding risk they felt.ResultsMultilevel modeling showed that people were accurate at lower wind speeds but overestimated wind speeds at higher levels. Wind speed perceptions mediated the direct relationship between actual wind speeds and perceptions of risk (i.e., the greater the perceived wind speed, the greater the perceived risk). The number of tropical cyclones people had experienced moderated the strength of the actual-perceived wind speed relationship; consequently, mediation was stronger for people who had experienced fewer storms.ConclusionThese findings provide a clearer understanding of wind and risk perception, which can aid development of public policy solutions toward communicating the severity and risks associated with natural disasters.
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