946 resultados para Farm engines.


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This paper analyzes data captured by a phasor measurement unit at a wind farm, employing two-speed induction generators, and investigates aspects of the control system's interaction with the power system. Composite superimposed transient events are proposed as a method to improve the quality of the analysis and reduce errors caused by unknowns, such as wind speed variation. A Mathworks SimPowerSystems model validates the inertia contribution of the wind farm, which is an important parameter in power systems with high wind penetration. Transients caused by turbine speed transitions are identified and explained. The analysis also highlights areas where wind farm control should be improved if useful inertia contribution is to be provided.

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Social scientists and other analysts have written about medicalization since at least the 1970s. Most of these studies depict the medical profession, interprofessional or organizational contests, or social movements and interest groups as the prime movers toward medicalization. This article contends that changes in medicine in the past two decades are altering the medicalization process. Using several case examples, I argue that three major changes in medical knowledge and organization have engendered an important shift in the engines that drive medicalization: biotechnology (especially the pharmaceutical industry and genetics), consumers, and managed care. Doctors are still gatekeepers for medical treatment, but their role has become more subordinate in the expansion or contraction of medicalization. Medicalization is now more driven by commercial and market interests than by professional claims-makers. The definitional center of medicalization remains constant, but the availability of new pharmaceutical and potential genetic treatments are increasingly drivers for new medical categories. This requires a shift in the sociological focus examining medicalization for the twenty-first century.

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In any internal combustion engine, the amount of heat rejected from the engine, and associated systems, is a result of the engine inefficiency. Successfully recovering a small proportion of this energy would therefore substantially improve the fuel economy.

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The objective of this study was to examine the estrogen and androgen hormone removal efficiency of reactive (Connelly zero-valent iron (ZVI), Gotthart Maier ZVI) and sorptive (AquaSorb 101 granular activated carbon (GAC) and OrganoLoc PM-100 organo clay (OC)) materials from HPLC grade water and constructed wetland system (CWS) treated dairy farm wastewater. Batch test studies were performed and hormone concentration analysis carried out using highly sensitive reporter gene assays (RGAs). The results showed that hormonal interaction with these materials is selective for individual classes of hormones. Connelly ZVI and AquaSorb 101 GAC were more efficient in removing testosterone (Te) than 17?-estradiol (E2) and showed faster removal rates of estrogen and androgen than the other materials. Gotthart Maier ZVI was more efficient in removing E2 than Te. OrganoLoc PM-100 OC achieved the lowest final concentration of E2 equivalent (EEQ) and provided maximum removal of both estrogens and androgens.

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The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

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The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency periodic pulsations contained within the active power flow from different wind farms. A primary concern is excitation of existing low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of the interconnected Northern and Southern power system networks. Recently grid code requirements on the Northern Ireland power system have been updated stipulating that wind farms connected after 2005 must be able to control the magnitude of oscillations in the range of 0.25 - 1.75 Hz to within 1% of the wind farm's registered output. In order to determine whether wind farm low-frequency oscillations have a negative effect (excite other modes) or possibly a positive impact (damping of existing modes) on the power system, the oscillations at the point of connection must be measured and characterised. Using time - frequency methods, research presented in this paper has been conducted to extract signal features from measured low-frequency active power pulsations produced by wind farms to determine the effective composition of possible oscillatory modes which may have a detrimental effect on system 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.

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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 paper presents a measurement based method for the early detection of power system oscillations, with attention to 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 transform and 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 different frequency bands, while SVDD 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. Method evaluation is exemplified used real data from a chosen wind farm.

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The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations has been investigated. The authors introduced data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. Through monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the two systems. The impact of tower shadow on the output power from a wind farm was analysed using data recorded on site. A case study investigates the effect on the system of the removal of a large fixed-speed wind farm. Conclusions are drawn on the impact that conventional generation and the output from fixed-speed wind farms have on the stability of the Irish power system.

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The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations was investigated. The authors used data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. By monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the Northern Ireland electricity system and that of the electricity supply board. Analysis was preformed to determine the relationship (if any) between the inter-area oscillation and the observed wind power generation at the corresponding time. Subsequently, regression analysis was introduced to model this relationship between the FFT output and the wind power generation. The effect of conventional generators on the magnitude and frequency of the inter-area oscillation was also considered.

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The inertia of fixed-speed wind turbine generators (WTGs) helps to mitigate under-frequency transients, promotes fault ride-through and damps inter-area oscillations. It is therefore important to quantify this inertia. The authors use measured wind farm responses during under-frequency transients to provide this information. They discuss the extent of the data and the criteria used to select certain events for further analysis. The estimation of WTG inertia is based on a induction generator model. The basis of the model will be described. The manner in which the model is applied to estimate the inertia from the measured data is then explained. Finally, the implications of the results for power system operation are assessed.

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The practical untenability of the quasi-static assumption makes any realistic engine intrinsically irreversible and its operating time finite, thus implying friction effects at short cycle times. An important technological goal is thus the design of maximally efficient engines working at the maximum possible power. We show that, by utilising shortcuts to adiabaticity in a quantum engine cycle, one can engineer a thermodynamic cycle working at finite power and zero friction. Our findings are illustrated using a harmonic oscillator undergoing a quantum Otto cycle.