40 resultados para Active power filters


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This paper investigates the use of plug-in parking lots (SmartPark) as integral energy storage to improve small-signal stability using plug-in electric vehicles (PEV). The paper establishes the Phillips-Heffron model of a power system for a SmartPark solution. Based on this model, SmartPark-based stabilisers have been designed based using phase compensation to improve power system oscillation stability. The effectiveness of stabilisation superimposed on the active and reactive power regulators is verified by simulations obtained from a multi-machine power system model with SmartPark and a large-scale wind farm inclusion.

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The doubly-fed induction generator (DFIG) now represents the dominant technology in wind turbine design. One consequence of this is limited damping and inertial response during transient grid disturbances. A dasiadecoupledpsila strategy is therefore proposed to operate the DFIG grid-side converter (GSC) as a static synchronous compensator (STATCOM) during a fault, supporting the local voltage, while the DFIG operates as a fixed-speed induction generator (FSIG) providing an inertial response. The modeling aspects of the decoupled control strategy, the selection of protection control settings, the significance of the fault location and operation at sub- and super-synchronous speeds are analyzed in detail. In addition, a case study is developed to validate the proposed strategy under different wind penetrations levels. The simulations show that suitable configuration of the decoupled strategy can be deployed to improve system voltage stability and inertial response for a range of scenarios, especially at high wind penetration. The conclusions are placed in context of the practical limitations of the technology employed and the system conditions.

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In the United Kingdom wind power is recognised as the main source of renewable energy to achieve the European Union 2020 renewable energy targets. Currently over 50% of renewable power is generated from onshore wind with a large number of offshore wind projects in development. Recently the government has re-iterated its commitment to offshore wind power and has announced that offshore wind subsidies are to increase from £135/MWh to £140/MWh until 2019. This paper provides a detailed overview of the offshore wind power industry in the United Kingdom in terms of market growth, policy development and offshore wind farm costs. The paper clearly shows that the United Kingdom is the world leader for installed offshore wind power capacity as pro-active policies and procedures have made it the most attractive location to develop offshore wind farm arrays. The key finding is that the United Kingdom has the potential to continue to lead the world in offshore wind power as it has over 48 GW of offshore wind power projects at different stages of operation and development. The growth of offshore wind power in the United Kingdom has seen offshore wind farm costs rise and level off at approximately £3 million/MW, which are higher than onshore wind costs at £1.5–2 million/MW. Considering the recent increase in offshore wind power subsidies and plans for 48 GW of offshore wind power could see more offshore wind power becoming increasingly financially competitive with onshore wind power. Therefore offshore wind power is likely to become a significant source of electricity in the United Kingdom beyond 2020.

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In this paper, we propose a novel finite impulse response (FIR) filter design methodology that reduces the number of operations with a motivation to reduce power consumption and enhance performance. The novelty of our approach lies in the generation of filter coefficients such that they conform to a given low-power architecture, while meeting the given filter specifications. The proposed algorithm is formulated as a mixed integer linear programming problem that minimizes chebychev error and synthesizes coefficients which consist of pre-specified alphabets. The new modified coefficients can be used for low-power VLSI implementation of vector scaling operations such as FIR filtering using computation sharing multiplier (CSHM). Simulations in 0.25um technology show that CSHM FIR filter architecture can result in 55% power and 34% speed improvement compared to carry save multiplier (CSAM) based filters.

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This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications. 

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We investigate intensity variations and energy deposition in five coronal loops in active region cores. These were selected for their strong variability in the AIA/SDO 94 Å intensity channel. We isolate the hot Fe XVIII and Fe XXI components of the 94 Å and 131 Å by modeling and subtracting the "warm" contributions to the emission. HMI/SDO data allow us to focus on "inter-moss" regions in the loops. The detailed evolution of the inter-moss intensity time series reveals loops that are impulsively heated in a mode compatible with a nanoflare storm, with a spike in the hot 131 Å signals leading and the other five EUV emission channels following in progressive cooling order. A sharp increase in electron temperature tends to follow closely after the hot 131 Å signal confirming the impulsive nature of the process. A cooler process of growing emission measure follows more slowly. The Fourier power spectra of the hot 131 Å signals, when averaged over the five loops, present three scaling regimes with break frequencies near 0.1 min–1 and 0.7 min–1. The low frequency regime corresponds to 1/f noise; the intermediate indicates a persistent scaling process and the high frequencies show white noise. Very similar results are found for the energy dissipation in a 2D "hybrid" shell model of loop magneto-turbulence, based on reduced magnetohydrodynamics, that is compatible with nanoflare statistics. We suggest that such turbulent dissipation is the energy source for our loops

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Energy consumption has become an important area of research of late. With the advent of new manycore processors, situations have arisen where not all the processors need to be active to reach an optimal relation between performance and energy usage. In this paper a study of the power and energy usage of a series of benchmarks, the PARSEC and the SPLASH- 2X Benchmark Suites, on the Intel Xeon Phi for different threads configurations, is presented. To carry out this study, a tool was designed to monitor and record the power usage in real time during execution time and afterwards to compare the r

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Currently wind power is dominated by onshore wind farms. However, as the demand for power grows driven by security of energy supply issues, dwindling fossil fuel supplies and greenhouse gas emissions reduction targets, offshore wind power will develop rapidly because of the decline of viable onshore sites. The United Kingdom has a target of 21% renewable electricity by 2020 and this is expected to come mostly from wind power. Britain is the most active internationally in terms of offshore wind farm development with almost 48GW in some stage of development. In addition the Scottish Government, the Northern Ireland Executive and the Government of Ireland undertook the 'Irish-Scottish Links on Energy Study' (ISLES), which examined the feasibility of creating an offshore interconnected transmission network and subsea electricity grid based on renewable energy sources off the coast of western Scotland and the Irish Sea. The aim of this paper is to provide an appraisal of offshore wind power development with a focus on the United Kingdom. © 2013 IEEE.

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Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.

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Background
Prostate cancer is one of the most common male cancers worldwide. Active Surveillance (AS) has been developed to allow men with lower risk disease to postpone or avoid the adverse side effects associated with curative treatments until the disease progresses. Despite the medical benefits of AS, it is reported that living with untreated cancer can create a significant emotional burden for patients.

Methods/design
The aim of this study is to gain insight into the experiences of men eligible to undergo AS for favourable-risk PCa.

This study has a mixed-methods sequential explanatory design consisting of two phases: quantitative followed by qualitative. Phase 1 has a multiple point, prospective, longitudinal exploratory design. Ninety men diagnosed with favourable-risk prostate cancer will be assessed immediately post-diagnosis (baseline) and followed over a period of 12 months, in intervals of 3 month. Ninety age-matched men with no cancer diagnosis will also be recruited using peer nomination and followed up in the same 3 month intervals. Following completion of Phase 1, 10–15 AS participants who have reported both the best and worst psychological functioning will be invited to participate in semi-structured qualitative interviews. Phase 2 will facilitate further exploration of the quantitative results and obtain a richer understanding of participants’ personal interpretations of their illness and psychological wellbeing.

Discussion
To our knowledge, this is the first study to utilise early baseline measures; include a healthy comparison group; calculate sample size through power calculations; and use a mixed methods approach to gain a deeper more holistic insight into the experiences of men diagnosed with favourable-risk prostate cancer.