Analysis and Control of Offshore Wind Power Collection Systems

The utilization of offshore wind energy in power systems generally includes power generation, power collection and power transmission. An efficient wind energy conversion system is proposed for offshore wind power generation. Three types of DC collection systems are discussed for both normal and fault operations. To integrate the power from several offshore wind farms with a grid, the multi-terminal HVDC system is applied. All the proposals are verified through extensive simulation studies

Estimating vehicles emissions at signalized intersections in the highway capacity manual

Over the past decades, motor vehicle volumes have continued to increase at a high rate. As a result, engineers in the transportation field not only need more robust knowledge of traffic operation control and transportation planning, but more attention is also needed to understand and estimate the influences that this increasing volume of vehicles has on the environment, especially the influence on air quality. The EPA has stated that reducing carbon monoxide (CO) from vehicle emissions is the most significant way to control air pollution from the transportation sector. The Highway Capacity Manual is a national and international resource that has become a guideline for evaluating the operation of roadway, transit and pedestrian facilities. The Highway Capacity Manual assesses the operation of a roadway based on the perception of its users. Performance measures are used to describe the traffic operation of the roadway. At present, no measures are provided to describe the operation of the roadway based on environmental impacts. The incorporation of air pollution estimation into the Highway Capacity Manual will allow the roadway’s operation to be assessed both from an operational and environmental aspect, ultimately creating a sustainable development for both transportation and the environment. The objective of this dissertation is to develop MOVES-like estimation models of vehicle emissions for pollutants at a signalized intersection that can be incorporated into the Highway Capacity Manual. “EPA’s Motor Vehicle Emission Simulator (MOVES) is a state-of-the-art emission modeling system that estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants, greenhouse gases, and air toxics.” (EPA, 2014). A thorough understanding is needed about what parameters, and influence of these parameters on vehicle emissions. This dissertation develops two kinds of models in order to estimate emissions caused by on-road vehicles. Two modeling approaches are used to estimate four kinds of emissions including CO, NO, NH3 and NOX separately. The following summarizes the work of this dissertation: The objective of this dissertation is to develop MOVES-like estimation models of vehicle emissions for pollutants at a signalized intersection that can be incorporated into the Highway Capacity Manual. “EPA’s Motor Vehicle Emission Simulator (MOVES) is a state-of-the-art emission modeling system that estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants, greenhouse gases, and air toxics.” (EPA, 2014). A thorough understanding is needed about what parameters, and influence of these parameters on vehicle emissions. This dissertation develops two kinds of models in order to estimate emissions caused by on-road vehicles. Two modeling approaches are used to estimate four kinds of emissions including CO, NO, NH3 and NOX separately. The following summarizes the work of this dissertation: (1) Two modeling approaches are used to estimate vehicle emissions including: multiple linear regression and Artificial Neural Network (ANN). In the multiple linear regression modeling, two different models were developed including one model using operation modes as independent variables and another model using traffic related parameters as independent variables. Both model approaches and independent variables are used to estimate four types of pollutant emissions. Statistically, the emission models using traffic parameters as independent HCM related parameters are capable of providing a better emissions estimate based on the higher R square value. For CO, the variables found to be significant were volume to capacity ratio and grade with an R2 of 61.56%. For NO, the variables found to be significant were volume to capacity ratio and grade with an R2 of 99.47%. For NOx, the variables found to be significant were volume to capacity ratio and grade with an R2 of 99.47%. For NH3, the variables found to be significant were volume to capacity ratio and grade with an R2 of 99.25%. This study shows that volume to capacity dominate the emissions quality at a signalized intersection. The research found that for NOx, Idling and Moderate Speed Coasting were significant. For NH3, all variables were significant except Low Speed Coasting. For CO, Braking and Cruise/Acceleration were significant. It was also found that longer delay time reduces CO emissions, but it causes the other three pollutant emissions increase. (2) The ANN modeling method using the Levenberg-Marquardt method was used to train the HCM related variables and MOVES emissions outputs. The parameters of volume to capacity ratio, and road grade are used to estimate emissions. The Validated R value of the obtained ANN model is found

Power Quality Signal De-noising with Sub band Adaptive Algorithm

A new level-dependent sub band adaptive noise reduction algorithm based on wavelet transform is proposed in order to improve the effect of power quality signal de-noising for power quality monitoring system. This threshold algorithm has two adjustable parameters to adjust the threshold both fine and coarsely, and the optimal parameters are determined by BP neural networks algorithm. Power disturbance data is referred to actual power disturbance data at IEEE open source and applied for test. The test results indicate that the proposed algorithm could denoise the different kind of power disturbances effectively, and the signal noise ratio is improved further with a smaller mean square error

Selective disruption of high sensitivity heat activation but not capsaicin activation of TRPV1 channels by pore turret mutations.

The capsaicin receptor transient receptor potential vanilloid (TRPV)1 is a highly heat-sensitive ion channel. Although chemical activation and heat activation of TRPV1 elicit similar pungent, painful sensation, the molecular mechanism underlying synergistic activation remains mysterious. In particular, where the temperature sensor is located and whether heat and capsaicin share a common activation pathway are debated. To address these fundamental issues, we searched for channel mutations that selectively affected one form of activation. We found that deletion of the first 10 amino acids of the pore turret significantly reduced the heat response amplitude and shifted the heat activation threshold, whereas capsaicin activation remained unchanged. Removing larger portions of the turret disrupted channel function. Introducing an artificial sequence to replace the deleted region restored sensitive capsaicin activation in these nonfunctional channels. The heat activation, however, remained significantly impaired, with the current exhibiting diminishing heat sensitivity to a level indistinguishable from that of a voltage-gated potassium channel, Kv7.4. Our results demonstrate that heat and capsaicin activation of TRPV1 are structurally and mechanistically distinct processes, and the pore turret is an indispensible channel structure involved in the heat activation process but is not part of the capsaicin activation pathway. Synergistic effect of heat and capsaicin on TRPV1 activation may originate from convergence of the two pathways on a common activation gate