Vattenfall

About: Vattenfall is a company organization based out in Stockholm, Sweden. It is known for research contribution in the topics: Wind power & Combustion. The organization has 685 authors who have published 857 publications receiving 18912 citations. The organization is also known as: Vattenfall AB & Kungliga Vattenfallstyrelsen.

Vattenfall Optimizes Offshore Wind Farm Design

Abstract: Key aspects of the wind farm design process include determining the placement of turbines and optimizing the cables used to interconnect them. The authors discuss their development of mixed-integer...

Is Human Reliability Relevant to Human Factors

Abstract: This paper presents a number of views from a panel discussion on the relationship between human reliability analysis (HRA) and human factors. HRA emerged concurrently with the field of human factors and now features a nearly fifty-year shared history. While built on human factors, HRA distinguished itself early on from human factors due to its emphasis on predicting human performance. While one of the major focus areas of human factors has been improving the design of novel systems to optimize human performance, HRA has largely focused on predicting human performance for as-built systems. Over time, as HRA became closely tied particularly to the nuclear energy industry, it increasingly became a field associated more with reliability engineering than human factors. Yet, the similarity to human factors has not abated, nor has the opportunity for the two fields to cooperate. Human factors research provides the empirical basis to support predicting human performance in HRA. Importantly, HRA continues to benefit human factors by providing: (1) a framework for modeling human performance, (2) an example of how a human factors discipline can be seamlessly integrated with an engineering field, and (3) insights on how predictive modeling may be used as a system design tool.

Yawing and performance of an offshore wind farm

Abstract: Optimization of yaw misalignment may improve energy output of wind farms. An analysis was made of the potential power loss of the Horns Reef wind farm due to yaw error. The method for the estimate was to measure the yaw error on an identical V80 onshore wind turbine and to extrapolate these findings to all turbines in the wind farm. The yaw errors were measured to be significant, and in average about 10° on the onshore V80 turbine. The flow inclination angle was measured to be significantly influenced by wake rotation from the neighboring wind turbines. The average power loss factor in the wind speed range 3-15m/s was found to be 0,971. Adjusting for a realistic yaw error interval the estimated power loss was 2,7%. When considering the wind distribution at the Horns Reef site and only considering the power below rated wind speed we end up with an estimated power loss of 1,6%, which corresponds to the production from 1,3 wind turbines in the Horns Reef wind farm.

Systematic Wind Farm Measurement Data Filtering Tool for Wake Model Calibration

Abstract: Wind farm wake data analysis is a complex process that requires filtering over many different types of sensors located at different geographical positions. The complexity of the task is increased by the different types of data corruption that can be present. Unfortunately, dealing with wind farm data corruption has rarely been addressed in the literature. This paper presents different methods intended to reinforce a wind farm dataset. These methods have been applied on several onshore and offshore wind farms.

MISiCFET Chemical Sensors for Applications in Exhaust Gases and Flue Gases

Abstract: A chemical gas sensor based on a silicon carbide field effect transistor with a catalytic gate metal has been under development for a number of years. The choice of silicon carbide as the semiconductor material allows the sensor to operate at high temperatures, for more than 6 months in flue gases at 300degreesC and for at least three days at 700degreesC. The chemical inertness of silicon carbide and a buried gate design makes it a suitable sensor technology for applications in corrosive environments such as exhaust gases and flue gases from boilers. The selectivity of the sensor devices is established through the choice of type and structure of the gate metal as well as the operation temperature. In this way NH3 sensors with low cross sensitivity to NOx have been demonstrated as potential sensors for control of selective catalytic reduction (SCR) of NOx by urea injection into diesel exhausts. Here we show that sensors with a porous platinum or iridium gate show different temperature ranges for NH3 detection. The hardness of the silicon carbide makes it for example more resistant to water splash at cold start of a petrol engine than existing technologies, and a sensor which can control the air to fuel ratio, before the exhaust gases are heated, has been demonstrated. Silicon carbide sensors are also tested in flue gases from boilers. Efficient regulation of the combustion in a boiler will decrease fuel consumption and reduce emissions.