Scandinavian demonstration projects for sustainable energy and transport:Their contribution to the formation of broad and aligned networks

This report gives results of an analysis of effects of demonstration projects in transition processes to sustainable energy and transport in the Scandinavian countries. The report is a result of the research project “Role of demonstration projects in innovation: transition to sustainable energy and transport” (2013–2014). It was funded by the Forfi programme at the Research Council of Norway

The biogas value chains in the Swedish region of Skåne

Biogas systems are complex in the sense that they cut across several sectors, mainly agriculture, waste management and energy. Cooperation between actors in these sectors must work for biogas projects to be realised and successful. The aim of this report is to describe the biogas systems in Skåne from a value chain perspective, including important development pathways. The different segments in the value chain are mapped with regard to actors, actors in supporting activities, technologies and institutions (mainly regulations). Skåne is a fairly small part of Sweden in terms of land area but it is the most important agricultural and food producing region in Sweden and comparatively densely populated. These characteristics explain why Skåne is an important (if not the most important) biogas region in Sweden. The earliest applications of biogas were for the purpose of reducing the volume of sewage from waste water treatment plants. The biogas produced was used mainly for plant process needs and part of it was often flared. Much of the biogas today, from a variety of types of biogas plants, is upgraded and used for transport. The development towards transport applications can be traced back to the desire to reduce oil dependence and urban air pollution from diesel buses. Initially buses were converted to compressed natural gas, but with regional ambitions for fossil free public transport attention in recent years has turned to compressed biogas. Biogas value chains have developed in response to sustainability concerns in energy and transport, sewage sludge and waste handling, and in agriculture. The development has generated new business opportunities, especially in the field of upgrading. The production of biogas, for transport fuel, waste handling and fertiliser, is expected to continue to grow in Skåne

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs

Comparison of Fuel Consumption of Descent Trajectories Under Arrival Metering

This paper compares fuel consumption of descent trajectories from cruise altitude to meter fix when the required time of arrival is later than the nominal time of arrival at the meter fix. The required delay, which is the difference between the nominal and the required times of arrival, is achieved by either slowing down the aircraft in the cruise and descent phases or flying a longer route at a constant altitude. Performance models of ten different Boeing and Airbus aircraft, obtained from the Base of Aircraft Data, are employed for generating the results. It is demonstrated that the most fuel-efficient speed control strategy for absorbing delay is first reducing descent speed as much as possible and then reducing cruise speed. This is a common finding for all ten aircraft considered. For some aircraft, flying at a fixed flight path angle and constant Mach-calibrated-airspeed results in lower fuel consumption compared to standard descent at idle-thrust and constant Mach-calibrated- airspeed. Finally, for the cases examined, it is shown that executing a path stretch maneuver at cruise altitude and descent at a reduced speed is more fuel efficient than inserting an intermediate-altitude cruise segment

Performance of an Automated System for Control of Traffic in Terminal Airspace

This paper examines the performance of a system that performs automated conflict resolution and arrival scheduling for aircraft in the terminal airspace around major airports. Such a system has the potential to perform separation assurance and arrival sequencing tasks that are currently handled manually by human controllers. The performance of the system is tested against several simulated traffic scenarios that are characterized by the rate at which air traffic is metered into the terminal airspace. For each traffic scenario, the levels of performance that are examined include: number of conflicts predicted to occur, types of resolution maneuver used to resolve predicted conflicts, and the amount of delay for all flights. The simulation results indicate that the percentage of arrivals that required a maneuver that changes the flight's horizontal route ranged between 11% and 15% in all traffic scenarios. That finding has certain implications if this automated system were to be implemented simply as a decision support tool. It is also found that arrival delay due to purely wake vortex separation requirements on final approach constituted only between 29% and 35% of total arrival delay, while the remaining major portion of it is mainly due to delay back propagation effects

Algorithms for Control of Arrival and Departure Traffic in Terminal Airspace

This paper presents a design approach and basic algorithms for a future system that can perform aircraft conflict resolution, arrival scheduling and convective weather avoidance with a high level of autonomy in terminal area airspace. Such a system, located on the ground, is intended to solve autonomously the major problems currently handled manually by human controllers. It has the potential to accommodate higher traffic levels and a mix of conventional and unmanned aerial vehicles with reduced dependency on controllers. The main objective of this paper is to describe the fundamental trajectory and scheduling algorithms that provide the foundation for an autonomous system of the future. These algorithms generate trajectories that are free of conflicts with other traffic, avoid convective weather if present, and provide scheduled times for landing with specified in-trail spacings. The maneuvers the algorithms generate to resolve separation and spacing conflicts include speed, horizontal path, and altitude changes. Furthermore, a method for reassigning arrival aircraft to alternate runways in order to reduce delays is also included. The algorithms generate conflict free trajectories for terminal area traffic, comprised primarily of arrivals and departures to and from multiple airports. Examples of problems solved and performance statistics from a fast-time simulation using simulated traffic of arrivals and departures at the Dallas/Fort Worth International Airport and Dallas Love Field are described