Benefits Assessment for Tactical Runway Configuration Management Tool

The Tactical Runway Configuration Management (TRCM) software tool was developed to provide air traffic flow managers and supervisors with recommendations for airport configuration changes and runway usage. The objective for this study is to conduct a benefits assessment at Memphis (MEM), Dallas Fort-Worth (DFW) and New York's John F. Kennedy (JFK) airports using the TRCM tool. Results from simulations using the TRCM-generated runway configuration schedule are compared with results using historical schedules. For the 12 days of data used in this analysis, the transit time (arrival fix to spot on airport movement area for arrivals, or spot to departure fix for departures) for MEM departures is greater (7%) than for arrivals (3%); for JFK, there is a benefit for arrivals (9%) but not for departures (-2%); for DFW, arrivals show a slight benefit (1%), but this is offset by departures (-2%). Departure queue length benefits show fewer aircraft in queue for JFK (29%) and MEM (11%), but not for DFW (-13%). Fuel savings for surface operations at MEM are seen for both arrivals and departures. At JFK there are fuel savings for arrivals, but these are offset by increased fuel use for departures. In this study, no surface fuel benefits resulted for DFW. Results suggest that the TRCM algorithm requires modifications for complex surface traffic operations that can cause taxi delays. For all three airports, the average number of changes in flow direction (runway configuration) recommended by TRCM was many times greater than the historical data; TRCM would need to be adapted to a particular airport's needs, to limit the number of changes to acceptable levels. The results from this analysis indicate the TRCM tool can provide benefits at some high-capacity airports. The magnitude of these benefits depends on many airport-specific factors and would require adaptation of the TRCM tool; a detailed assessment is needed prior to determining suitability for a particular airport

From Packet to Power Switching: Digital Direct Load Scheduling

At present, the power grid has tight control over its dispatchable generation capacity but a very coarse control on the demand. Energy consumers are shielded from making price-aware decisions, which degrades the efficiency of the market. This state of affairs tends to favor fossil fuel generation over renewable sources. Because of the technological difficulties of storing electric energy, the quest for mechanisms that would make the demand for electricity controllable on a day-to-day basis is gaining prominence. The goal of this paper is to provide one such mechanisms, which we call Digital Direct Load Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle individual requests for energy and digitize them so that they can be automatically scheduled in a cellular architecture. Specifically, rather than storing energy or interrupting the job of appliances, we choose to hold requests for energy in queues and optimize the service time of individual appliances belonging to a broad class which we refer to as "deferrable loads". The function of each neighborhood scheduler is to optimize the time at which these appliances start to function. This process is intended to shape the aggregate load profile of the neighborhood so as to optimize an objective function which incorporates the spot price of energy, and also allows distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications (JSAC): Smart Grid Communications series, to appea

On Spectrum Sharing Between Energy Harvesting Cognitive Radio Users and Primary Users

This paper investigates the maximum secondary throughput for a rechargeable secondary user (SU) sharing the spectrum with a primary user (PU) plugged to a reliable power supply. The SU maintains a finite energy queue and harvests energy from natural resources and primary radio frequency (RF) transmissions. We propose a power allocation policy at the PU and analyze its effect on the throughput of both the PU and SU. Furthermore, we study the impact of the bursty arrivals at the PU on the energy harvested by the SU from RF transmissions. Moreover, we investigate the impact of the rate of energy harvesting from natural resources on the SU throughput. We assume fading channels and compute exact closed-form expressions for the energy harvested by the SU under fading. Results reveal that the proposed power allocation policy along with the implemented RF energy harvesting at the SU enhance the throughput of both primary and secondary links

Applications of stochastic modeling in air traffic management : Methods, challenges and opportunities for solving air traffic problems under uncertainty

In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management

Dynamic traffic assignment: model classifications and recent advances in travel choice principles

Dynamic Traffic Assignment (DTA) has been studied for more than four decades and numerous reviews of this research area have been conducted. This review focuses on the travel choice principle and the classification of DTA models, and is supplementary to the existing reviews. The implications of the travel choice principle for the existence and uniqueness of DTA solutions are discussed, and the interrelation between the travel choice principle and the traffic flow component is explained using the nonlinear complementarity problem, the variational inequality problem, the mathematical programming problem, and the fixed point problem formulations. This paper also points out that all of the reviewed travel choice principles are extended from those used in static traffic assignment. There are also many classifications of DTA models, in which each classification addresses one aspect of DTA modeling. Finally, some future research directions are identified.postprin