Social Equity Impacts of Congestion Management Strategies

This white paper examines the social equity impacts of various congestion management strategies. The paper includes a comprehensive list of 30 congestion management strategies and a discussion of equity implications related to each strategy. The authors analyze existing literature and incorporate findings from 12 expert interviews from academic, non-governmental organization (NGO), public, and private sector respondents to strengthen results and fill gaps in understanding. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework (Shaheen et al., 2017) to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular congestion mitigation measure. The congestion management strategies discussed are grouped into six main categories, including: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation. The findings show that the social equity impacts of certain congestion management strategies are not well understood, at present, and further empirical research is needed. Congestion mitigation measures have the potential to affect travel costs, commute times, housing, and accessibility in ways that are distinctly positive or negative for different populations. For these reasons, social equity implications of congestion management strategies should be understood and mitigated for in planning and implementation of these strategies

TCP Control Groups: Aggregated Congestion Control for TCP (MA Thesis)

This thesis presents a framework for aggregated congestion management for TCP flows and shows how to integrate such an approach in an existing TCP protocol stack. The thesis presents an initial implementation of this congestion management scheme in Linux, with performance evaluation in ns as well

Policy Brief: Social Equity Impacts of Congestion Management Strategies

To better understand the equity implications of a variety of congestion management strategies, researchers at the Transportation Sustainability Research Center (TSRC) at University of California, Berkeley analyzed existing literature on congestion management strategies and findings from 12 expert interviews. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework1 to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular strategy. The congestion management strategies of interest were categorized into six broader categories: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation

Optimal network congestion management using wind farms

With the increased use of wind energy for the power generation several TSO have increasing difficulties for congestion forecasting due to the unpredictable nature of the energy source. An actual method used to deal with days-ahead congestion planning is based on an order of disconnection of the generation of the type “last generation installed, first generation limited”. This paper proposes to enhance the congestion management using a real time supervisor. This supervisor is developed to perform automatic and dynamic re-dispatching using both wind and conventional generators. In order to reduce the production constraints to the minimum, the real time congestion management is based on an indicator of the efficiency of a re-dispatching on the power flowing in the overloaded line. This approach leads to reduced re-dispatching costs and increased network reliability. Actual and proposed methods are compared in the paper using Matlab/Simulink simulations of a realistic test grid. It is shown that the real-time supervisor allows maximization of renewable production during congestions while ensuring network reliability.Congestion management; Wind farm; Power Transfer Distribution Factors (PTDF); Power system control; Active power dispatch; Variable speed wind turbines.

OFAR-CM: Efficient Dragonfly networks with simple congestion management

Dragonfly networks are appealing topologies for large-scale Data center and HPC networks, that provide high throughput with low diameter and moderate cost. However, they are prone to congestion under certain frequent traffic patterns that saturate specific network links. Adaptive non-minimal routing can be used to avoid such congestion. That kind of routing employs longer paths to circumvent local or global congested links. However, if a distance-based deadlock avoidance mechanism is employed, more Virtual Channels (VCs) are required, what increases design complexity and cost. OFAR (On-the-Fly Adaptive Routing) is a previously proposed routing that decouples VCs from deadlock avoidance, making local and global misrouting affordable. However, the severity of congestion with OFAR is higher, as it relies on an escape sub network with low bisection bandwidth. Additionally, OFAR allows for unlimited misroutings on the escape sub network, leading to unbounded paths in the network and long latencies. In this paper we propose and evaluate OFAR-CM, a variant of OFAR combined with a simple congestion management (CM) mechanism which only relies on local information, specifically the credit count of the output ports in the local router. With simple escape sub networks such as a Hamiltonian ring or a tree, OFAR outperforms former proposals with distance-based deadlock avoidance. Additionally, although long paths are allowed in theory, in practice packets arrive at their destination in a small number of hops. Altogether, OFAR-CM constitutes the first practicable mechanism to the date that supports both local and global misrouting in Dragonfly networks.The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. ERC-2012-Adg-321253- RoMoL, the Spanish Ministry of Science under contracts TIN2010-21291-C02-02, TIN2012-34557, and by the European HiPEAC Network of Excellence. M. García participated in this work while affiliated with the University of Cantabria.Peer ReviewedPostprint (author's final draft

Congestion management in the Nordic power market : nodal pricing versus zonal pricing

In the Nordic day-ahead electricity market zonal pricing or market splitting is used for relieving congestion between a predetermined set of price areas. This congestion management method represents an aggregation of individual connection points into price areas, and flows in the actual electricity network are only partially represented in the market clearing. Because of several strained situations in the power system during 2009 and 2010, changes in the congestion management method are under consideration by the Norwegian regulator NVE. We discuss three different congestion management methods – nodal pricing, and optimal and simplified zonal pricing. Four hourly cases from 2010 are used to illustrate the effects of different congestion management methods on prices, surpluses and network utilization

Congestion management in traffic-light intersections via Infinitesimal Perturbation Analysis

We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengths to given reference setpoints. The technique is based on multivariable integrators with adaptive gains, computed at each control cycle by assessing the IPA gradients of the plant functions. Moreover, the IPA gradients are computable on-line despite the absence of detailed models of the traffic flows. The technique is applied to a two-intersection system where it exhibits robustness with respect to modeling uncertainties and computing errors, thereby permitting us to simplify the on-line computations perhaps at the expense of accuracy while achieving the desired tracking. We compare, by simulation, the performance of a centralized, joint two-intersection control with distributed control of each intersection separately, and show similar performance of the two control schemes for a range of parameters