Benchmarking Utility Clean Energy Deployment: 2016

Benchmarking Utility Clean Energy Deployment: 2016 provides a window into how the global transition toward clean energy is playing out in the U.S. electric power sector. Specifically, it reveals the extent to which 30 of the largest U.S. investor-owned electric utility holding companies are increasingly deploying clean energy resources to meet customer needs.Benchmarking these companies provides an opportunity for transparent reporting and analysis of important industry trends. It fills a knowledge gap by offering utilities, regulators, investors, policymakers and other stakeholders consistent and comparable information on which to base their decisions. And it provides perspective on which utilities are best positioned in a shifting policy landscape, including likely implementation of the U.S. EPA's Clean Power Plan aimed at reducing carbon pollution from power plants

EU and OECD benchmarking and peer review compared

Benchmarking and peer review are essential elements of the so-called EU open method of coordination (OMC) which has been contested in the literature for lack of effectiveness. In this paper we compare benchmarking and peer review procedures as used by the EU with those used by the OECD. Different types of benchmarking and peer review are distinguished and pitfalls for (international) benchmarking are discussed. We find that the OECD has a clear single objective for its benchmarking and peer review activities (i.e. horizontal policy transfers) whereas the EU suffers from a mix of objectives (a. horizontal policy learning; b. EU wide vertical policy coordination and c. multilateral monitoring and surveillance under the shadow of hierarchy). Whereas the OECD is able to skirt around most of the benchmarking pitfalls, this is not the case for the EU. It is argued that, rather than continue working with the panacea OMC benchmarking and peer review currently represents, EU benchmarking should take a number of more distinct shapes in order to improve effectiveness. Moreover, in some areas benchmarking and peer review are not sufficient coordination tools, and are at best additional to those means of coordination that include enforceable sanctions

Benchmarking Utility Clean Energy Deployment: 2014

This report assembles data from more than 10 sources, including state Renewable Portfolio Standard (RPS) annual reports, U.S. Securities and Exchange Commission 10-K filings and Public Utility Commission reports, to show how 32 of the largest U.S. investor-owned electric utility holding companies stack up on renewable energy and energy efficiency

RoboTSP - A Fast Solution to the Robotic Task Sequencing Problem

In many industrial robotics applications, such as spot-welding, spray-painting or drilling, the robot is required to visit successively multiple targets. The robot travel time among the targets is a significant component of the overall execution time. This travel time is in turn greatly affected by the order of visit of the targets, and by the robot configurations used to reach each target. Therefore, it is crucial to optimize these two elements, a problem known in the literature as the Robotic Task Sequencing Problem (RTSP). Our contribution in this paper is two-fold. First, we propose a fast, near-optimal, algorithm to solve RTSP. The key to our approach is to exploit the classical distinction between task space and configuration space, which, surprisingly, has been so far overlooked in the RTSP literature. Second, we provide an open-source implementation of the above algorithm, which has been carefully benchmarked to yield an efficient, ready-to-use, software solution. We discuss the relationship between RTSP and other Traveling Salesman Problem (TSP) variants, such as the Generalized Traveling Salesman Problem (GTSP), and show experimentally that our method finds motion sequences of the same quality but using several orders of magnitude less computation time than existing approaches.Comment: 6 pages, 7 figures, 1 tabl

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram