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This survey was undertaken as part of the initial phase of a larger market design project. The goal of the project is to design a wholesale electric power market such that electric energy storage (EES) resources are permitted to participate and receive compensation that is commensurate with the benefits they provide to the grid. This survey compares and contrasts 3 operating reserve markets in the seven U.S. ISO/RTO-managed electric energy regions. The reserve market categories employed in each energy region are placed into a common framework. The terminology used for reserve markets in each region, as well as the characteristics of these markets, is discussed. Finally, the market procedures currently in place in the seven energy regions for the procurement, settlement, and allocation of costs for reserves are examined.keywords: Power market design, ancillary services, operating reserve, frequency control, and electrical energy storage.4 Acknowledgment

This Handbook is a description of the complex process that comprises drilling a geothermal well. The focus of the detailed Chapters covering various aspects of the process (casing design, cementing, logging and instrumentation, etc) is on techniques and hardware that have proven successful in geothermal reservoirs around the world. The Handbook will eventually be linked to the GIA web site, with the hope and expectation that it can be continually updated as new methods are demonstrated or proven.

Distributed photovoltaic (PV) projects must go through an interconnection study process before connecting to the distribution grid. These studies are intended to identify the likely impacts and mitigation alternatives. In the majority of the cases, system impacts can be ruled out or mitigation can be identified without an involved study, through a screening process or a simple supplemental review study. For some proposed projects, expensive and timeconsuming interconnection studies are required. The challenges to performing the studies are twofold. First, every study scenario is potentially unique, as the studies are often highly specific to the amount of PV generation capacity that varies greatly from feeder to feeder and is often unevenly distributed along the same feeder. This can cause location-specific impacts and mitigations. The second challenge is the inherent variability in PV power output which can interact with feeder operation in complex ways, by affecting the operation of voltage regulation and protection devices.The typical simulation tools and methods in use today for distribution system planning are often not adequate to accurately assess these potential impacts. This report demonstrates how quasi-static time series (QSTS) simulation and high time-resolution data can be used to assess the potential impacts in a more comprehensive manner. The QSTS simulations are applied to a set of sample feeders with high PV deployment to illustrate the usefulness of the approach. The report describes methods that can help determine how PV affects distribution system operations. The simulation results are focused on enhancing the understanding of the underlying technical issues. The examples also highlight the steps needed to perform QSTS simulation and describe the data needed to drive the simulations. The goal of this report is to make the methodology of time series power flow analysis readily accessible to utilities and others responsible for evaluating potential PV impacts. 4 ACKNOWLEDGMENTSMatthew Lave for assistance with the Wavelet-based Variability Model. Wes Sunderman for assistance with the Open Distribution System Simulator. 5

The High Performance Linpack (HPL), or Top 500, benchmark [1] is the most widely recognized and discussed metric for ranking high performance computing systems. However, HPL is increasingly unreliable as a true measure of system performance for a growing collection of important science and engineering applications.In this paper we describe a new high performance conjugate gradient (HPCG) benchmark. HPCG is composed of computations and data access patterns more commonly found in applications. Using HPCG we strive for a better correlation to real scientific application performance and expect to drive computer system design and implementation in directions that will better impact performance improvement.