this paper is a result of ongoing activity carried out by Understanding, Prediction, Mitigation and Restoration of Cascading Failures Task Force under IEEE Computer Analytical Methods Subcommittee (CAMS). The task force's previous papers [1, 2] are focused on general aspects of cascading outages such as understanding, prediction, prevention and restoration from cascading failures. This is the second of two new papers, which extend this previous work to summarize the state of the art in cascading failure risk analysis methodologies and modeling tools. The first paper reviews the state of the art in methodologies for performing risk assessment of potential cascading outages [3]. This paper describes the state of the art in cascading failure modeling tools, documenting the view of experts representing utilities, universities and consulting companies. The paper is intended to constitute a valid source of information and references about presently available tools that deal with prediction of cascading failure events. This effort involves reviewing published literature and other documentation from vendors, universities and research institutions. The assessment of cascading outages risk evaluation is in continuous evolution. Investigations to gain even better understanding and identification of cascading events are the subject of several research programs underway aimed at solving the complexity of these events that electrical utilities face today. Assessing the risk of cascading failure events in planning and operation for power transmission systems require adequate mathematical tools/software.

SUMMARYVoltage stability analysis and control are key applications for maintaining and enhancing the voltage security of bulk power systems. In today's control center, as power systems become more stressed and the penetration of renewable energies increases, system operators need to analyze voltage security of the systems based on actual operating conditions, contingency and power transactions of the system. In this paper, the model used to represent a power system losing stability is described. It is shown that the voltage collapse point is reached at saddlenode bifurcation or a structure-induced bifurcation. Computation of P-V curves showing system load margin to voltage collapse, system load margin to voltage-limit violation and system load margin to thermal-limit violation is presented. The architecture and example results of the Voltage Stability Analysis and Enhancement system at the California Independent System Operator implementing this research are shown. The continuation power flow engine at the core of this work is presented in detail, and study results are shown. Other key functions, contingency selection (insecure or critical) and ranking, preventive control to increase the load margin of insecure contingencies such that it is secure and enhancement control to increase the load margin of critical contingencies, are presented. Finally, a novel method to enhance the continuation power flow in handling uncertainty of renewable energy is shown.

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The California Independent System Operator Corporation (CAISO) is in charge of managing the electricity flow along California's open-market wholesale power grid. The CAISO implemented a nodal LMP Electricity Market based on the full network model and upgraded its infrastructure with new state of the art technology in 2009. The implementation of the new market system utilized the Service Oriented Architecture (SOA) and enterprise service bus-based technology to integrate many of the CAISO systems to assure grid reliability and efficient and economic operation of the electricity market. The CAISO systems are acquired from different application vendors and this created an integration challenge. This paper summarizes how CAISO leverages IEC TC57 Common Information Model (CIM) for the network models and enterprise wide messaging in integrating different applications from different vendors. The paper will also outline how CAISO created CIM extensions for different market and grid applications and network models used by CAISO. Index Terms-Common Information Model (CIM), California Independent System Operator Corporation (CAISO), Full Network Model, Market CIM Extension

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