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Wang Q.,20 City Center Drive | McCalley J.D.,Iowa State University | Li W.,Iowa State University
Electric Power Systems Research

This paper uses QV curve analysis to investigate the voltage instability performance of risk-based security-constrained optimal power flow (RB-SCOPF), where risk is modeled to capture the system's overall security level. The RB-SCOPF is an improvement of the traditional security-constrained optimal power flow (SCOPF) model. In previous works, we have demonstrated that the operating conditions obtained from RB-SCOPF were more secure (less risky) than those obtained from SCOPF. This raises the question of whether the RB-SCOPF operating condition is more stable than the SCOPF-operating condition for a power system. We respond to this question by comparing the voltage stability performance of operating conditions obtained from RB-SCOPF and SCOPF. We employ a practical algorithm to obtain the QV curves at the buses of concern and calculate the reactive power reserves associated with each bus for operating conditions obtained from RB-SCOPF and SCOPF, respectively. Test results for IEEE 30-bus system are presented to illustrate that RB-SCOPF has better voltage instability performance than SCOPF. © 2014 Elsevier B.V. Source

Wang Q.,20 City Center Drive | McCalley J.D.,Iowa State University | Zheng T.,ISO New England | Litvinov E.,ISO New England
International Journal of Electrical Power and Energy Systems

This paper presents an efficient decomposition based algorithm to solve the corrective risk-based security-constrained optimal power flow (CRB-SCOPF) problem. The mathematical formulation was proposed imposing, in addition to the traditional post-contingency corrective constraints, constraints related to both circuit risk and system risk. Solving the CRB-SCOPF model is difficult since the risk index is a function of conditions under normal and all contingencies, and thus it greatly increases the dimension of the optimization problem. The proposed approach applies Lagrangian relaxation to the system risk constraints and then applies Benders decomposition to the remaining Lagrangian subproblem. The proposed approach is tested on the IEEE 30-bus system and on the ISO New England bulk system. © 2015 Elsevier Ltd. All rights reserved. Source

Khazaei J.,University of South Florida | Fan L.,University of South Florida | Jiang W.,20 City Center Drive | Manjure D.,20 City Center Drive
Electric Power Systems Research

Prony analysis has been applied in power system oscillation identification for decades. For a single PMU signal with 30 Hz sampling rate, merely applying Prony analysis cannot give accurate results of oscillating modes of power systems. This paper presents an analysis to show the effect of sampling rate on estimation accuracy and the mitigation methods to obtain accurate estimation. The methods include sampling rate reduction and multiple-signal Prony analysis. For multiple-signal Prony analysis, this paper proposes a distributed Prony analysis algorithm using consensus and subgradient update. This algorithm can be applied to multiple signals from multiple locations collected at the same period of time. This algorithm is scalable and can handle a large-dimension of PMU data by solving least square estimation problems with small sizes in parallel and iteratively. Real-world PMU data are used for analysis and validation. The proposed distributed Prony analysis shows being robust against sampling rate and generates reconstructed signals with better matching degree compared to the conventional Prony analysis for multiple signals. © 2015 Elsevier B.V. All rights reserved. Source

Zhang X.,20 City Center Drive | Wang Q.,20 City Center Drive | Xu G.,Siemens AG | Wu Z.,University of Denver
IEEE PES Innovative Smart Grid Technologies Conference Europe

The growing regulatory environment and security concerns about fossil fuels are driving the research and development of new technologies that can contribute significantly to sustainable and resilient urban energy systems. Plug-in electric vehicle (PEV) is just one of those new technologies that meet current and future environmental and economic challenges of transportation. By charging from the electric power grid or renewables, aggregated PEVs can be deployed as dynamically configurable distributed energy storages (DESs) to supply additional power to home appliances, buildings, or the electric power grid when necessary. This growing PEV penetration coupled with the increasing consumers' interaction with market operations are paving the way for decentralized electric power systems that promise to be efficient, reliable, flexible, economic, and environmentally friendly. This study surveys and summarizes the latest progress and advancement of PEVs, especially as mobile DESs in the areas of technologies, market development, policy, system impact and operations, and relevant pairing infrastructures in smart grid environment. © 2014 IEEE. Source

Zhang X.,20 City Center Drive | Chatterjee D.,20 City Center Drive | Peng T.,20 City Center Drive | Sutton R.,20 City Center Drive
IEEE Power and Energy Society General Meeting

Correct interface definition and pricing is essential to address uncertainty and schedule economic and efficient interchange transactions between Regional Transmission Organizations (RTOs) or between RTOs and non-market entities, e.g. Tennessee Valley Authority (TVA). Incorrect interface prices cannot reflect the true incremental system dispatch cost or decremental system production cost savings, thus resulting in inefficient interchanges that flow from higher-cost regions to lower-cost regions, as well as uneconomic transactions that were charged more for the export and credited less for the import, or vice versa. Also, correct interface pricing is a key role leading to the joint optimal dispatch between two RTOs, e.g. Midcontinent Independent System Operator (MISO) and PJM Interconnection (PJM). This paper proposes and summarizes new designed solution methodologies aiming to resolve interface pricing related issues and thus improve electricity market efficiency and performance. © 2014 IEEE. Source

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