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Transmission Risk Optimization in Interconnected Systems: Risk-Adjusted Available Transfer Capability

Transmission Risk Optimization in Interconnected Systems: Risk-Adjusted Available Transfer Capability
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Author(s): Nimal Madhu M. (Asian Institute of Technology, Thailand), Jai Govind Singh (Asian Institute of Technology, Thailand), Vivek Mohan (National Institute of Technology Tiruchirappalli, India)and Weerakorn Ongsakul (Asian Institute of Technology, Thailand)
Copyright: 2021
Pages: 17
Source title: Research Advancements in Smart Technology, Optimization, and Renewable Energy
Source Author(s)/Editor(s): Pandian Vasant (University of Technology Petronas, Malaysia), Gerhard Weber (Poznan University of Technology, Poland)and Wonsiri Punurai (Mahidol University, Thailand)
DOI: 10.4018/978-1-7998-3970-5.ch010

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Abstract

Available transfer capability is a key indicator of transmission reliability and varies with the variation in power flow pattern through the network. ATC determination considering the uncertainties in renewable generation and demand is of key significance for the safe and economic operation of power system, especially in a competitive market environment. A two-stage, risk-adjusted, generation dispatch minimizing the variation in ATC, caused by the changes in renewable energy power output and the change in load, is discussed. The solution strategy is designed for a network operator, considering the ease of use and practicality. A combined transmission-distribution system with solar, wind, and conventional dispatchable energy sources is developed, and ATC for the systems is estimated combining continuation power flow and power transfer sensitivity factor methods. The joint probability distribution function of ATC is derived using individual discrete probabilities renewable power generation and loads. Risk, quantified as the variance of ATC, is minimized using stochastic weight trade-off non-dominated sorting particle swarm optimization, considering various goals of the network operator, for example, maximizing overall system performance and minimizing the renewable energy risk.

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