A Multi-Criteria Decision Framework for Optimal Augmentation of Transmission Grid Addressing a Tool for Sensitive Zone Detection in Electricity Market

M.R. Hesamzadeh, N. Hosseinzadeh, and P.J. Wolfs (Australia)


Sensitivity Analysis, Reliability, Electricity Market, Planning, Dynamic Programming, Linear Programming, Single Contingency


Transmission system structure under pool model of electricity market has an essential effect on the reliability and electricity market performance, especially when producers bids strategically. As a part of an on-going research on the design of a robust algorithm for expansion planning of transmission grid in the Australian electricity market, this paper presents a framework which addresses; (1) Security of power delivery to the load points of transmission system in case of single line outages, (2) Minimization of transmission system lost load, (3) Providing full competitive electricity market for market participants, (4) Construction and maintenance costs of transmission augmentation options, (5) Operation efficiency of transmission grid, in its planning procedure. The suggested algorithm benefits from the dynamic programming and sensitivity analysis approaches along with aggregation method in its multi criteria decision making to locate the optimum configuration of future transmission system. A set of indices that account for impacts of the augmentation options of the transmission grid on five aforementioned reliability and market criteria, are proposed and used in the optimum framework for expansion planning of the transmission grid. Although the methodology is promising for expansion planning of the transmission system and considering the sensitivity analysis concept employed, the proposed methodology would be able to detect the sensitive areas of the transmission system to be expanded. The tool would be very useful in the case of large scale power systems for a smart reduction of the power system. The proposed methodology is applied to a 6 bus and a modified IEEE 30 bus test system to show the effectiveness of the sensitivity based algorithm.

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