Co-optimizing Generation and Transmission Expansion with Wind Power in Large-Scale Power Grids Implementation in the US Eastern Interconnection

You, Shutang; Hadley, Stanton W.; Shankar, Mallikarjun; Liu, Yilu

doi:10.1016/j.epsr.2015.12.023

Title: Co-optimizing Generation and Transmission Expansion with Wind Power in Large-Scale Power Grids Implementation in the US Eastern Interconnection

Journal Article · Tue Jan 12 00:00:00 EST 2016 · Electric Power Systems Research

DOI:https://doi.org/10.1016/j.epsr.2015.12.023· OSTI ID:1237158

You, Shutang ^[1]; Hadley, Stanton W. ^[2]; Shankar, Mallikarjun ^[2]; Liu, Yilu ^[3]

University of Tennessee, Knoxville (UTK)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
University of Tennessee, Knoxville (UTK); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

This paper studies the generation and transmission expansion co-optimization problem with a high wind power penetration rate in the US Eastern Interconnection (EI) power grid. In this paper, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. Our paper also analyzed a time series generation method to capture the variation and correlation of both load and wind power across regions. The obtained series can be easily introduced into the expansion planning problem and then solved through existing MIP solvers. Simulation results show that the proposed planning model and series generation method can improve the expansion result significantly through modeling more detailed information of wind and load variation among regions in the US EI system. Moreover, the improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare in large-scale power grids.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1237158

Alternate ID(s):: OSTI ID: 1359093

Journal Information:: Electric Power Systems Research, Vol. 133; ISSN 0378-7796

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 47 works

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