Title :
Fast Sensitivity Analysis Approach to Assessing Congestion Induced Wind Curtailment
Author :
Yingzhong Gu ; Le Xie
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
Although the installed wind generation capacity has grown remarkably over the past decades, percentage of wind energy in electricity supply portfolio is still relatively low. Due to the technical limitations of power system operations, considerable wind generation cannot integrate into the grid but gets curtailed. Among various factors, transmission congestion accounts for a significant portion of wind curtailment. Derived from DC power network, an analytical approach is proposed to efficiently assess the congestion induced wind curtailment sensitivity without iterative simulation. Compared to empirical simulation-based wind curtailment studies, the proposed approach offers the following advantages: 1) computational efficiency, 2) low input information requirement, and 3) robustness against uncertainties. This approach could benefit system operators, wind farm owners as well as wind power investors to better understand the interactions between wind curtailment and power system operations and can further help for curtailment alleviation. Numerical experiments of a modified IEEE 24-bus Reliability Test System (RTS) as well as a practical 5889-bus system are conducted to verify the effectiveness and robustness of the proposed approach.
Keywords :
investment; power generation economics; power generation reliability; sensitivity analysis; wind power plants; DC power network; RTS; analytical approach; congestion induced wind curtailment assessment; electricity supply portfolio; fast sensitivity analysis approach; modified IEEE 24-bus reliability test system; power system operations; transmission congestion; wind energy; wind farm; wind generation capacity; Equations; Power system stability; Sensitivity analysis; Thermal stability; Wind; Wind power generation; Integration of renewable energy; sensitivity analysis; transmission congestion; wind generation curtailment;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2013.2282286