Prediction of Critical Load Levels for AC Optimal Power Flow Dispatch Model
Critical Load Levels (CLLs) are load levels at which a new binding or non-binding constraint occurs. Successful prediction of CLLs is very useful for identifying congestion and price change patterns. This paper extends the existing work to completely solve the problem of predicting the Previous CLL and Next CLL around the present operating point for an AC Optimal Power Flow (ACOPF) framework. First, quadratic variation patterns of system statuses such as generator dispatches, line flows, and Lagrange multipliers associated with binding constraints with respect to load changes are revealed through a numerical study of polynomial curve-fitting. Second, in order to reduce the intensive computation with the quadratic curve-fitting approach in calculating the coefficients of the quadratic pattern, an algorithm based on three-point quadratic extrapolation is presented to get the coefficients. A heuristic algorithm is introduced to seek three load levels needed by the quadratic extrapolation approach. The proposed approach can predict not only the CLLs, but also the important changes in system statuses such as new congestion and congestion relief. The high efficiency and accuracy of the proposed approach is demonstrated on a PJM 5-bus system and the IEEE 118-bus system.
R. Bo et al., "Prediction of Critical Load Levels for AC Optimal Power Flow Dispatch Model," International Journal of Electrical Power and Energy Systems, vol. 42, no. 1, pp. 635-643, Elsevier, Nov 2012.
The definitive version is available at http://dx.doi.org/10.1016/j.ijepes.2012.04.035
Electrical and Computer Engineering
Keywords and Phrases
Congestion Prediction; Critical Load; Marginal Units; Optimal Power Flows; Power System Planning; AC Generator Motors; Acoustic Generators; Curve Fitting; Extrapolation; Forecasting; Heuristic Algorithms; Lagrange Multipliers; Polynomial Approximation; Electric Load Flow; Critical Load Level; Marginal Unit; Optimal Power Flow
International Standard Serial Number (ISSN)
Article - Journal
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