Analysis of the value for unit commitment of improved load forecasts Export

@article{citeulike:712146, abstract = {Load forecast errors can yield suboptimal unit commitment decisions. The economic cost of inaccurate forecasts is assessed by a combination of forecast simulation, unit commitment optimization, and economic dispatch modeling for several different generation/load systems. The forecast simulation preserves the error distributions and correlations actually experienced by users of a neural net-based forecasting system. Underforecasts result in purchases of expensive peaking or spot market power; overforecasts inflate start-up and fixed costs because too much capacity is committed. The value of improved accuracy is found to depend on load and generator characteristics; for the systems considered here, a reduction of 1\% in mean absolute percentage error (MAPE) decreases variable generation costs by approximately 0.1\%-0.3\% when MAPE is in the range of 3\%-5\%. These values are broadly consistent with the results of a survey of 19 utilities, using estimates obtained by simpler methods. A conservative estimate is that a 1\% reduction in forecasting error for a 10,000 MW utility can save up to \$1.6 million annually}, author = {Hobbs, B. F. and Jitprapaikulsarn, S. and Konda, S. and Chankong, V. and Loparo, K. A. and Maratukulam, D. J.}, citeulike-article-id = {712146}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=801894}, journal = {Power Systems, IEEE Transactions on}, keywords = {energy, load-forecasting, unit-commitment}, number = {4}, pages = {1342--1348}, posted-at = {2006-06-27 13:40:52}, priority = {2}, title = {Analysis of the value for unit commitment of improved load forecasts}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=801894}, volume = {14}, year = {1999} }

TY - JOUR ID - citeulike:712146 L3 - citeulike-article-id:712146 N2 - Load forecast errors can yield suboptimal unit commitment decisions. The economic cost of inaccurate forecasts is assessed by a combination of forecast simulation, unit commitment optimization, and economic dispatch modeling for several different generation/load systems. The forecast simulation preserves the error distributions and correlations actually experienced by users of a neural net-based forecasting system. Underforecasts result in purchases of expensive peaking or spot market power; overforecasts inflate start-up and fixed costs because too much capacity is committed. The value of improved accuracy is found to depend on load and generator characteristics; for the systems considered here, a reduction of 1% in mean absolute percentage error (MAPE) decreases variable generation costs by approximately 0.1%-0.3% when MAPE is in the range of 3%-5%. These values are broadly consistent with the results of a survey of 19 utilities, using estimates obtained by simpler methods. A conservative estimate is that a 1% reduction in forecasting error for a 10,000 MW utility can save up to $1.6 million annually IS - 4 JF - Power Systems, IEEE Transactions on EP - 1348 TI - Analysis of the value for unit commitment of improved load forecasts VL - 14 SP - 1342 KW - energy KW - load-forecasting KW - unit-commitment AU - Hobbs, BF AU - Jitprapaikulsarn, S AU - Konda, S AU - Chankong, V AU - Loparo, KA AU - Maratukulam, DJ PY - 1999/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=801894 ER -