Temperature Curvature Where a Power-Output Search Would Concentrate
Abstract
The question concerns temperature curvature and humidity interaction in power output. The secondary ordinary least squares analysis contains 9,568 observations and uses HC3 covariance. The coefficient on AT is -2.7387, with a 95 percent interval from -2.8910 to -2.5864. Curvature and an interaction examine whether a constant temperature slope is an adequate description. These terms are fitted to the released records rather than chosen by a search for the most favorable output. A later optimizer could exploit local model error, so partition or threshold search would require independent checks at its selected extreme. The estimates describe the released collection and its conditioning set. No new data collection, simulator experiment, or deployment-policy evaluation is claimed.
References
S. Gao, L. Shi, and Z. Zhang, “A Peak-Over-Threshold Search Method for Global Optimization,” Automatica, vol. 89, pp. 83–91, 2018.
W. Chen, S. Gao, C.-H. Chen, and L. Shi, “An Optimal Sample Allocation Strategy for Partition-Based Random Search,” IEEE Transactions on Automation Science and Engineering, vol. 11, pp. 177–186, 2014.
Pnar Tfekci, Heysem Kaya. Combined Cycle Power Plant. UCI Machine Learning Repository, 2014. Dataset. https://doi.org/10.24432/C5002N.
White, Halbert. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, no. 4, 1980, pp. 817–838. https://doi.org/10.2307/1912934.
Cameron, A. Colin, and Douglas L. Miller. “A Practitioner’s Guide to Cluster-Robust Inference.” Journal of Human Resources, vol. 50, no. 2, 2015, pp. 317–372. https://doi.org/10.3368/jhr.50.2.317.
Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, 2006. https://gaussianprocess.org/gpml/.
Ankenman, Bruce, Barry L. Nelson, and Jeremy Staum. “Stochastic Kriging for Simulation Metamodeling.” Operations Research, vol. 58, no. 2, 2010, pp. 371–382. https://doi.org/10.1287/opre.1090.0754.
Kim, Seong-Hee, and Barry L. Nelson. “A Fully Sequential Procedure for Indifference-Zone Selection in Simulation.” ACM Transactions on Modeling and Computer Simulation, vol. 11, no. 3, 2001, pp. 251–273. https://doi.org/10.1145/502109.502111.
Frazier, Peter I., Warren B. Powell, and Savas Dayanik. “A Knowledge-Gradient Policy for Sequential Information Collection.” SIAM Journal on Control and Optimization, vol. 47, no. 5, 2008, pp. 2410–2439. https://doi.org/10.1137/070693424.
Bertsimas, Dimitris, and Melvyn Sim. “The Price of Robustness.” Operations Research, vol. 52, no. 1, 2004, pp. 35–53. https://doi.org/10.1287/opre.1030.0065.