A preliminary Markov chain Monte Carlo (MCMC) calibration algorithm is presented for
estimating the demand pattern multipliers of a distribution system network model utilizing
tracer test data. A simple 35 node distribution system network is used to generate a synthetic
tracer study data set over a 55-hour simulation time. The MCMC calibration algorithm is
able to reproduce the 55-hour demand pattern multipliers from an initial guess absent of any
temporal information. This preliminary study for the MCMC calibration algorithm provides
the basis for extending the capabilities to include spatial correlation of user demands. Includes 5 references, figures.
| Edition : | Vol. - No. |
| File Size : | 1
file
, 440 KB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 10 |
| Published : | 11/15/2004 |
