| Author | Lee, Yean-shin |
| Call Number | AIT Thesis no.CS-95-12 |
| Subject(s) | Electric power-plants--Taiwan--Tainan--Load
|
| Note | A thesis submitted in partial fulfillment of the requirement for the degree of Master of Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | Although considerable work has been done in the past on the application of some type of
systematic approach to electric power forecasting, its application to distribution load forecasting
has unfortunately been somewhat neglected, especially the short-term distribution load forecasting
for only certain areas like Taiwan Power Company (TPC) Tainan District.
Recently years, due to the uprising of environmental protection consciousness, the land
acquisition of not only power plants but also secondary substations becomes more difficult than
before. Most Districts of TPC will face the embarrassment of power shortage and area rationing of
power commodity predictably will be seen more often. In these circumstances, reliable short-term
distribution load forecasting tools will enable TPC to plan ahead of time for peak demand and
inform their customers as earlier as possible when area rationing is inevitable.
Three forecasting approaches namely Neural Network, Box-Jenkins and Winters were
investigated through the study cin distribution daily peak load and weekly peak load forecasting for
TPC in Tainan District. The results showed that the daily peak load forecasting performance by
Box-Jenkins model along with standardization method is the best among the approaches
considered. For weekly peak load data the Winters' method gives the best forecasting performance
with lead times from one to three weeks.
For daily peak load data, the accuracy of forecasting with Box-Jenkins seasonal models is
much better than that of non-seasonal models. Moreover, with standardized daily peak load data
the forecasting performance is improved significantly.
The Backpropagation Networks can not give a good forecasting performance when only
time series data are used. |
| Year | 1995 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Huynh, Ngoc Phien; |
| Examination Committee(s) | Do, Ba Khang;Nagarur, Nagendra N.; |
| Scholarship Donor(s) | R.O.C. Government; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 1995 |