Difference between revisions of "Short-Term Energy Demand Forecasting"

From ISLAB/CAISR
(Created page with "{{StudentProjectTemplate |Summary=Forecasting the electricity consumption based on historical usage by using smart meter data |Keywords=load forecasting, demand response |Refe...")
 
 
Line 9: Line 9:
 
|Level=Master
 
|Level=Master
 
|Status=Open
 
|Status=Open
}}
+
}}  
 
The project is about evaluating different forecasting methods for short term electricity usage and implementing them. There are some available methods e.g. time series, frequency analysis, NN, etc. which student should investigate them and discuss about the most suitable forecasting model.
 
The project is about evaluating different forecasting methods for short term electricity usage and implementing them. There are some available methods e.g. time series, frequency analysis, NN, etc. which student should investigate them and discuss about the most suitable forecasting model.

Latest revision as of 19:12, 24 October 2016

Title Short-Term Energy Demand Forecasting
Summary Forecasting the electricity consumption based on historical usage by using smart meter data
Keywords load forecasting, demand response
TimeFrame
References Hong, Wei-Chiang. Intelligent Energy Demand Forecasting. Vol. 10. Springer, 2013.

Ghofrani, M., et al. "Smart meter based short-term load forecasting for residential customers." North American Power Symposium (NAPS), 2011. IEEE, 2011. http://www.sciencedirect.com/science/article/pii/S1877050914011053

Prerequisites Cooperating Intelligent Systems and Learning Systems courses
Author
Supervisor Anita Sant'Anna, Sławomir Nowaczyk, Hassan Mashad Nemati
Level Master
Status Open


The project is about evaluating different forecasting methods for short term electricity usage and implementing them. There are some available methods e.g. time series, frequency analysis, NN, etc. which student should investigate them and discuss about the most suitable forecasting model.