Title :
Low-cost, short-term electric load prediction using the α-β-γfilter
Author :
Stanciu, I.R. ; Sorandaru, C.
Author_Institution :
Fac. of Mech. Eng., Politeh. Univ. of Timisoara, Timisoara, Romania
Abstract :
As the society evolves and the population grows, the demand for electrical energy increases. Search for new energy resources, increase the efficiency of the existing power plants, and cost minimization are actions to be taken. One way to reduce the cost is predicting the need for electricity. This problem is not new. This paper presents a low-cost method for short-term electric load prediction. After studying his stability, the algorithm is implemented in LabVIEW and a week of power data is used to test it and assess its performance.
Keywords :
energy resources; load forecasting; power engineering computing; power filters; power generation economics; power plants; stability; virtual instrumentation; LabVIEW; Low-cost short-term electric load prediction; a-β-γ filter; cost minimization; electrical energy demand; energy resources; power plants; stability; Electricity; Equations; Estimation; Filtering algorithms; Genetic algorithms; Load modeling; Power generation;
Conference_Titel :
Intelligent Engineering Systems (INES), 2011 15th IEEE International Conference on
Conference_Location :
Poprad
Print_ISBN :
978-1-4244-8954-1
DOI :
10.1109/INES.2011.5954769