Title :
An “load forecasting - dispatching” integration system for multiple boilers in thermal power plants
Author :
Yu, Chen-Long ; Lu, Yong-Zai ; Chu, Jian
Author_Institution :
Res. Inst. of Cyber-Syst. & Control, Zhejiang Univ., Hangzhou, China
Abstract :
An improved integration system of multiple utility boilers is proposed in this study. Short-term load demand forecasting and load dispatching for multiple boilers are the two function blocks, they are modeled with Artificial Neural Network (ANN) and Multi-objective Optimization Problem (MOP) respectively. In particular, the MOP is solved by a novel hybrid multi-objective optimization algorithm with a combination of Particle Swarm Optimization (PSO) and Extremal Optimization (EO) solutions, called “PSO-EO-MO”. Both the two function blocks have been developed to a integration system software based on real production data from a thermal power plant and have being running online on the spot with the procedure of production. The results illustrate the efficiency and applicability of the software and the software has got Software Copyright in 2010.
Keywords :
boilers; demand forecasting; load dispatching; neural nets; particle swarm optimisation; power engineering computing; thermal power stations; artificial neural network; extremal optimization solutions; hybrid multiobjective optimization; integration system software; load dispatching; multiobjective optimization problem; multiple utility boilers; particle swarm optimization; short-term load demand forecasting; software copyright; thermal power plants; Boilers; Dispatching; Energy consumption; Forecasting; Heuristic algorithms; Load modeling; Software; EO; Load Forecasting; Load dispatching; MOP; PSO;
Conference_Titel :
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9691-4
DOI :
10.1109/PEAM.2011.6135003
