The extensive use of energy generation processes presents a severe challenge to the environment and makes indispensable to focus the research on the maximization of the energy efficiency and minimization of environmental impact like NOx and CO emissions. The proposed idea describes an approach, based on an artificial life environment, for on-line optimization of complex processes for energy production. Such approach is based on evolutionary control methodology that by emulating the mechanism of the biological evolution, composes the capability of elaborate models with the continuous learning. In order to work with MSWC (Municipal Solid Waste Combustion) it was necessary to improve the stability of the optimizer to obtain a good compromise between stability and reactivity. So a specific MSWI performance function has been properly defined in order to characterize quantitatively the current status of the process. The evolutionary control approach has been successfully tested on a MSWC simulator and subsequently installed on a real MWSC plant which produce electricity and heat for a small Italian town (Ferrara). The paper reports the first promising experimental tests on the real plant for optimization of energetic efficiency and pollutant emission reduction.
|Publication status||Published - 2005|
|Event||3rd International Conference on Computing, Communications and Control Technologies, CCCT 2005 - , United States|
Duration: 1 Jan 2005 → …
|Conference||3rd International Conference on Computing, Communications and Control Technologies, CCCT 2005|
|Period||1/1/05 → …|
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Control and Systems Engineering
Annunziato, M., Bertini, I., Pannicelli, A., & Pizzuti, S. (2005). Evolutionary control and on-line optimization of an MSWC energy process. Paper presented at 3rd International Conference on Computing, Communications and Control Technologies, CCCT 2005, United States.