COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR MAXIMUM ENERGY EFFICIENCY OF AN INTERNAL COMBUSTION ENGINE AND A STEAM TURBINE OF A COGENERATION PROCESS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SEIJO FERNANDEZ SANDRA; DEL CAMPO I.; ECHANOBE J.; GARCIA SEDANO J.; SUSO E.; ARBIZU E.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING Year:2014 | Volume:5 | Issue:2 Page(s): 1-10

Download Full-Text

View:

273

Download:

119

Cites:

Information Journal Paper

Title

COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR MAXIMUM ENERGY EFFICIENCY OF AN INTERNAL COMBUSTION ENGINE AND A STEAM TURBINE OF A COGENERATION PROCESS

Author(s)

Keywords

COMPUTATIONAL INTELLIGENCE

NEURO-FUZZY

NEURAL NETWORK

COGENERATION PLANT

EFFICIENCY

OPTIMIZATION

MODELIZATION

Abstract

This paper discusses the development of a model of a real COGENERATION PLANT based on COMPUTATIONAL INTELLIGENCE (CI) algorithms. In particular, two CI strategies are used: one based on artificial NEURAL NETWORK and the other one based on a NEURO-FUZZY system. Both systems are trained with a data collection from the COGENERATION PLANT.Data mining techniques are applied to remove erroneous and redundant data, and also to obtain information about the variables and its behaviour. This task allows to select only the relevant information and is also a way to decrease the complexity of the model. In this first approach on the work, two separate subsystems of the cogeneration process are considered: an engine and a steam turbine. The obtained models are used to analyze the role of each involved variable and to derive a set of recommendations (i.e., changes in some of the input variables) to optimize the performance of the system. The recommendations applied to the models improve the behaviour of the plant providing higher energy production with a lower cost.

Cites

No record.

References

No record.

Cite

APA: Copy

SEIJO FERNANDEZ, SANDRA, DEL CAMPO, I., ECHANOBE, J., GARCIA SEDANO, J., SUSO, E., & ARBIZU, E.. (2014). COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR MAXIMUM ENERGY EFFICIENCY OF AN INTERNAL COMBUSTION ENGINE AND A STEAM TURBINE OF A COGENERATION PROCESS. INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING, 5(2), 1-10. SID. https://sid.ir/paper/327082/en

Vancouver: Copy

SEIJO FERNANDEZ SANDRA, DEL CAMPO I., ECHANOBE J., GARCIA SEDANO J., SUSO E., ARBIZU E.. COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR MAXIMUM ENERGY EFFICIENCY OF AN INTERNAL COMBUSTION ENGINE AND A STEAM TURBINE OF A COGENERATION PROCESS. INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING[Internet]. 2014;5(2):1-10. Available from: https://sid.ir/paper/327082/en

IEEE: Copy

SANDRA SEIJO FERNANDEZ, I. DEL CAMPO, J. ECHANOBE, J. GARCIA SEDANO, E. SUSO, and E. ARBIZU, “COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR MAXIMUM ENERGY EFFICIENCY OF AN INTERNAL COMBUSTION ENGINE AND A STEAM TURBINE OF A COGENERATION PROCESS,” INTERNATIONAL JOURNAL OF ENERGY AND ENVIRONMENTAL ENGINEERING, vol. 5, no. 2, pp. 1–10, 2014, [Online]. Available: https://sid.ir/paper/327082/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops