Swarm-assisted investment planning of a bioethanol plant

• Autorzy: Redlarski G. , Krawczuk M. , Kupczyk A. , Piechocki J. , Ambroziak D. , Palkowski A.
• Języki publikacji: EN

Abstrakty

EN

Bioethanol is a liquid fuel for which a significant increase in the share of energy sources has been observed in the economies of many countries. The most significant factor in popularizing bioethanol is the profitability of investments in construction of facilities producing this energy source, as well as the profitability of its supply chain. With the market filled with a large amount of equipment used in the bioethanol production process, it is often difficult to make an optimal decision regarding the investment. Another issue is the location of the plant itself. Economic benefits are strongly associated with costs of equipment and materials, the amount of revenue from sales, and transportation costs. This article presents an attempt to solve this problem by using several swarm algorithms – new and fast-growing optimisation techniques. By employing ant colony optimization, river formation dynamics, particle swarm optimization, and cuckoo search algorithms in the task of bioethanol plant investment planning, the overall suitability of this type of technique has been tested. Moreover, the results allow us to determine which of the preceding algorithms is the most efficient in the given task.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 3
• Opis fizyczny: p.1203-1214,fig.,ref.

Twórcy

autor

Redlarski G.

• Department of Mechatronics and High-Voltage Engineering, Gdansk University of Technology, G. Narutowicza 11/12, 80-233 Gdansk, Poland

autor

Krawczuk M.

• Department of Production Management and Engineering, Warsaw University of Life Sciences, Nowoursynowska 164, 02-787 Warsaw, Poland

autor

Kupczyk A.

• Department of Production Management and Engineering, Warsaw University of Life Sciences, Nowoursynowska 164, 02-787 Warsaw, Poland

autor

Piechocki J.

• Department of Electrical Engineering, Power Engineering, Electronics, and Control Engineering, University of Warmia and Mazury, M. Oczapowskiego 11, 10-719 Olsztyn, Poland

autor

Ambroziak D.

• Department of Mechatronics and High-Voltage Engineering, Gdansk University of Technology, G. Narutowicza 11/12, 80-233 Gdansk, Poland

autor

Palkowski A.

• Department of Mechatronics and High-Voltage Engineering, Gdansk University of Technology, G. Narutowicza 11/12, 80-233 Gdansk, Poland

Bibliografia

• 1. Baena L., Gomez M., Calderon J. Aggressiveness of a 20autoparts: I behavior of metallic materials and evaluation of their electrochemical properties. Fuel 95, 320, 2012.
• 2. Park S.H., Kim H.J., Suh H.K., Lee C.S. Atomization and spray characteristics of bioethanol and bioethanol blended gasoline fuel injected through a direct injection gasoline injector. International Journal of Heat and Fluid Flow 30, 1183, 2009.
• 3. Naik S., Goud V.V., Rout P.K., Dalai A.K. Production of first and second generation biofuels: A comprehensive review. Renewable and Sustainable Energy Reviews 14, 578, 2010.
• 4. Salazar-Ordonez M., Perez-Hernandez P.P., Martin-Lozano J.M. Sugar beet for bioethanol production: An approach based on environmental agricultural outputs. Energy Policy 55. Special section: Long Run Transitions to Sustainable Economic Structures in the European Union and Beyond, 662, 2013.
• 5. Goh C.S., Lee K.T. A visionary and conceptual macroalgae-based third-generation bioethanol (TGB) biorefinery in Sabah, Malaysia as an underlay for renewable and sustainable development. Renewable and Sustainable Energy Reviews 14, 842, 2010.
• 6. European Commission. Proposal for a Regulation of the European Parliament and of the Council on Support for Rural Development by the European Agricultural Fund for Rural Development (EAFRD). COM 627, Final/2, 2011.
• 7. The European parliament and the council of the European Union. Directive 2009/28/EC of the European parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing directives 2001/77/EC and 2003/30/EC. Official journal of the European Union 52, 16, 2009.
• 8. The European parliament and the council of the European Union. Directive 2009/29/EC of the European parliament and of the council of 23 April 2009 amending directive 2003/87/EC so as to improve and extend the greenhouse gas emission allowance trading scheme of the community. Official journal of the European Union 52, 63, 2009.
• 9. The European parliament and the council of the European Union. Directive 2009/31/EC of the European parliament and of the council of 23 April 2009 on the geological storage of carbon dioxide and amending council directive 85/337/EEC. European parliament and council directives 2000/60/EC, 2001/80/EC, 2004/35/EC, 2006/12/EC, 2008/1/EC and regulation (EC) No 1013/2006. Official journal of the European Union 52, 114-135, 2009.
• 10. Krajnc, D. & Glavic, P. Assessment of different strategies for the co-production of bioethanol and beet sugar. Chemical Engineering Research and Design 87. Special Issue on Biorefinery Integration Biorefinery Integration SI, 1217, 2009.
• 11. Redlarski G., Piechocki J., Dąbkowski M. Reducing Air Pollutant Emissions from the Residential Sector by Switching to Alternative Energy Sources in Single-Family Homes. Polish Journal of Environmental Studies 22, 197, 2013.
• 12. Vucurovic D.G., Dodic S.N., Popov S.D., Dodic J.M., Grahovac J.A. Process model and economic analysis of ethanol production from sugar beet raw juice as part of the cleaner production concept. Bioresource Technology 104, 367, 2012.
• 13. Fakharudin A.S., Sulaiman M.N., Salihon J., Zainol N. Implementing Artificial Neural Networks and Genetic Algorithms to Solve Modeling and Optimisation of Biogas Production in Proceedings of the 4th International Conference on Computing and Informatics, ICOCI 2013, 121, 2013.
• 14. Wolf C., McLoone S., Bongards M. Biogas plant optimization using genetic algorithms and particle swarm optimization in IET Irish Signals and Systems Conference (ISSC 2008) (Galway, Ireland), 244, 2008. DOI:10.1049/cp:20080670.
• 15. Wei X., Kusiak A. Optimization of Biogas Production Process in a Wastewater Treatment Plant in Proceedings of the 2012 Industrial and Systems Engineering Research Conference (Orlando, FL), 1, 2012.
• 16. Kocoloski M., GriFFIn W.M., Matthews H.S. Impacts of facility size and location decisions on ethanol production cost. Energy Policy 39, 47, 2011.
• 17. Celli G., Ghiani E., Loddo M., Pilo F., Pani S. Optimal location of biogas and biomass generation plants in Universities Power Engineering Conference, 2008. UPEC 2008. 43rd International, 1, 2008. DOI:10.1109/UPEC.2008.4651490.
• 18. Leduc S., Starfelt F., Dotzauer E., Kindermann G., McCallum I., Obersteiner M., Lundgren J. Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy 35, 2709, 2010.
• 19. Mas M.D., Giarola S., Zamboni A., Bezzo F. In 20th European Symposium on Computer Aided Process Engineering (Eds Pierucci S., Ferraris G.B.) 97, Elsevier, 2010. DOI:10.1016/S1570-7946(10)28017-3.
• 20. Zhang J., Osmani A., Awudu I., Gonela V. An integrated optimization model for switchgrass-based bioethanol supply chain. Applied Energy 102. Special Issue on Advances in sustainable biofuel production and use – XIX International Symposium on Alcohol Fuels – ISAF, 1205, 2013.
• 21. Osmani A., Zhang J. Economic and environmental optimization of a large scale sustainable dual feedstock lignocellulosic-based bioethanol supply chain in a stochastic environment. Applied Energy 114, 572, 2014.
• 22. Bai Y., Hwang T., Kang S., Ouyang Y. Biofuel refinery location and supply chain planning under trafc congestion. Transportation Research Part B: Methodological 45, 162. ISSN: 0191-2615, 2011.
• 23. Akgul O., Shah N., Papageorgiou L.G. Economic optimisation of a UK advanced biofuel supply chain. Biomass and Bioenergy 41, 57. ISSN: 0961-9534, 2012.
• 24. Balaman S.Y., Selim H. A decision model for cost efective design of biomass based green energy supply chains. Bioresource Technology 191, 97. ISSN: 0960-8524, 2015.
• 25. Samer M. A software program for planning and designing biogas plants. Transactions of the ASABE 53, 1277, 2010.
• 26. Karuppiah R., Peschel A., Grossmann I.E., Martin M., Martinson W., Zullo L. Energy optimization for the design of corn-based ethanol plants. AIChE Journal 54, 1499, 2008.
• 27. Kostin A., Guillen-Gosalbez G., Mele F., Bagajewicz M., Jimenez L. Design and planning of infrastructures for bioethanol and sugar production under demand uncertainty. Chemical Engineering Research and Design 90, 359, 2012.
• 28. Tong K., Gong J., Yue D., You F. Stochastic Programming Approach to Optimal Design and Operations of Integrated Hydrocarbon Biofuel and Petroleum Supply Chains. ACS Sustainable Chemistry & Engineering 2, 49, 2014.
• 29. Castillo-Villar K.K. Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future. Energies 7, 57. ISSN: 7640-7672, 2014.
• 30. Santek B., Gwehenberger G., Santek M.I., Narodoslawsky M., Horvat P. Evaluation of energy demand and the sustainability of different bioethanol production processes from sugar beet. Resources, Conservation and Recycling 54, 872, 2010.
• 31. Yang X.-S., Deb S., Fong S. In Networked Digital Technologies (Ed Fong, S.) 53–66 (Springer Berlin Heidelberg). ISBN: 978-3-642-22184-2. DOI:10.1007/978-3-642-22185-9_6, 2011.
• 32. Dorigo M., Birattari M., Stutzle T. Ant colony optimization. Computational Intelligence Magazine, IEEE 1, 28, 2006.
• 33. Prakash A., Tiwari M.K., Shankar R. Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm. Journal of Intelligent Manufacturing 19, 161. ISSN: 1572-8145, 2008.
• 34. Rabanal P., Rodriguez I., Rubio F. In Unconventional Computation (eds Akl S., Calude C., Dinneen M., Rozenberg G. & Wareham, H.) 163–177 (Springer Berlin Heidelberg). DOI:10.1007/978-3-540-73554-0_16, 2007.
• 35. Poli R., Kennedy J., Blackwell T. Particle swarm optimization. Swarm Intelligence 1, 33, 2007.
• 36. Wei X., Kusiak A. Optimization of Biogas Production Process in a Wastewater Treatment Plant in Industrial and Systems Engineering Research Conference, 1, 2012.
• 37. Yang X.-S., Deb S. Cuckoo Search via Lévy flights in Nature Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on (2009), 210–214. DOI:10.1109/NABIC.2009.5393690, 2009.
• 38. Yang X.-S., Deb S. Cuckoo search: recent advances and applications. Neural Computing and Applications 24, 169, 2014.
• 39. Piechocki J., Ambroziak D., Palkowski A., Redlarski G. Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-suffcient farms. Applied Energy 114, 901, 2014.

Identyfikatory

DOI

10.15244/pjoes/68151