Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms

Applied Energy

Volumn 114, Issue , 2014, Pages 901-908

  Piechocki, Janusz ^a   Ambroziak, Dominik ^b   Palkowski, Aleksander ^b   Redlarski, Grzegorz ^b  

^a UNIVERSITY OF WARMIA AND MAZURY IN OLSZTYN   (Poland)

^b GDANSK UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Energy efficiency; Environmental impact; Integrated power systems; Modified Cuckoo Search; Power system optimization; Swarm optimization

Indexed keywords

COMPUTER AIDED DESIGN; ENERGY EFFICIENCY; ENVIRONMENTAL IMPACT; LEARNING ALGORITHMS; POLLUTION;

BUILDING TECHNOLOGIES; CUCKOO SEARCH ALGORITHMS; CUCKOO SEARCHES; ECOLOGICAL AND ECONOMIC; INTEGRATED POWER SYSTEMS; POWER SYSTEM OPTIMIZATION; SWARM OPTIMIZATION; VARIOUS TECHNOLOGIES;

OPTIMIZATION;

ALGORITHM; ENERGY EFFICIENCY; ENVIRONMENTAL IMPACT; FARM; OPTIMIZATION; RENEWABLE RESOURCE; SELF SUFFICIENCY; STANDARD (REGULATION);

EID: 84888838958     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.07.057     Document Type: Article

References (39)

1. European union commission. Agricultural labour input. Internet; 2013.
2. European union commission. EU 2012 Budget: for 500 million Europeans, for growth and employment. Internet; 2013.
3. Regnier E. Oil and energy price volatility. Energy Econom 2007, 29:405-427.
4. Bentley R., Mannan S., Wheeler S. Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 2007, 35:6364-6382.
5. Ren H., Zhou W., Nakagami K., Gao W., Wu Q. Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects. Appl Energy 2010, 87:3642-3651.
6. Sandberg J., Larsson M., Wang C., Dahl J., Lundgren J. A new optimal solution space based method for increased resolution in energy system optimisation. Appl Energy 2012, 92:583-592.
7. Zhou Z., Zhang J., Liu P., Li Z., Georgiadis M.C., Pistikopoulos E.N. A two-stage stochastic programming model for the optimal design of distributed energy systems. Appl Energy 2013, 103:135-144.
8. Wang W., Zmeureanu R., Rivard H. Applying multi-objective genetic algorithms in green building design optimization. Build Environ 2005, 40:1512-1525.
9. Wright J.A., Loosemore H.A., Farmani R. Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy Build 2002, 34:959-972.
10. Lozano M.A., Ramos J.C., Carvalho M., Serra L.M. Structure optimization of energy supply systems in tertiary sector buildings. Energy Build 2009, 41:1063-1075.
11. Yao J. Energy optimization of building design for different housing units in apartment buildings. Appl Energy 2012, 94:330-337.
12. 2 emissions for energy resource planning and utility system optimization. Appl Energy 2013, 104:783-790.
13. 2 emissions. Energy 2010, 35:1412-1424.
14. Diakaki C., Grigoroudis E., Kolokotsa D. Towards a multi-objective optimization approach for improving energy efficiency in buildings. Energy Build 2008, 40:1747-1754.
15. Diakaki C., Grigoroudis E., Kabelis N., Kolokotsa D., Kalaitzakis K., Stavrakakis G. A multi-objective decision model for the improvement of energy efficiency in buildings. Energy 2010, 35:5483-5496.
16. Griego D., Krarti M., Hernndez-Guerrero A. Optimization of energy efficiency and thermal comfort measures for residential buildings in Salamanca, Mexico. Energy Build 2012, 54:540-549.
17. Kuprianov V.I. Applications of a cost-based method of excess air optimization for the improvement of thermal efficiency and environmental performance of steam boilers. Renew Sust Energy Rev 2005, 9:474-498.
18. 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, vol. 52; 2009. p. 16-62.
19. 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 vol. 52; 2009. p. 63-87.
20. 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 vol. 52; 2009. p. 114-35.
21. The president of Poland, Protokol z Kioto do Ramowej konwencji Narodow Zjednoczonych w sprawie zmian klimatu; 1997. Dz. U. 05.203.1684. Polish.
22. Yang X-S. Cuckoo Search via Lévy flights. In: 2009 World congress on nature and biologically inspired computing (NaBIC). IEEE; 2009. p. 210-4.
23. Walton S., Hassan O., Morgan K., Brown M. Modified cuckoo search: a new gradient free optimisation algorithm. Chaos Solitons Fract 2011, 44:710-718.
24. Wang L., Singh C. Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm. Electr Power Syst Res 2007, 77:1654-1664.
25. Ganesan T., Elamvazuthi I., Shaari K.Z.K., Vasant P. Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production. Appl Energy 2013, 103:368-374.
26. Tsai M.-T., Yen C.-W. The influence of carbon dioxide trading scheme on economic dispatch of generators. Appl Energy 2011, 88:4811-4816.
27. Brigatto G, Carmargo C, Sica E. Multiobjective optimization of distributed generation portfolio insertion strategies. In: Transmission and distribution conference and exposition: Latin America (T D-LA); 2010 IEEE/PES. p. 622-8.
28. Redlarski G., Wojdalski J., Kupczyk A., Piechocki J. Efficiency of biomass energy used for heating purposes in a residential building in comparison with other energy sources. TEKA Comm Motoriza Power Ind Agric 2012, 12:211-218.
29. Polish committee for standardization, heating systems in buildings. Method for calculation of the design heat load PN-EN 12831:2006; 2006.
30. Polish committee for standardization, building components and building elements. Thermal resistance and thermal transmittance. Calculation method PN-EN ISO 6946:2008; 2008.
31. Polish committee for standardization, building components and building elements. Thermal resistance and thermal transmittance. Calculation method PN-EN ISO 6946:1996; 1996.
32. Ministry of environmental protection, natural resources and forestry. Wskaznik emisji substancji zanieczyszczajacych wprowadzanych do powietrza z procesow energetycznego spalania pzoa/1159/96; 1996 [in Polish].
33. Redlarski G., Piechocki J., Dabkowski M. Reducing air pollutant emissions from the residential sector by switching to alternative energy sources in single-family homes. Pol J Environ Stud 2013, 22:197-203.
34. Polish ministry of infrastructure. W sprawie metodologii obliczania charakterystyki energetycznej budynku i lokalu mieszkalnego lub czesci budynku stanowiacej samodzielna calosc techniczno-uzytkowa oraz sposobu sporzadzania i wzorow swiadectw ich charakterystyki energetycznej. Internet; 2013, [in Polish].
35. Tuba M., Subotic M., Stanarevic N. Modified cuckoo search algorithm for unconstrained optimization problems. European computing conference (ECC 11) 2011, 263-268. WSEAS Press, Paris (France).
36. Yang X.-S., Deb S. Engineering optimisation by cuckoo search. Int J Math Modell Numer Optim 2010, 1:330-343.
37. Yang X.-S., Deb S. Cuckoo search: recent advances and applications. Neural Comput Appl 2013, 1-6.
38. Gandomi A.H., Yang X.-S., Alavi A.H. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 2011, 29:17-35.
39. Civicioglu P., Besdok E. A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Artif Intell Rev 2013, 39:315-346.