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

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  • Piechocki, Janusz
  • Ambroziak, Dominik
  • Palkowski, Aleksander
  • Redlarski, Grzegorz

Abstract

In the face of increasingly stringent pollutant emission regulations, designing an agricultural holding becomes a difficult challenge of connecting a large number of coefficients that describe an energy system of a farm in regard to its ecological and economic efficiency. One way to cope with this issue is to design an energy self-sufficient farm that integrates various technologies, including renewable energy. However, the selection of appropriate components of such a system may be difficult. Large selection of facilities for management of heating and water systems and the choice of appropriate building technology makes it difficult to solve the problem of optimizing characteristics of such a holding by using standard methods. In this paper the issue of computer-aided design of energy systems for farms is dealt with. The solution proposed use the Modified Cuckoo Search algorithm in the process of optimizing the selection of particular components that influence performance of the power system, such as energy sources, water preparation systems or structure of walls. Presented results of the optimization process with the use of different fitness functions allow to state that the system developed achieved very satisfactory results and is capable to cope with the task. Through the use of the swarm algorithm it is possible to search for solutions in a large feature space and achieve optimality in terms of energy, economy and pollutant emission simultaneously.

Suggested Citation

  • Piechocki, Janusz & Ambroziak, Dominik & Palkowski, Aleksander & Redlarski, Grzegorz, 2014. "Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms," Applied Energy, Elsevier, vol. 114(C), pages 901-908.
  • Handle: RePEc:eee:appene:v:114:y:2014:i:c:p:901-908
    DOI: 10.1016/j.apenergy.2013.07.057
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    1. Radhi, H., 2010. "On the optimal selection of wall cladding system to reduce direct and indirect CO2 emissions," Energy, Elsevier, vol. 35(3), pages 1412-1424.
    2. Al-Mayyahi, Mohmmad A. & Hoadley, Andrew F.A. & Rangaiah, G.P., 2013. "A novel graphical approach to target CO2 emissions for energy resource planning and utility system optimization," Applied Energy, Elsevier, vol. 104(C), pages 783-790.
    3. Sandberg, Johan & Larsson, Mikael & Wang, Chuan & Dahl, Jan & Lundgren, Joakim, 2012. "A new optimal solution space based method for increased resolution in energy system optimisation," Applied Energy, Elsevier, vol. 92(C), pages 583-592.
    4. Yao, Jian, 2012. "Energy optimization of building design for different housing units in apartment buildings," Applied Energy, Elsevier, vol. 94(C), pages 330-337.
    5. Regnier, Eva, 2007. "Oil and energy price volatility," Energy Economics, Elsevier, vol. 29(3), pages 405-427, May.
    6. Walton, S. & Hassan, O. & Morgan, K. & Brown, M.R., 2011. "Modified cuckoo search: A new gradient free optimisation algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 44(9), pages 710-718.
    7. Ganesan, T. & Elamvazuthi, I. & Ku Shaari, Ku Zilati & Vasant, P., 2013. "Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production," Applied Energy, Elsevier, vol. 103(C), pages 368-374.
    8. Kuprianov, Vladimir I., 2005. "Applications of a cost-based method of excess air optimization for the improvement of thermal efficiency and environmental performance of steam boilers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(5), pages 474-498, October.
    9. Tsai, Ming-Tang & Yen, Chih-Wei, 2011. "The influence of carbon dioxide trading scheme on economic dispatch of generators," Applied Energy, Elsevier, vol. 88(12), pages 4811-4816.
    10. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    11. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    12. Diakaki, Christina & Grigoroudis, Evangelos & Kabelis, Nikos & Kolokotsa, Dionyssia & Kalaitzakis, Kostas & Stavrakakis, George, 2010. "A multi-objective decision model for the improvement of energy efficiency in buildings," Energy, Elsevier, vol. 35(12), pages 5483-5496.
    13. Bentley, R.W. & Mannan, S.A. & Wheeler, S.J., 2007. "Assessing the date of the global oil peak: The need to use 2P reserves," Energy Policy, Elsevier, vol. 35(12), pages 6364-6382, December.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Taslimi-Renani, Ehsan & Modiri-Delshad, Mostafa & Elias, Mohamad Fathi Mohamad & Rahim, Nasrudin Abd., 2016. "Development of an enhanced parametric model for wind turbine power curve," Applied Energy, Elsevier, vol. 177(C), pages 544-552.
    3. Nesamalar, J. Jeslin Drusila & Venkatesh, P. & Raja, S. Charles, 2016. "Energy management by generator rescheduling in congestive deregulated power system," Applied Energy, Elsevier, vol. 171(C), pages 357-371.
    4. Baklacioglu, Tolga & Turan, Onder & Aydin, Hakan, 2015. "Dynamic modeling of exergy efficiency of turboprop engine components using hybrid genetic algorithm-artificial neural networks," Energy, Elsevier, vol. 86(C), pages 709-721.
    5. Coelho, Leandro dos Santos & Klein, Carlos Eduardo & Sabat, Samrat L. & Mariani, Viviana Cocco, 2014. "Optimal chiller loading for energy conservation using a new differential cuckoo search approach," Energy, Elsevier, vol. 75(C), pages 237-243.

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