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Multi-objective design optimization of distributed energy systems through cost and exergy assessments

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  • Di Somma, M.
  • Yan, B.
  • Bianco, N.
  • Graditi, G.
  • Luh, P.B.
  • Mongibello, L.
  • Naso, V.

Abstract

In recent years, distributed energy systems (DESs) have been recognized as a promising option for sustainable development of future energy systems, and their application has increased rapidly with supportive policies and financial incentives. With growing concerns on global warming and depletion of fossil fuels, design optimization of DESs through economic assessments for short-run benefits only is not sufficient, while application of exergy principles can improve the efficiency in energy resource use for long-run sustainability of energy supply. The innovation of this paper is to investigate exergy in DES design to attain rational use of energy resources including renewables by considering energy qualities of supply and demand. By using low-temperature sources for low-quality thermal demand, the waste of high-quality energy can be reduced, and the overall exergy efficiency can be increased. The goal of the design optimization problem is to determine types, numbers and sizes of energy devices in DESs to reduce the total annual cost and increase the overall exergy efficiency. Based on a pre-established DES superstructure with multiple energy devices such as combined heat and power and PV, a multi-objective linear problem is formulated. In modeling of energy devices, the novelty is that the entire available size ranges and the variation of their efficiencies, capital and operation and maintenance costs with sizes are considered. The operation of energy devices is modeled based on previous work on DES operation optimization. By minimizing a weighted sum of the total annual cost and primary exergy input, the problem is solved by branch-and-cut. Numerical results show that the Pareto frontier provides good balancing solutions for planners based on economic and sustainability priorities. The total annual cost and primary exergy input of DESs with optimized configurations are reduced by 21–36% as compared with conventional energy supply systems, where grid power is used for the electricity demand, and gas-fired boilers and electric chillers fed by grid power for thermal demand. A sensitivity analysis is also carried out to analyze the influence of energy prices and energy demand variation on the optimized DES configurations.

Suggested Citation

  • Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    • Handle: RePEc:eee:appene:v:204:y:2017:i:c:p:1299-1316
    DOI: 10.1016/j.apenergy.2017.03.105
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    References listed on IDEAS

    as
    1. Dincer, Ibrahim & Rosen, Marc A., 1999. "Energy, environment and sustainable development," Applied Energy, Elsevier, vol. 64(1-4), pages 427-440, September.
    2. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    3. Chinese, Damiana & Meneghetti, Antonella, 2005. "Optimisation models for decision support in the development of biomass-based industrial district-heating networks in Italy," Applied Energy, Elsevier, vol. 82(3), pages 228-254, November.
    4. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    5. Kalogirou, Soteris A. & Karellas, Sotirios & Badescu, Viorel & Braimakis, Konstantinos, 2016. "Exergy analysis on solar thermal systems: A better understanding of their sustainability," Renewable Energy, Elsevier, vol. 85(C), pages 1328-1333.
    6. Rosen, Marc A. & Dincer, Ibrahim & Kanoglu, Mehmet, 2008. "Role of exergy in increasing efficiency and sustainability and reducing environmental impact," Energy Policy, Elsevier, vol. 36(1), pages 128-137, January.
    7. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    8. Torío, H. & Schmidt, D., 2010. "Framework for analysis of solar energy systems in the built environment from an exergy perspective," Renewable Energy, Elsevier, vol. 35(12), pages 2689-2697.
    9. Bilgen, E, 2000. "Exergetic and engineering analyses of gas turbine based cogeneration systems," Energy, Elsevier, vol. 25(12), pages 1215-1229.
    10. Pepermans, G. & Driesen, J. & Haeseldonckx, D. & Belmans, R. & D'haeseleer, W., 2005. "Distributed generation: definition, benefits and issues," Energy Policy, Elsevier, vol. 33(6), pages 787-798, April.
    11. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    12. Mongibello, Luigi & Bianco, Nicola & Caliano, Martina & Graditi, Giorgio, 2015. "Influence of heat dumping on the operation of residential micro-CHP systems," Applied Energy, Elsevier, vol. 160(C), pages 206-220.
    13. Barelli, L. & Bidini, G. & Gallorini, F. & Ottaviano, A., 2011. "An energetic–exergetic analysis of a residential CHP system based on PEM fuel cell," Applied Energy, Elsevier, vol. 88(12), pages 4334-4342.
    14. Pohekar, S. D. & Ramachandran, M., 2004. "Application of multi-criteria decision making to sustainable energy planning--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(4), pages 365-381, August.
    15. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    16. Ruan, Yingjun & Liu, Qingrong & Zhou, Weiguo & Firestone, Ryan & Gao, Weijun & Watanabe, Toshiyuki, 2009. "Optimal option of distributed generation technologies for various commercial buildings," Applied Energy, Elsevier, vol. 86(9), pages 1641-1653, September.
    17. 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.
    18. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    19. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    20. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    21. Koca, Ahmet & Oztop, Hakan F. & Koyun, Tansel & Varol, Yasin, 2008. "Energy and exergy analysis of a latent heat storage system with phase change material for a solar collector," Renewable Energy, Elsevier, vol. 33(4), pages 567-574.
    22. Barbieri, Enrico Saverio & Melino, Francesco & Morini, Mirko, 2012. "Influence of the thermal energy storage on the profitability of micro-CHP systems for residential building applications," Applied Energy, Elsevier, vol. 97(C), pages 714-722.
    23. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    24. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    25. 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.
    26. Bayod-Rújula, Angel A., 2009. "Future development of the electricity systems with distributed generation," Energy, Elsevier, vol. 34(3), pages 377-383.
    27. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
    28. Buoro, D. & Casisi, M. & De Nardi, A. & Pinamonti, P. & Reini, M., 2013. "Multicriteria optimization of a distributed energy supply system for an industrial area," Energy, Elsevier, vol. 58(C), pages 128-137.
    29. Michel Feidt & Monica Costea, 2012. "Energy and Exergy Analysis and Optimization of Combined Heat and Power Systems. Comparison of Various Systems," Energies, MDPI, vol. 5(9), pages 1-22, September.
    30. Bianchi, Michele & De Pascale, Andrea & Spina, Pier Ruggero, 2012. "Guidelines for residential micro-CHP systems design," Applied Energy, Elsevier, vol. 97(C), pages 673-685.
    31. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    32. Hepbasli, Arif, 2008. "A key review on exergetic analysis and assessment of renewable energy resources for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(3), pages 593-661, April.
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