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Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System

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  • Yifang Tang

    (School of Energy Science and Engineering, Central South University, Changsha 410083, China)

  • Zhiqiang Liu

    (School of Energy Science and Engineering, Central South University, Changsha 410083, China)

  • Lan Li

    (China Light Industry Wuhan Design & Engineering Co., Ltd., Wuhan 430060, China)

Abstract

The distributed energy system (DES) has increasingly attracted considerable attention from researchers due to its environmental friendliness and high efficiency. In the hot summer and cold winter areas, DES is an efficient alternative for district cooling and heating. A case study located in Changsha, China, which is a typical hot summer and cold winter area, is analyzed. Four control strategies are proposed in this study. The four cases under different control strategies are compared in terms of energy, economy, environment, solar fraction, and soil annual heat imbalance rate. Results show that the DES can be an energy saving and environmentally friendly alternative. The primary energy saving (PES) is more than 36.70% and can reach up to 48.04%, whereas DES can realize economical operation and reduce the emission of carbon dioxide, sulphur dioxide, and dust. In addition, DES consumes more electricity and less natural gas than the conventional energy system. These features are beneficial to the optimization of China’s energy consumption structure. Moreover, the operation of seasonal thermal storage for the ground soil is effective in maintaining the balance of soil annual heat. The control strategy combining geothermal and solar energies is recommended due to its good performance and high flexibility. This study may provide guidance in the development of DESs in hot summer and cold winter climate zones.

Suggested Citation

  • Yifang Tang & Zhiqiang Liu & Lan Li, 2019. "Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System," Energies, MDPI, vol. 12(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4613-:d:294294
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    References listed on IDEAS

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    1. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhai, Zhiqiang (John), 2011. "Performance comparison of combined cooling heating and power system in different operation modes," Applied Energy, Elsevier, vol. 88(12), pages 4621-4631.
    2. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    3. Calise, Francesco & Dentice d'Accadia, Massimo & Figaj, Rafal Damian & Vanoli, Laura, 2016. "A novel solar-assisted heat pump driven by photovoltaic/thermal collectors: Dynamic simulation and thermoeconomic optimization," Energy, Elsevier, vol. 95(C), pages 346-366.
    4. Pan, Yu & Liu, Liuchen & Zhu, Tong & Zhang, Tao & Zhang, Junying, 2017. "Feasibility analysis on distributed energy system of Chongming County based on RETScreen software," Energy, Elsevier, vol. 130(C), pages 298-306.
    5. 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.
    6. 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.
    7. Alanne, Kari & Saari, Arto, 2006. "Distributed energy generation and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(6), pages 539-558, December.
    8. Kang, Ligai & Yang, Junhong & An, Qingsong & Deng, Shuai & Zhao, Jun & Wang, Hui & Li, Zelin, 2017. "Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff," Applied Energy, Elsevier, vol. 194(C), pages 454-466.
    9. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    10. Cho, Heejin & Mago, Pedro J. & Luck, Rogelio & Chamra, Louay M., 2009. "Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme," Applied Energy, Elsevier, vol. 86(12), pages 2540-2549, December.
    11. 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.
    12. 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.
    13. Jung, Jaesung & Villaran, Michael, 2017. "Optimal planning and design of hybrid renewable energy systems for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 180-191.
    14. Wei, F. & Wu, Q.H. & Jing, Z.X. & Chen, J.J. & Zhou, X.X., 2016. "Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach," Energy, Elsevier, vol. 111(C), pages 933-946.
    15. Ren, Hongbo & Zhou, Weisheng & Gao, Weijun, 2012. "Optimal option of distributed energy systems for building complexes in different climate zones in China," Applied Energy, Elsevier, vol. 91(1), pages 156-165.
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