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Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network

Author

Listed:
  • Miao Li

    (School of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, China)

  • Yiran Feng

    (School of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, China)

  • Maojun Zhou

    (School of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, China)

  • Hailin Mu

    (Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Longxi Li

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Yajun Wang

    (School of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, China)

Abstract

The purpose of this research is to develop a mixed integer linear programming model for optimization of a distributed energy system integrated with electricity network. In this model, the optimal configuration of the selected equipment and dynamic intelligent control of the hourly electricity interchange among end-users were determined. The multi-objective function was to maximize the total cost saving and pollutant emission reduction. As an illustrative example, the model was applied to a neighborhood level containing hotel, office and residential buildings in Dalian, China. According to the results, with the installation of the electricity network, the load rate of the power generating unit in the hotel and office were improved and the power generate unit (PGU) often operated at full loads during the daytime with the surplus electricity distributed to the residential buildings. Furthermore, the overall performance was enhanced leading to a more than 30–40% reduction compared to the only distributed energy system (20–30%). In addition, the advancement of the electricity network was reflected in its application in office, where most of the excess electricity is transferred from office to residential building during the daytime in winter, while during the night time, the phenomenon was reversed, so that the office received electricity from residential buildings and no generated unit was at work in office.

Suggested Citation

  • Miao Li & Yiran Feng & Maojun Zhou & Hailin Mu & Longxi Li & Yajun Wang, 2019. "Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network," Energies, MDPI, vol. 12(10), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1844-:d:231353
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    References listed on IDEAS

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    1. Steffen Wehkamp & Lucas Schmeling & Lena Vorspel & Fabian Roelcke & Kai-Lukas Windmeier, 2020. "District Energy Systems: Challenges and New Tools for Planning and Evaluation," Energies, MDPI, vol. 13(11), pages 1-20, June.

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