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Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost

Author

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  • Xiuyun Wang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, Jilin, China)

  • Shaoxin Chen

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, Jilin, China)

  • Yibing Zhou

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, Jilin, China)

  • Jian Wang

    (State Grid Sanmenxia Power Supply Company, Sanmenxia 472000, Henan, China)

  • Yang Cui

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, Jilin, China)

Abstract

With the rapid development of wind power generation and photovoltaic power generation, the phenomenon of wind and solar abandoning becomes more and more serious in the operation of power systems, and the microgrid is a new operating mode of power systems which provides a new consumption mode for wind power generation. With the increasingly close connection among energy resources and people’s increasing awareness of environmental protection, this paper establishes a microgrid optimal scheduling model with a combined heat and power system, in consideration of environmental costs. This model aims at the lowest comprehensive cost, at the same time taking into account the emission reductions of SO 2 and NO x , considering the cost of power generated by the micro-generator, environmental cost, the related cost of battery, operation and maintenance cost of wind power, and photovoltaic power generation. The related constraints of thermal balance and power balance are also considered during microgrid system operation. The established model is solved with an improved particle swarm algorithm. At last, taking a microgrid system as an example, the validity and reliability of the proposed model are verified.

Suggested Citation

  • Xiuyun Wang & Shaoxin Chen & Yibing Zhou & Jian Wang & Yang Cui, 2018. "Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost," Energies, MDPI, vol. 11(10), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2493-:d:170963
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    References listed on IDEAS

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    Cited by:

    1. Byeong-Cheol Jeong & Dong-Hwan Shin & Jae-Beom Im & Jae-Young Park & Young-Jin Kim, 2019. "Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid," Energies, MDPI, vol. 12(6), pages 1-20, March.
    2. F. Daniel Santillán-Lemus & Hertwin Minor-Popocatl & Omar Aguilar-Mejía & Ruben Tapia-Olvera, 2019. "Optimal Economic Dispatch in Microgrids with Renewable Energy Sources," Energies, MDPI, vol. 12(1), pages 1-14, January.
    3. Guangyi Wu & Xiangxin Shao & Hong Jiang & Shaoxin Chen & Yibing Zhou & Hongyang Xu, 2020. "Control Strategy of the Pumped Storage Unit to Deal with the Fluctuation of Wind and Photovoltaic Power in Microgrid," Energies, MDPI, vol. 13(2), pages 1-23, January.
    4. Lingling Li & Jiarui Pei & Qiang Shen, 2023. "A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids," Energies, MDPI, vol. 16(10), pages 1-23, May.
    5. Omid Sadeghian & Arash Moradzadeh & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Fausto Pedro Garcia Marquez, 2020. "Generation Units Maintenance in Combined Heat and Power Integrated Systems Using the Mixed Integer Quadratic Programming Approach," Energies, MDPI, vol. 13(11), pages 1-25, June.
    6. Abunima, Hamza & Park, Woan-Ho & Glick, Mark B. & Kim, Yun-Su, 2022. "Two-Stage stochastic optimization for operating a Renewable-Based Microgrid," Applied Energy, Elsevier, vol. 325(C).

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