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Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response

Author

Listed:
  • Yongli Wang

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Yujing Huang

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Yudong Wang

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Fang Li

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Yuanyuan Zhang

    (School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China)

  • Chunzheng Tian

    (State Grid Henan Economic Research Institute, Zhenzhou 450000, China)

Abstract

With the application of distributed generation and the development of smart grid technology, micro-grid, an economic and stable power grid, tends to play an important role in the demand side management. Because micro-grid technology and demand response have been widely applied, what Demand Response actions can realize the economic operation of micro-grid has become an important issue for utilities. In this proposed work, operation optimization modeling for micro-grid is done considering distributed generation, environmental factors and demand response. The main contribution of this model is to optimize the cost in the context of considering demand response and system operation. The presented optimization model can reduce the operation cost of micro-grid without bringing discomfort to the users, thus increasing the consumption of clean energy effectively. Then, to solve this operational optimization problem, genetic algorithm is used to implement objective function and DR scheduling strategy. In addition, to validate the proposed model, it is employed on a smart micro-grid from Tianjin. The obtained numerical results clearly indicate the impact of demand response on economic operation of micro-grid and development of distributed generation. Besides, a sensitivity analysis on the natural gas price is implemented according to the situation of China, and the result shows that the natural gas price has a great influence on the operation cost of the micro-grid and effect of demand response.

Suggested Citation

  • Yongli Wang & Yujing Huang & Yudong Wang & Fang Li & Yuanyuan Zhang & Chunzheng Tian, 2018. "Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response," Sustainability, MDPI, vol. 10(3), pages 1-25, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:847-:d:136698
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    Citations

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    Cited by:

    1. Silvia Jiménez-Fernández & Carlos Camacho-Gómez & Ricardo Mallol-Poyato & Juan Carlos Fernández & Javier Del Ser & Antonio Portilla-Figueras & Sancho Salcedo-Sanz, 2018. "Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm," Sustainability, MDPI, vol. 11(1), pages 1-21, December.
    2. Jong-Chan Kim & Jun-Ho Huh & Jae-Sub Ko, 2020. "Optimization Design and Test Bed of Fuzzy Control Rule Base for PV System MPPT in Micro Grid," Sustainability, MDPI, vol. 12(9), pages 1-25, May.
    3. Arash Moradzadeh & Sahar Zakeri & Maryam Shoaran & Behnam Mohammadi-Ivatloo & Fazel Mohammadi, 2020. "Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    4. Wang, Yongli & Li, Ruiwen & Dong, Huanran & Ma, Yuze & Yang, Jiale & Zhang, Fuwei & Zhu, Jinrong & Li, Shuqing, 2019. "Capacity planning and optimization of business park-level integrated energy system based on investment constraints," Energy, Elsevier, vol. 189(C).
    5. Nikolaos Kolokas & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "Multi-Step Energy Demand and Generation Forecasting with Confidence Used for Specification-Free Aggregate Demand Optimization," Energies, MDPI, vol. 14(11), pages 1-36, May.
    6. Yuquan Meng & Yuhang Yang & Haseung Chung & Pil-Ho Lee & Chenhui Shao, 2018. "Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review," Sustainability, MDPI, vol. 10(12), pages 1-28, December.
    7. Francisco David Moya & José Luis Torres-Moreno & José Domingo Álvarez, 2020. "Optimal Model for Energy Management Strategy in Smart Building with Energy Storage Systems and Electric Vehicles," Energies, MDPI, vol. 13(14), pages 1-18, July.
    8. Xiaohui Yang & Jiating Long & Peiyun Liu & Xiaolong Zhang & Xiaoping Liu, 2018. "Optimal Scheduling of Microgrid with Distributed Power Based on Water Cycle Algorithm," Energies, MDPI, vol. 11(9), pages 1-17, September.
    9. Danyang Guo & Jilai Yu & Mingfei Ban, 2018. "Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    10. Simona-Vasilica Oprea & Adela Bâra & Adina Ileana Uță & Alexandru Pîrjan & George Căruțașu, 2018. "Analyses of Distributed Generation and Storage Effect on the Electricity Consumption Curve in the Smart Grid Context," Sustainability, MDPI, vol. 10(7), pages 1-25, July.
    11. Kalim Ullah & Quanyuan Jiang & Guangchao Geng & Rehan Ali Khan & Sheraz Aslam & Wahab Khan, 2022. "Optimization of Demand Response and Power-Sharing in Microgrids for Cost and Power Losses," Energies, MDPI, vol. 15(9), pages 1-22, April.
    12. Abbas Rabiee & Ali Abdali & Seyed Masoud Mohseni-Bonab & Mohsen Hazrati, 2021. "Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources," Sustainability, MDPI, vol. 13(13), pages 1-24, June.
    13. Máximo A. Domínguez-Garabitos & Víctor S. Ocaña-Guevara & Félix Santos-García & Adriana Arango-Manrique & Miguel Aybar-Mejía, 2022. "A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market," Energies, MDPI, vol. 15(4), pages 1-28, February.
    14. David García Elvira & Hugo Valderrama Blaví & Àngel Cid Pastor & Luis Martínez Salamero, 2018. "Efficiency Optimization of a Variable Bus Voltage DC Microgrid," Energies, MDPI, vol. 11(11), pages 1-21, November.
    15. Yongli Wang & Haiyang Yu & Mingyue Yong & Yujing Huang & Fuli Zhang & Xiaohai Wang, 2018. "Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss," Energies, MDPI, vol. 11(7), pages 1-21, June.

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