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Adaptive Consensus Algorithm for Distributed Heat-Electricity Energy Management of an Islanded Microgrid

Author

Listed:
  • Xiaofeng Dong

    (Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100000, China
    State Grid Suzhou Power Supply Company, Suzhou 215004, China)

  • Xiaoshun Zhang

    (College of Engineering, Shantou University, Shantou 515000, China)

  • Tong Jiang

    (Department of Electrical and Electronic Engineering, North China Electric Power University, Beijing 100000, China)

Abstract

This paper proposes a novel adaptive consensus algorithm (ACA) for distributed heat-electricity energy management (HEEM) of an islanded microgrid. In order to simultaneously satisfy the heat-electricity energy balance constraints, ACA is implemented with a switch between unified consensus and independent consensus according to the dynamic energy mismatches. The feasible operation region of a combined heat and power (CHP) unit is decomposed into eight searching sub-regions, thus its electricity and heat energy outputs can simultaneously match the incremental cost consensus requirement and the heat-electricity energy balance constraints. Case studies are thoroughly carried out to verify the performance of ACA for distributed HEEM of an islanded microgrid.

Suggested Citation

  • Xiaofeng Dong & Xiaoshun Zhang & Tong Jiang, 2018. "Adaptive Consensus Algorithm for Distributed Heat-Electricity Energy Management of an Islanded Microgrid," Energies, MDPI, vol. 11(9), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2236-:d:165878
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    References listed on IDEAS

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    1. Ibrahim Alsaidan & Abdulaziz Alanazi & Wenzhong Gao & Hongyu Wu & Amin Khodaei, 2017. "State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing," Energies, MDPI, vol. 10(9), pages 1-14, September.
    2. Hak-Man Kim & Yujin Lim & Tetsuo Kinoshita, 2012. "An Intelligent Multiagent System for Autonomous Microgrid Operation," Energies, MDPI, vol. 5(9), pages 1-16, September.
    3. Guanglin Zhang & Yu Cao & Yongsheng Cao & Demin Li & Lin Wang, 2017. "Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources," Energies, MDPI, vol. 10(9), pages 1-18, August.
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    Cited by:

    1. Abdul Latif & S. M. Suhail Hussain & Dulal Chandra Das & Taha Selim Ustun, 2020. "Optimum Synthesis of a BOA Optimized Novel Dual-Stage PI − (1 + ID) Controller for Frequency Response of a Microgrid," Energies, MDPI, vol. 13(13), pages 1-12, July.
    2. Masoud Babaei & Ahmadreza Abazari & S. M. Muyeen, 2020. "Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid," Energies, MDPI, vol. 13(2), pages 1-23, January.
    3. Yang, Kang & Li, Chunhua & Jing, Xu & Zhu, Zhiyu & Wang, Yuting & Ma, Haodong & Zhang, Yu, 2022. "Energy dispatch optimization of islanded multi-microgrids based on symbiotic organisms search and improved multi-agent consensus algorithm," Energy, Elsevier, vol. 239(PC).
    4. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

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