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Controllable load operation in microgrids using control scheme based on gossip algorithm

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  • Krkoleva Mateska, Aleksandra
  • Borozan, Vesna
  • Krstevski, Petar
  • Taleski, Rubin

Abstract

The paper presents a novel control scheme for thermostatically controllable devices (TCDs) for application in Microgrids (MGs). It is implemented assuming that household controllable load is connected and interfaced with appropriate, commercially available equipment that allows communication. The work presented in this paper provides an integrated solution for continuous control of TCDs operation under normal MG operation as well as controlled change of TCDs states upon request of MG operator or aggregator. The solution is based on gossip algorithm (GSA) adapted for implementation in MGs. The simulation results of the proposed scheme show that its implementation facilitates MG operation control. The simulation results also show that it allows fast control message dissemination and adequate changes of operation of TCDs according the request of MG operator or an aggregator. The proposed control scheme also considers customer’s comfort and does not require customer’s continuous involvement in the control process.

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  • Krkoleva Mateska, Aleksandra & Borozan, Vesna & Krstevski, Petar & Taleski, Rubin, 2018. "Controllable load operation in microgrids using control scheme based on gossip algorithm," Applied Energy, Elsevier, vol. 210(C), pages 1336-1346.
    • Handle: RePEc:eee:appene:v:210:y:2018:i:c:p:1336-1346
    DOI: 10.1016/j.apenergy.2017.06.049
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    References listed on IDEAS

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    2. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Georghiou, George E., 2021. "Social arrangements, technical designs and impacts of energy communities: A review," Renewable Energy, Elsevier, vol. 169(C), pages 1138-1156.
    3. Xu, Fangyuan & Wu, Wanli & Zhao, Fei & Zhou, Ya & Wang, Yongjian & Wu, Runji & Zhang, Tao & Wen, Yongchen & Fan, Yiliang & Jiang, Shengli, 2019. "A micro-market module design for university demand-side management using self-crossover genetic algorithms," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

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