Decentralized Robust Energy and Reserve Co-optimization for Multiple Integrated Electricity and Heating Systems

Jin Tan, Qiuwei Wu, Wei Wei, Feng Liu, Canbing Li, Bin Zhou

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The growing uncertainty caused by the increasing wind power penetration brings an urgent need of increased reserve capacity to ensure the secure operation of power systems. The interconnection of multiple integrated electricity and heating systems (IEHSs) allows resource sharing among them and the district heating system can provide additional reserves to the electric power system. In this paper, a decentralized robust energy and reserve co-optimization for multiple IEHSs is proposed to handle wind power uncertainty in a more economic and efficient way. In each IEHS, the day-ahead energy and reserve scheduling is formulated as a two-stage adaptive robust optimization, where the feasibility of day-ahead reserve deployment in the real-time operation is guaranteed. Then, a decentralized methodology is developed based on the alternating direction method of multipliers (ADMM) to achieve the synergistic yet independent operation by exchanging tie-line power flows with adjacent IEHSs. In order to accelerate the convergence of the decentralized operation and reduce the communication demand, the improved ADMM with locally adaptive penalty parameters is adopted. Simulation results demonstrate the effectiveness of the proposed decentralized robust energy and reserve optimization scheme in terms of improving the economic efficiency and ensuring the secure operation for IEHSs, as well as preserving information privacy
Original languageEnglish
Article number118040
Publication statusPublished - 2020


  • Adaptive robust optimization
  • Energy and reserve co-optimization
  • Improved ADMM algorithm
  • Integrated electricity and heating


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