Distributed Operation for Integrated Electricity and Heat System With Hybrid Stochastic/Robust Optimization

Junjie Zhong, Yi Tan, Yong Li, Yijia Cao, Yanjian Peng, Zilong Zeng, Yosuke Nakanishi, Yicheng Zhou

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

With the wide application of combined heat and power (CHP) and power to heat (P2H) technology, the integrated electricity and heat system (IEHS) has been attracting great attention. The hybrid stochastic/robust optimization is combined to handle the uncertainties of IEHS, in which the stochastic optimization is concentrated on the uncertainties and spatial-temporal correlativity of load and wind power, while the robust optimization is used to deal with the market electricity price uncertainty. Considering the multi-entities characteristics of IEHS, the MINLP model of the original IEHS is decoupled to the one MILP power network and one NLP heat network based on the Bregman alternating direction method of multipliers (BADMM) and the improved quantity regulation. The simulation results show that the constructed model can effectively increase the flexibility of IEHS, and the uncertainty and spatial-temporal correlativity of IEHS can affect the system state. Furthermore, the proposed distributed model based on BADMM can not only improve the convergence effectively compared with traditional ADMM, but also realize the distributed cooperative operation of IEHS.

Original languageEnglish
Article number106680
JournalInternational Journal of Electrical Power and Energy Systems
Volume128
DOIs
Publication statusPublished - 2021 Jun

Keywords

  • Distributed operation
  • Improved quantity regulation
  • Integrated electricity and heat system
  • Robust optimization
  • Stochastic optimization

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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