Energy management for active distribution network incorporating office buildings based on chance-constrained programming

Su Su, Zening Li, Xiaolong Jin, Koji Yamashita, Mingchao Xia, Qifang Chen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Aiming to the more flexible operation of the active distribution network (ADN), an energy management method for ADN incorporating office buildings is proposed based on chance-constrained programming. First, based on the thermal dynamics of buildings, an energy consumption prediction model of office buildings with integrated thermostatically controlled loads (TCLs) is developed. Then, an optimal energy management strategy for the ADN is proposed through the branch flow model (BFM) and the second-order cone relaxation (SOCR), considering the constraints of the grid and office buildings. The chance-constrained programming is exploited to consider further the uncertainties of photovoltaic (PV) power and ambient temperature, and the optimization model of the ADN incorporating office buildings is reformulated as a mixed-integer second-order cone programming (MISOCP) problem, using the deterministic transformation of chance constraints. Finally, the impact of the office buildings with TCLs on the economic operation of the ADN is analyzed under different confidence levels in the winter heating scenario. Numerical studies justify that the lower confidence level capitalizes on the thermal storage characteristics of office buildings retaining the temperature comfort of office workers to attain the flexible operation of the ADN additionally.
Original languageEnglish
Article number107360
JournalInternational Journal of Electrical Power and Energy Systems
Volume134
Number of pages12
ISSN0142-0615
DOIs
Publication statusPublished - 2022

Keywords

  • Active distribution network (ADN)
  • Chance-constrained programming
  • Energy management
  • Office buildings
  • Thermostatically controlled loads (TCLs)

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