Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings

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

doi:10.17775/CSEEJPES.2021.04510

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Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings

Regular Papers | 更新时间：2026-10-15

- Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings
- CSEE Journal of Power and Energy Systems Vol. 10, Issue 2, Pages: 504-517(2024)
- 作者机构：
  
  1. National Active Distribution Network Technology Research Center, Beijing Jiaotong University,Beijing,China
  2. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University,Tianjin,China
  3. Electrical and Computer Engineering, University of California, Riverside,CA,USA
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2021.04510
  CLC：
- Published：01 March 2024
- 稿件说明：
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Zening Li, Su Su, Xiaolong Jin, et al. Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 504-517.
DOI：

Zening Li, Su Su, Xiaolong Jin, et al. Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings[J]. CSEE Journal of Power and Energy Systems, 2024, 10(2): 504-517. DOI： 10.17775/CSEEJPES.2021.04510.

摘要

Abstract

This paper proposes a stochastic and distributed optimal energy management approach for active distribution networks (ADNs) within office buildings. The proposed approach aims at scheduling office buildings fitted with heating ventilation and air conditioning (HVAC) systems

and electric vehicle (EV) charging piles

to participate in the ADN optimization. First

an energy management approach for the ADN with aggregated office buildings is proposed. And the ADN optimization model is formulated considering the detailed building thermal dynamics and the mobile behaviors of workers. Then

to consider uncertainties of photovoltaic (PV) power

scenario-based stochastic programming is integrated into the ADN optimization model. To further realize the stochastic energy management of the ADN within office buildings in a distributed manner

the alternating direction method of multipliers (ADMM) is used to solve the ADN optimization model. The original ADN optimization problem is divided into the network-side and the building-side sub-problems to effectively protect the privacy of the ADN and the office buildings. Finally

the ADN optimization model incorporating office buildings is validated in the winter by numerical studies. In addition

the impacts of comfort temperature range and expected state of charge (SOC) at departure are analyzed.

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