Robustly Optimal Operation in Grid‐Interactive Efficient Buildings Facilitating Small‐Signal Stability

ABSTRACT Grid‐interactive efficient buildings (GEBs) have garnered global attention for their ability to achieve flexible, resilient, and environmentally friendly objectives. However, the increasing integration of renewable energy sources (RESs) introduces challenges which can compromise power system stability. Traditional robust energy management approaches fall short as they fail to address the adverse impacts on small‐signal stability. Additionally, the complexity of coordinating diverse devices and their intricate interactions leave the concept of co‐optimization in GEBs in its nascent stages. To address these challenges, this paper proposes a robust optimization model for GEBs that minimizes costs while ensuring system stability. The model integrates adjustable droop gains in inverters connected to distributed energy resources (DERs). First, dynamic models for various GEB devices are developed. Next, an hourly optimal power flow problem is formulated using interval predictions for RESs to ensure robustness against uncertainties. Leveraging a polyhedral uncertainty set, the model is solved via a Benders decomposition‐based method, incorporating analytical stability sensitivity cuts. Simulations on a 33‐bus GEB demonstrate that the proposed model significantly enhances small‐signal stability at a relatively low cost, outperforming benchmark models in handling uncertainties. This approach marks a significant step forward in advancing the co‐optimization of energy management and stability in GEBs.

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Publication Details

Journal
IET Renewable Power Generation
Published
2025-01-01
DOI
https://doi.org/10.1049/rpg2.70056
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Robustly Optimal Operation in Grid‐Interactive Efficient Buildings Facilitating Small‐Signal Stability

Yunhe Hou, Xiaodong Zheng, Nengling Tai, Jun Wang et al.
IET Renewable Power Generation
Distributed and Parallel Computing Systems
article

Robustly Optimal Operation in Grid‐Interactive Efficient Buildings Facilitating Small‐Signal Stability

Yunhe Hou, Xiaodong Zheng, Nengling Tai, Jun Wang, Weibin Li, Qiyu Lu, Wei Bao
article en

Abstract

ABSTRACT Grid‐interactive efficient buildings (GEBs) have garnered global attention for their ability to achieve flexible, resilient, and environmentally friendly objectives. However, the increasing integration of renewable energy sources (RESs) introduces challenges which can compromise power system stability. Traditional robust energy management approaches fall short as they fail to address the adverse impacts on small‐signal stability. Additionally, the complexity of coordinating diverse devices and their intricate interactions leave the concept of co‐optimization in GEBs in its nascent stages. To address these challenges, this paper proposes a robust optimization model for GEBs that minimizes costs while ensuring system stability. The model integrates adjustable droop gains in inverters connected to distributed energy resources (DERs). First, dynamic models for various GEB devices are developed. Next, an hourly optimal power flow problem is formulated using interval predictions for RESs to ensure robustness against uncertainties. Leveraging a polyhedral uncertainty set, the model is solved via a Benders decomposition‐based method, incorporating analytical stability sensitivity cuts. Simulations on a 33‐bus GEB demonstrate that the proposed model significantly enhances small‐signal stability at a relatively low cost, outperforming benchmark models in handling uncertainties. This approach marks a significant step forward in advancing the co‐optimization of energy management and stability in GEBs.

IET Renewable Power GenerationVol. 19(1)
Shanghai Jiao Tong University (CN), University of Hong Kong (HK)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 89%
Distributed and Parallel Computing Systems
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