A hierarchical framework-based coordinated optimization of building HVAC systems and EVs
Abstract
The demands of electric vehicles (EVs) and building heating, ventilation, and air conditioning (HVAC) systems have considerable flexibility. Their flexibility is influenced by occupants’ behavior resulting in huge complementary and dispatchable capability. Therefore, the coordination of EVs and HVAC systems holds significant potential for optimizing the building demand profiles and energy cost under time-of-use (TOU) tariffs. However, solving the coordinated problem in practice still faces the challenges in computational complexity and global information requirement due to the spatio-temperal coupling constraints. In this paper, a mixed-integer linear programming model is developed to formulate the multi-building energy system with EVs and the impact of occupants’ behavior on the demand and flexibility of the system. The problem is converted into a three-level structure using Lagrangian relaxation framework. A dynamic programming-based Lagrangian relaxation (DPLR) algorithm is developed to independently solve all sub-problems of the three-level structure in a decomposition and coordination way while avoiding the iterative computation between the middle and lower level. The numerical results show the developed method can obtain a near-optimal solution in an efficient way without perceivable degradation in accuracy, which is 4% worse but at least three times faster, compared to the existing centralized algorithm. Note to Practitioners—The escalating demand for EVs and HVAC syst…
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Most mentioned studies overlook the potential benefits of an integrated DER environment, such as DERMS, where EVs could operate in coordination with other DERs to enhance overall grid stability and flexibility.
“Second, most studies overlook the potential benefits of an integrated DER environment, such as DERMS, where EVs could operate in coordination with other DERs to enhance overall grid stability and flexibility.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [22]
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- Authors
- Zhao, H., Xu, Z., Wu, J., Liu, F., & Guan, X.
- Affiliations
- Xi'an Jiaotong University (CN)
- Venue
- IEEE Transactions on Automation Science and Engineering
- Published
- 2025
- Volume
- 22
- Pages
- 6530-6542
- ISSN
- 1545-5955 (ISSN-L)
- 1558-3783
- OpenAlex
- W4402808109
- Cited by
- 8
- References
- 27
- Citations by year
- 2026: 5 · 2025: 3
- FWCI
- 0.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Automation Science and Engineering (publishedVersion)
- Funders
- National Natural Science Foundation of China (62122062, 62192755, 62192750, 62192752)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Keywords
- electric vehicle charging, HVAC systems, occupant behavior, time-of-use pricing, energy cost reduction, Lagrangian relaxation, hierarchical optimization, spatiotemporal coupling, decomposition and coordination
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