Hierarchical co-optimization of EV scheduling considering customer and system in distribution networks
Open accessAbstract
The global surge in the adoption of electric vehicles (EV) has affected distribution networks, with uncoordinated charging increasing peak load and loss. EV scheduling has the potential to become a business that utilizes vehicle-to-grid (V2G) technology to mitigate system impacts while providing financial incentives to customers. Efficient EV scheduling is a multi-objective optimization problem that simultaneously considers network and customer perspectives for co-optimization. This study introduces a hierarchical EV charging management platform (EVMP) with day-ahead and real-time stages that satisfy customer preferences while ensuring efficient system operation. In this process, in order to solve the computational issues of the optimal power flow (OPF) problem, including integer variables, the computational burden was alleviated by removing integer variables from the OPF problem of the day-ahead stage, and EV dynamics were effectively handled using the rolling-horizon framework in the real-time stage. This study focuses on the relationships between the objective functions at each stage and utilizes the augmented ɛ-constraint method (AUGMECON) to obtain a Pareto front that assists in stakeholder decision making. The Pareto front is constructed by considering stakeholders from both two- and three-way perspectives, allowing the system operator to select a solution from the Pareto front for decision making.
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Centralized solutions that require the DNO to collect information from all EVAs are only suitable for small and medium-sized resources.
“However, these methods are centralized solutions that require the DNO to collect in formation from all EVAs and are therefore only suitable for small and medium-sized resources.”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [15]
Studies in Refs [11 -17,19 -22] do not introduce a proper flexibility quantification method to effectively exploit the flexibility of EVs.
“Furthermore, the studies in Refs. [11 -17,19 -22] do not introduce a proper flexibility quantification method to effectively exploit the flexibility of EVs”
From Improving distribution system flexibility using electric vehicles under the distributed energy resource management system framework (2026) · cites this paper as [15]
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 [15]
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- Authors
- Cha, J., Han, C., Song, S., Kang, S., Lee, D., Chang, M., & Jang, G.
- Affiliations
- Korea University (KR)
- Gyeongsang National University (KR)
- Korea Electrotechnology Research Institute (KR)
- Corresponding author
- Jang, Gilsoo
- Venue
- Sustainable Energy, Grids and Networks
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 38
- Pages
- 101361
- ISSN
- 2352-4677 (ISSN-L)
- OpenAlex
- W4393181168
- Cited by
- 14
- References
- 34
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 4
- FWCI
- 1.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Sustainable Energy Grids and Networks (publishedVersion, cc-by-nc)
- Funders
- National Research Foundation of Korea
- Nuclear Safety and Security Commission
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Keywords
- electric vehicle scheduling, EV charging management, distribution networks, vehicle-to-grid, hierarchical optimization, rolling horizon, augmented epsilon-constraint method, Pareto front, multi-objective optimization, optimal power flow, consumer preferences, peak shaving, network loss reduction
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