Stochastic planning of energy hub considering demand response and electric vehicles with Stackelberg game

In this study, we present a stochastic planning model for the planning and operation of a grid-interactive energy hub. The model emphasises demand response (DR) and Vehicle-to-Grid (V2G) technology. We explored the behavioural model of electric vehicles (EVs) to achieve optimal planning, energy efficiency improvement, and optimal interaction with the grid for energy hubs by simulating the impact of EVs' one-day charging and discharging behaviour on energy hub planning and operation, in conjunction with the construction of mathematical models for photovoltaic (PV), combined heat and power unit (CHP), and absorption chiller (AC) equipment. Through model optimisation, we analyse the operation of the energy hub under different dispatch schemes. The results show that the integrated consideration of DR and EV reverse discharge can reduce the investment cost of the energy hub equipment by 2.6%, improve the energy utilisation efficiency, and facilitate the ‘peak shaving and valley filling’ of the grid. The results provide a theoretical basis and practical guidance for the planning and operation of energy hubs.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0376
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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article

Stochastic planning of energy hub considering demand response and electric vehicles with Stackelberg game

Song Wu, Shuaijia He, Hong‐Jun Gao, Yufan Wang
1 citations
IET conference proceedings.
Electric Vehicles and Infrastructure
0.73
article

Stochastic planning of energy hub considering demand response and electric vehicles with Stackelberg game

Song Wu, Shuaijia He, Hong‐Jun Gao, Yufan Wang
article en
1 citations

Abstract

In this study, we present a stochastic planning model for the planning and operation of a grid-interactive energy hub. The model emphasises demand response (DR) and Vehicle-to-Grid (V2G) technology. We explored the behavioural model of electric vehicles (EVs) to achieve optimal planning, energy efficiency improvement, and optimal interaction with the grid for energy hubs by simulating the impact of EVs' one-day charging and discharging behaviour on energy hub planning and operation, in conjunction with the construction of mathematical models for photovoltaic (PV), combined heat and power unit (CHP), and absorption chiller (AC) equipment. Through model optimisation, we analyse the operation of the energy hub under different dispatch schemes. The results show that the integrated consideration of DR and EV reverse discharge can reduce the investment cost of the energy hub equipment by 2.6%, improve the energy utilisation efficiency, and facilitate the ‘peak shaving and valley filling’ of the grid. The results provide a theoretical basis and practical guidance for the planning and operation of energy hubs.

IET conference proceedings.Vol. 2024(33)
Sichuan University (CN)
Affordable and clean energy
Openalex Percentile: Top 31%
Electric Vehicles and Infrastructure
0.73
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Stochastic planning of energy hub considering demand response and electric vehicles with Stackelberg game — Song Wu, Shuaijia He, et al. · IET conference proceedings. (2025) | TGRS Research Map | TGRS