Many-objective bi-level energy scheduling method for integrated energy stations based on power allocation strategy

Xiang Liao; Jun Ma; Bangli Yin; Beibei Qian; Runjie Lei; Fu B; Chaoshun Li

doi:10.1016/j.isci.2024.109305

Many-objective bi-level energy scheduling method for integrated energy stations based on power allocation strategy

iScience. 2024 Feb 23;27(3):109305. doi: 10.1016/j.isci.2024.109305. eCollection 2024 Mar 15.

Authors

Xiang Liao¹, Jun Ma¹, Bangli Yin¹, Beibei Qian¹, Runjie Lei¹, Fu B¹, Chaoshun Li²

Affiliations

¹ Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China.
² Huazhong University Sci & Technol, Coll Hydroelect Digitizat Engn, Huazhong University of Science & Technology, Wuhan 430074, China.

Abstract

The integrated energy station of new energy vehicle hydrogenation/charging/power exchange is proposed, which also includes hydrogen production, hydrogen storage, electricity sales to users and the grid (WPIES). To address the efficiency of renewable energy use, this paper proposes a future value competition strategy for wind and photovoltaic (PV) allocation based on goal optimization (FVCS). In order to better realize the distribution of wind power/PV in the integrated energy station and improve the energy utilization efficiency of the integrated energy station, a two-layer optimization model of FVCS-WPIES is proposed, in which the upper layer model aims to maximize the expected income. The goals of the lower-level model are to maximize total profit, minimize battery losses, and minimize pollutant emissions. The model also considers the hydrogen power constraint and the upper-level model penalty. The comparison results show that the Pareto solution set is superior to the traditional model.

Keywords: Energy Modelling; Energy management; Energy systems.