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

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

Xiang Liao  1 , Jun Ma  1 , Bangli Yin  1 , Beibei Qian  1 , Runjie Lei  1 , Fu B  1 , Chaoshun Li  2
Affiliations

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

Xiang Liao et al. iScience. .

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Schematic diagram of FVCS-WPIES model
Figure 2
Figure 2
Schematic diagram of grid-connected FVCS-WPIES microgrid access
Figure 3
Figure 3
Number of EVs and HVs and power load
Figure 4
Figure 4
PV and WT power generation
Figure 5
Figure 5
Charging and discharging price of integrated energy station
Figure 6
Figure 6
Schematic diagram of BESS model
Figure 7
Figure 7
FVCS schematic
Figure 8
Figure 8
Pareto frontier of two models (A) FVCS-WPIES model. (B) Comparison model.
Figure 9
Figure 9
Two models objective functions (A) Total profit. (B) Total emission. (C) Battery loss.
Figure 10
Figure 10
Pre-distribution value of wind/PV for each module of the upper-level model
Figure 11
Figure 11
BCS module and HT module SOC state change diagram
Figure 12
Figure 12
Number of batteries in different states of charge in the BSS module at different times
Figure 13
Figure 13
BESS module and EV module power purchase by time period
Figure 14
Figure 14
EV and HV earnings by time period
Figure 15
Figure 15
Total charge and discharge of BESS module by time period
Figure 16
Figure 16
Wind and PV ratio of each sub-module (A) HT module. (B) BESS module. (C) EV module.
See this image and copyright information in PMC

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